From 866f54da8d7eed41a0554648aef8cf213551ee59 Mon Sep 17 00:00:00 2001 From: Chenlei Hu Date: Mon, 24 Jun 2024 14:47:28 -0400 Subject: [PATCH 001/133] Add browser test action synced with TS repo (#3852) * Add browser test action * Add npm install task --- .github/workflows/test-browser.yml | 61 ++++++++++++++++++++++++++++++ 1 file changed, 61 insertions(+) create mode 100644 .github/workflows/test-browser.yml diff --git a/.github/workflows/test-browser.yml b/.github/workflows/test-browser.yml new file mode 100644 index 000000000..049b1cde2 --- /dev/null +++ b/.github/workflows/test-browser.yml @@ -0,0 +1,61 @@ +# This is a temporary action during frontend TS migration. +# This file should be removed after TS migration is completed. +# The browser test is here to ensure TS repo is working the same way as the +# current JS code. +# If you are adding UI feature, please sync your changes to the TS repo: +# huchenlei/ComfyUI_frontend and update test expectation files accordingly. +name: Playwright Browser Tests CI + +on: + pull_request: + branches: [ main, master ] + +jobs: + test: + runs-on: ubuntu-latest + steps: + - name: Checkout ComfyUI + uses: actions/checkout@v4 + with: + repository: "comfyanonymous/ComfyUI" + path: "ComfyUI" + - name: Checkout ComfyUI_frontend + uses: actions/checkout@v4 + with: + repository: "huchenlei/ComfyUI_frontend" + path: "ComfyUI_frontend" + ref: "23a4ee83144d9bf22e7218b9c78c71f8544c8b27" + - uses: actions/setup-node@v3 + with: + node-version: lts/* + - uses: actions/setup-python@v4 + with: + python-version: '3.10' + - name: Install requirements + run: | + python -m pip install --upgrade pip + pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu + pip install -r requirements.txt + pip install wait-for-it + working-directory: ComfyUI + - name: Start ComfyUI server + run: | + python main.py --cpu & + wait-for-it --service 127.0.0.1:8188 -t 600 + working-directory: ComfyUI + - name: Install ComfyUI_frontend dependencies + run: | + npm ci + working-directory: ComfyUI_frontend + - name: Install Playwright Browsers + run: npx playwright install --with-deps + working-directory: ComfyUI_frontend + - name: Run Playwright tests + run: npx playwright test + working-directory: ComfyUI_frontend + - uses: actions/upload-artifact@v4 + if: always() + with: + name: playwright-report + path: ComfyUI_frontend/playwright-report/ + retention-days: 30 From eab211bb1e79fbda0b8eef00e44249993c040ae0 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Mon, 24 Jun 2024 16:55:20 -0400 Subject: [PATCH 002/133] Resample audio to 44100 when VAE encoding it. --- comfy_extras/nodes_audio.py | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/comfy_extras/nodes_audio.py b/comfy_extras/nodes_audio.py index 5f4bd3540..57d0a20ab 100644 --- a/comfy_extras/nodes_audio.py +++ b/comfy_extras/nodes_audio.py @@ -31,7 +31,13 @@ class VAEEncodeAudio: CATEGORY = "_for_testing/audio" def encode(self, vae, audio): - t = vae.encode(audio["waveform"].movedim(1, -1)) + sample_rate = audio["sample_rate"] + if 44100 != sample_rate: + waveform = torchaudio.functional.resample(audio["waveform"], sample_rate, 44100) + else: + waveform = audio["waveform"] + + t = vae.encode(waveform.movedim(1, -1)) return ({"samples":t}, ) class VAEDecodeAudio: From 90aebb6c868d713c3e6457d1474c53808cb5f6a2 Mon Sep 17 00:00:00 2001 From: pythongosssss <125205205+pythongosssss@users.noreply.github.com> Date: Tue, 25 Jun 2024 11:49:25 +0100 Subject: [PATCH 003/133] New Menu & Workflow Management (#3112) * menu * wip * wip * wip * wip * wip * workflow saving/loading * Support inserting workflows Move buttosn to top of lists * fix session storage implement renaming * temp * refactor, better workflow instance management * wip * progress on progress * added send to workflow various fixes * Support multiple image loaders * Support dynamic size breakpoints based on content * various fixes add close unsaved warning * Add filtering tree * prevent renaming unsaved * fix zindex on hover * fix top offset * use filename as workflow name * resize on setting change * hide element until it is drawn * remove glow * Fix export name * Fix test, revert accidental changes to groupNode * Fix colors on all themes * show hover items on smaller screen (mobile) * remove debugging code * dialog fix * Dont reorder open workflows Allow elements around canvas * Toggle body display on setting change * Fix menu disappearing on chrome * Increase delay when typing, remove margin on Safari, fix dialog location * Fix overflow issue on iOS * Add reset view button Prevent view changes causing history entries * Bottom menu wip * Various fixes * Fix merge * Fix breaking old menu position * Fix merge adding restore view to loadGraphData --- app/user_manager.py | 91 ++- tests-ui/utils/setup.js | 1 + web/extensions/core/colorPalette.js | 30 +- web/extensions/core/groupNode.js | 2 +- web/extensions/core/undoRedo.js | 177 ----- web/fonts/materialdesignicons-webfont.woff2 | Bin 0 -> 403216 bytes web/index.html | 1 + web/jsconfig.json | 4 +- web/lib/materialdesignicons.min.css | 3 + web/scripts/api.js | 75 +- web/scripts/app.js | 223 ++++-- web/scripts/changeTracker.js | 242 +++++++ web/scripts/domWidget.js | 14 +- web/scripts/ui.js | 34 +- web/scripts/ui/components/asyncDialog.js | 64 ++ web/scripts/ui/components/button.js | 163 +++++ web/scripts/ui/components/buttonGroup.js | 45 ++ web/scripts/ui/components/popup.js | 128 ++++ web/scripts/ui/components/splitButton.js | 43 ++ web/scripts/ui/dialog.js | 28 +- web/scripts/ui/menu/index.js | 302 ++++++++ web/scripts/ui/menu/interruptButton.js | 23 + web/scripts/ui/menu/menu.css | 701 ++++++++++++++++++ web/scripts/ui/menu/queueButton.js | 93 +++ web/scripts/ui/menu/queueOptions.js | 77 ++ web/scripts/ui/menu/viewHistory.js | 27 + web/scripts/ui/menu/viewList.js | 203 ++++++ web/scripts/ui/menu/viewQueue.js | 55 ++ web/scripts/ui/menu/workflows.js | 764 ++++++++++++++++++++ web/scripts/ui/settings.js | 20 +- web/scripts/ui/utils.js | 56 ++ web/scripts/utils.js | 68 ++ web/scripts/workflows.js | 450 ++++++++++++ web/style.css | 75 ++ web/types/comfy.d.ts | 16 +- 35 files changed, 3986 insertions(+), 312 deletions(-) delete mode 100644 web/extensions/core/undoRedo.js create mode 100644 web/fonts/materialdesignicons-webfont.woff2 create mode 100644 web/lib/materialdesignicons.min.css create mode 100644 web/scripts/changeTracker.js create mode 100644 web/scripts/ui/components/asyncDialog.js create mode 100644 web/scripts/ui/components/button.js create mode 100644 web/scripts/ui/components/buttonGroup.js create mode 100644 web/scripts/ui/components/popup.js create mode 100644 web/scripts/ui/components/splitButton.js create mode 100644 web/scripts/ui/menu/index.js create mode 100644 web/scripts/ui/menu/interruptButton.js create mode 100644 web/scripts/ui/menu/menu.css create mode 100644 web/scripts/ui/menu/queueButton.js create mode 100644 web/scripts/ui/menu/queueOptions.js create mode 100644 web/scripts/ui/menu/viewHistory.js create mode 100644 web/scripts/ui/menu/viewList.js create mode 100644 web/scripts/ui/menu/viewQueue.js create mode 100644 web/scripts/ui/menu/workflows.js create mode 100644 web/scripts/ui/utils.js create mode 100644 web/scripts/workflows.js diff --git a/app/user_manager.py b/app/user_manager.py index 209094af1..53dff18b7 100644 --- a/app/user_manager.py +++ b/app/user_manager.py @@ -2,6 +2,8 @@ import json import os import re import uuid +import glob +import shutil from aiohttp import web from comfy.cli_args import args from folder_paths import user_directory @@ -56,16 +58,16 @@ class UserManager(): if os.path.commonpath((root_dir, user_root)) != root_dir: return None - parent = user_root - if file is not None: # prevent leaving /{type}/{user} path = os.path.abspath(os.path.join(user_root, file)) if os.path.commonpath((user_root, path)) != user_root: return None + parent = os.path.split(path)[0] + if create_dir and not os.path.exists(parent): - os.mkdir(parent) + os.makedirs(parent, exist_ok=True) return path @@ -108,33 +110,96 @@ class UserManager(): user_id = self.add_user(username) return web.json_response(user_id) - @routes.get("/userdata/{file}") - async def getuserdata(request): - file = request.match_info.get("file", None) - if not file: + @routes.get("/userdata") + async def listuserdata(request): + directory = request.rel_url.query.get('dir', '') + if not directory: return web.Response(status=400) - path = self.get_request_user_filepath(request, file) + path = self.get_request_user_filepath(request, directory) if not path: return web.Response(status=403) if not os.path.exists(path): return web.Response(status=404) - return web.FileResponse(path) + recurse = request.rel_url.query.get('recurse', '').lower() == "true" + results = glob.glob(os.path.join( + glob.escape(path), '**/*'), recursive=recurse) + results = [os.path.relpath(x, path) for x in results if os.path.isfile(x)] + + split_path = request.rel_url.query.get('split', '').lower() == "true" + if split_path: + results = [[x] + x.split(os.sep) for x in results] - @routes.post("/userdata/{file}") - async def post_userdata(request): - file = request.match_info.get("file", None) + return web.json_response(results) + + def get_user_data_path(request, check_exists = False, param = "file"): + file = request.match_info.get(param, None) if not file: return web.Response(status=400) path = self.get_request_user_filepath(request, file) if not path: return web.Response(status=403) + + if check_exists and not os.path.exists(path): + return web.Response(status=404) + + return path + + @routes.get("/userdata/{file}") + async def getuserdata(request): + path = get_user_data_path(request, check_exists=True) + if not isinstance(path, str): + return path + + return web.FileResponse(path) + + @routes.post("/userdata/{file}") + async def post_userdata(request): + path = get_user_data_path(request) + if not isinstance(path, str): + return path + + overwrite = request.query["overwrite"] != "false" + if not overwrite and os.path.exists(path): + return web.Response(status=409) body = await request.read() + with open(path, "wb") as f: f.write(body) - return web.Response(status=200) + resp = os.path.relpath(path, self.get_request_user_filepath(request, None)) + return web.json_response(resp) + + @routes.delete("/userdata/{file}") + async def delete_userdata(request): + path = get_user_data_path(request, check_exists=True) + if not isinstance(path, str): + return path + + os.remove(path) + + return web.Response(status=204) + + @routes.post("/userdata/{file}/move/{dest}") + async def move_userdata(request): + source = get_user_data_path(request, check_exists=True) + if not isinstance(source, str): + return source + + dest = get_user_data_path(request, check_exists=False, param="dest") + if not isinstance(source, str): + return dest + + overwrite = request.query["overwrite"] != "false" + if not overwrite and os.path.exists(dest): + return web.Response(status=409) + + print(f"moving '{source}' -> '{dest}'") + shutil.move(source, dest) + + resp = os.path.relpath(dest, self.get_request_user_filepath(request, None)) + return web.json_response(resp) diff --git a/tests-ui/utils/setup.js b/tests-ui/utils/setup.js index e46258943..3a6d69b72 100644 --- a/tests-ui/utils/setup.js +++ b/tests-ui/utils/setup.js @@ -72,6 +72,7 @@ export function mockApi(config = {}) { storeUserData: jest.fn((file, data) => { userData[file] = data; }), + listUserData: jest.fn(() => []) }; jest.mock("../../web/scripts/api", () => ({ get api() { diff --git a/web/extensions/core/colorPalette.js b/web/extensions/core/colorPalette.js index 02546782f..245f3b93e 100644 --- a/web/extensions/core/colorPalette.js +++ b/web/extensions/core/colorPalette.js @@ -63,6 +63,10 @@ const colorPalettes = { "border-color": "#4e4e4e", "tr-even-bg-color": "#222", "tr-odd-bg-color": "#353535", + "content-bg": "#4e4e4e", + "content-fg": "#fff", + "content-hover-bg": "#222", + "content-hover-fg": "#fff" } }, }, @@ -120,6 +124,10 @@ const colorPalettes = { "border-color": "#888", "tr-even-bg-color": "#f9f9f9", "tr-odd-bg-color": "#fff", + "content-bg": "#e0e0e0", + "content-fg": "#222", + "content-hover-bg": "#adadad", + "content-hover-fg": "#222" } }, }, @@ -176,6 +184,10 @@ const colorPalettes = { "border-color": "#657b83", // Base00 "tr-even-bg-color": "#002b36", "tr-odd-bg-color": "#073642", + "content-bg": "#657b83", + "content-fg": "#fdf6e3", + "content-hover-bg": "#002b36", + "content-hover-fg": "#fdf6e3" } }, }, @@ -244,7 +256,11 @@ const colorPalettes = { "error-text": "#ff4444", "border-color": "#6e7581", "tr-even-bg-color": "#2b2f38", - "tr-odd-bg-color": "#242730" + "tr-odd-bg-color": "#242730", + "content-bg": "#6e7581", + "content-fg": "#fff", + "content-hover-bg": "#2b2f38", + "content-hover-fg": "#fff" } }, }, @@ -313,7 +329,11 @@ const colorPalettes = { "error-text": "#ff4444", "border-color": "#545d70", "tr-even-bg-color": "#2e3440", - "tr-odd-bg-color": "#161b22" + "tr-odd-bg-color": "#161b22", + "content-bg": "#545d70", + "content-fg": "#e5eaf0", + "content-hover-bg": "#2e3440", + "content-hover-fg": "#e5eaf0" } }, }, @@ -382,7 +402,11 @@ const colorPalettes = { "error-text": "#ff4444", "border-color": "#30363d", "tr-even-bg-color": "#161b22", - "tr-odd-bg-color": "#13171d" + "tr-odd-bg-color": "#13171d", + "content-bg": "#30363d", + "content-fg": "#e5eaf0", + "content-hover-bg": "#161b22", + "content-hover-fg": "#e5eaf0" } }, } diff --git a/web/extensions/core/groupNode.js b/web/extensions/core/groupNode.js index 0b0763d1d..9a2238908 100644 --- a/web/extensions/core/groupNode.js +++ b/web/extensions/core/groupNode.js @@ -1278,4 +1278,4 @@ const ext = { } }; -app.registerExtension(ext); +app.registerExtension(ext); \ No newline at end of file diff --git a/web/extensions/core/undoRedo.js b/web/extensions/core/undoRedo.js deleted file mode 100644 index 900eed2a7..000000000 --- a/web/extensions/core/undoRedo.js +++ /dev/null @@ -1,177 +0,0 @@ -import { app } from "../../scripts/app.js"; -import { api } from "../../scripts/api.js" - -const MAX_HISTORY = 50; - -let undo = []; -let redo = []; -let activeState = null; -let isOurLoad = false; -function checkState() { - const currentState = app.graph.serialize(); - if (!graphEqual(activeState, currentState)) { - undo.push(activeState); - if (undo.length > MAX_HISTORY) { - undo.shift(); - } - activeState = clone(currentState); - redo.length = 0; - api.dispatchEvent(new CustomEvent("graphChanged", { detail: activeState })); - } -} - -const loadGraphData = app.loadGraphData; -app.loadGraphData = async function () { - const v = await loadGraphData.apply(this, arguments); - if (isOurLoad) { - isOurLoad = false; - } else { - checkState(); - } - return v; -}; - -function clone(obj) { - try { - if (typeof structuredClone !== "undefined") { - return structuredClone(obj); - } - } catch (error) { - // structuredClone is stricter than using JSON.parse/stringify so fallback to that - } - - return JSON.parse(JSON.stringify(obj)); -} - -function graphEqual(a, b, root = true) { - if (a === b) return true; - - if (typeof a == "object" && a && typeof b == "object" && b) { - const keys = Object.getOwnPropertyNames(a); - - if (keys.length != Object.getOwnPropertyNames(b).length) { - return false; - } - - for (const key of keys) { - let av = a[key]; - let bv = b[key]; - if (root && key === "nodes") { - // Nodes need to be sorted as the order changes when selecting nodes - av = [...av].sort((a, b) => a.id - b.id); - bv = [...bv].sort((a, b) => a.id - b.id); - } - if (!graphEqual(av, bv, false)) { - return false; - } - } - - return true; - } - - return false; -} - -const undoRedo = async (e) => { - const updateState = async (source, target) => { - const prevState = source.pop(); - if (prevState) { - target.push(activeState); - isOurLoad = true; - await app.loadGraphData(prevState, false); - activeState = prevState; - } - } - if (e.ctrlKey || e.metaKey) { - if (e.key === "y") { - updateState(redo, undo); - return true; - } else if (e.key === "z") { - updateState(undo, redo); - return true; - } - } -}; - -const bindInput = (activeEl) => { - if (activeEl && activeEl.tagName !== "CANVAS" && activeEl.tagName !== "BODY") { - for (const evt of ["change", "input", "blur"]) { - if (`on${evt}` in activeEl) { - const listener = () => { - checkState(); - activeEl.removeEventListener(evt, listener); - }; - activeEl.addEventListener(evt, listener); - return true; - } - } - } -}; - -let keyIgnored = false; -window.addEventListener( - "keydown", - (e) => { - requestAnimationFrame(async () => { - let activeEl; - // If we are auto queue in change mode then we do want to trigger on inputs - if (!app.ui.autoQueueEnabled || app.ui.autoQueueMode === "instant") { - activeEl = document.activeElement; - if (activeEl?.tagName === "INPUT" || activeEl?.type === "textarea") { - // Ignore events on inputs, they have their native history - return; - } - } - - keyIgnored = e.key === "Control" || e.key === "Shift" || e.key === "Alt" || e.key === "Meta"; - if (keyIgnored) return; - - // Check if this is a ctrl+z ctrl+y - if (await undoRedo(e)) return; - - // If our active element is some type of input then handle changes after they're done - if (bindInput(activeEl)) return; - checkState(); - }); - }, - true -); - -window.addEventListener("keyup", (e) => { - if (keyIgnored) { - keyIgnored = false; - checkState(); - } -}); - -// Handle clicking DOM elements (e.g. widgets) -window.addEventListener("mouseup", () => { - checkState(); -}); - -// Handle prompt queue event for dynamic widget changes -api.addEventListener("promptQueued", () => { - checkState(); -}); - -// Handle litegraph clicks -const processMouseUp = LGraphCanvas.prototype.processMouseUp; -LGraphCanvas.prototype.processMouseUp = function (e) { - const v = processMouseUp.apply(this, 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::before{content:"\F02E5"}.mdi-pot-mix::before{content:"\F065B"}.mdi-pot-mix-outline::before{content:"\F0677"}.mdi-pot-outline::before{content:"\F02FF"}.mdi-pot-steam::before{content:"\F065A"}.mdi-pot-steam-outline::before{content:"\F0326"}.mdi-pound::before{content:"\F0423"}.mdi-pound-box::before{content:"\F0424"}.mdi-pound-box-outline::before{content:"\F117F"}.mdi-power::before{content:"\F0425"}.mdi-power-cycle::before{content:"\F0901"}.mdi-power-off::before{content:"\F0902"}.mdi-power-on::before{content:"\F0903"}.mdi-power-plug::before{content:"\F06A5"}.mdi-power-plug-battery::before{content:"\F1C3B"}.mdi-power-plug-battery-outline::before{content:"\F1C3C"}.mdi-power-plug-off::before{content:"\F06A6"}.mdi-power-plug-off-outline::before{content:"\F1424"}.mdi-power-plug-outline::before{content:"\F1425"}.mdi-power-settings::before{content:"\F0426"}.mdi-power-sleep::before{content:"\F0904"}.mdi-power-socket::before{content:"\F0427"}.mdi-power-socket-au::before{content:"\F0905"}.mdi-power-socket-ch::before{content:"\F0FB3"}.mdi-power-socket-de::before{content:"\F1107"}.mdi-power-socket-eu::before{content:"\F07E7"}.mdi-power-socket-fr::before{content:"\F1108"}.mdi-power-socket-it::before{content:"\F14FF"}.mdi-power-socket-jp::before{content:"\F1109"}.mdi-power-socket-uk::before{content:"\F07E8"}.mdi-power-socket-us::before{content:"\F07E9"}.mdi-power-standby::before{content:"\F0906"}.mdi-powershell::before{content:"\F0A0A"}.mdi-prescription::before{content:"\F0706"}.mdi-presentation::before{content:"\F0428"}.mdi-presentation-play::before{content:"\F0429"}.mdi-pretzel::before{content:"\F1562"}.mdi-printer::before{content:"\F042A"}.mdi-printer-3d::before{content:"\F042B"}.mdi-printer-3d-nozzle::before{content:"\F0E5B"}.mdi-printer-3d-nozzle-alert::before{content:"\F11C0"}.mdi-printer-3d-nozzle-alert-outline::before{content:"\F11C1"}.mdi-printer-3d-nozzle-heat::before{content:"\F18B8"}.mdi-printer-3d-nozzle-heat-outline::before{content:"\F18B9"}.mdi-printer-3d-nozzle-off::before{content:"\F1B19"}.mdi-printer-3d-nozzle-off-outline::before{content:"\F1B1A"}.mdi-printer-3d-nozzle-outline::before{content:"\F0E5C"}.mdi-printer-3d-off::before{content:"\F1B0E"}.mdi-printer-alert::before{content:"\F042C"}.mdi-printer-check::before{content:"\F1146"}.mdi-printer-eye::before{content:"\F1458"}.mdi-printer-off::before{content:"\F0E5D"}.mdi-printer-off-outline::before{content:"\F1785"}.mdi-printer-outline::before{content:"\F1786"}.mdi-printer-pos::before{content:"\F1057"}.mdi-printer-pos-alert::before{content:"\F1BBC"}.mdi-printer-pos-alert-outline::before{content:"\F1BBD"}.mdi-printer-pos-cancel::before{content:"\F1BBE"}.mdi-printer-pos-cancel-outline::before{content:"\F1BBF"}.mdi-printer-pos-check::before{content:"\F1BC0"}.mdi-printer-pos-check-outline::before{content:"\F1BC1"}.mdi-printer-pos-cog::before{content:"\F1BC2"}.mdi-printer-pos-cog-outline::before{content:"\F1BC3"}.mdi-printer-pos-edit::before{content:"\F1BC4"}.mdi-printer-pos-edit-outline::before{content:"\F1BC5"}.mdi-printer-pos-minus::before{content:"\F1BC6"}.mdi-printer-pos-minus-outline::before{content:"\F1BC7"}.mdi-printer-pos-network::before{content:"\F1BC8"}.mdi-printer-pos-network-outline::before{content:"\F1BC9"}.mdi-printer-pos-off::before{content:"\F1BCA"}.mdi-printer-pos-off-outline::before{content:"\F1BCB"}.mdi-printer-pos-outline::before{content:"\F1BCC"}.mdi-printer-pos-pause::before{content:"\F1BCD"}.mdi-printer-pos-pause-outline::before{content:"\F1BCE"}.mdi-printer-pos-play::before{content:"\F1BCF"}.mdi-printer-pos-play-outline::before{content:"\F1BD0"}.mdi-printer-pos-plus::before{content:"\F1BD1"}.mdi-printer-pos-plus-outline::before{content:"\F1BD2"}.mdi-printer-pos-refresh::before{content:"\F1BD3"}.mdi-printer-pos-refresh-outline::before{content:"\F1BD4"}.mdi-printer-pos-remove::before{content:"\F1BD5"}.mdi-printer-pos-remove-outline::before{content:"\F1BD6"}.mdi-printer-pos-star::before{content:"\F1BD7"}.mdi-printer-pos-star-outline::before{content:"\F1BD8"}.mdi-printer-pos-stop::before{content:"\F1BD9"}.mdi-printer-pos-stop-outline::before{content:"\F1BDA"}.mdi-printer-pos-sync::before{content:"\F1BDB"}.mdi-printer-pos-sync-outline::before{content:"\F1BDC"}.mdi-printer-pos-wrench::before{content:"\F1BDD"}.mdi-printer-pos-wrench-outline::before{content:"\F1BDE"}.mdi-printer-search::before{content:"\F1457"}.mdi-printer-settings::before{content:"\F0707"}.mdi-printer-wireless::before{content:"\F0A0B"}.mdi-priority-high::before{content:"\F0603"}.mdi-priority-low::before{content:"\F0604"}.mdi-professional-hexagon::before{content:"\F042D"}.mdi-progress-alert::before{content:"\F0CBC"}.mdi-progress-check::before{content:"\F0995"}.mdi-progress-clock::before{content:"\F0996"}.mdi-progress-close::before{content:"\F110A"}.mdi-progress-download::before{content:"\F0997"}.mdi-progress-helper::before{content:"\F1BA2"}.mdi-progress-pencil::before{content:"\F1787"}.mdi-progress-question::before{content:"\F1522"}.mdi-progress-star::before{content:"\F1788"}.md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2s infinite linear;animation:mdi-spin 2s infinite linear}@-webkit-keyframes mdi-spin{0%{-webkit-transform:rotate(0deg);transform:rotate(0deg)}100%{-webkit-transform:rotate(359deg);transform:rotate(359deg)}}@keyframes mdi-spin{0%{-webkit-transform:rotate(0deg);transform:rotate(0deg)}100%{-webkit-transform:rotate(359deg);transform:rotate(359deg)}} + +/*# sourceMappingURL=materialdesignicons.css.map */ \ No newline at end of file diff --git a/web/scripts/api.js b/web/scripts/api.js index 8c8155be6..39f0a9bb2 100644 --- a/web/scripts/api.js +++ b/web/scripts/api.js @@ -327,7 +327,7 @@ class ComfyApi extends EventTarget { /** * Gets user configuration data and where data should be stored - * @returns { Promise<{ storage: "server" | "browser", users?: Promise, migrated?: boolean }> } + * @returns { Promise<{ storage: "server" | "browser", users?: Promise, migrated?: boolean }> } */ async getUserConfig() { return (await this.fetchApi("/users")).json(); @@ -335,7 +335,7 @@ class ComfyApi extends EventTarget { /** * Creates a new user - * @param { string } username + * @param { string } username * @returns The fetch response */ createUser(username) { @@ -394,7 +394,7 @@ class ComfyApi extends EventTarget { * Gets a user data file for the current user * @param { string } file The name of the userdata file to load * @param { RequestInit } [options] - * @returns { Promise } The fetch response object + * @returns { Promise } The fetch response object */ async getUserData(file, options) { return this.fetchApi(`/userdata/${encodeURIComponent(file)}`, options); @@ -404,18 +404,75 @@ class ComfyApi extends EventTarget { * Stores a user data file for the current user * @param { string } file The name of the userdata file to save * @param { unknown } data The data to save to the file - * @param { RequestInit & { stringify?: boolean, throwOnError?: boolean } } [options] - * @returns { Promise } + * @param { RequestInit & { overwrite?: boolean, stringify?: boolean, throwOnError?: boolean } } [options] + * @returns { Promise } */ - async storeUserData(file, data, options = { stringify: true, throwOnError: true }) { - const resp = await this.fetchApi(`/userdata/${encodeURIComponent(file)}`, { + async storeUserData(file, data, options = { overwrite: true, stringify: true, throwOnError: true }) { + const resp = await this.fetchApi(`/userdata/${encodeURIComponent(file)}?overwrite=${options?.overwrite}`, { method: "POST", body: options?.stringify ? JSON.stringify(data) : data, ...options, - }); - if (resp.status !== 200) { + }); + if (resp.status !== 200 && options?.throwOnError !== false) { throw new Error(`Error storing user data file '${file}': ${resp.status} ${(await resp).statusText}`); } + return resp; + } + + /** + * Deletes a user data file for the current user + * @param { string } file The name of the userdata file to delete + */ + async deleteUserData(file) { + const resp = await this.fetchApi(`/userdata/${encodeURIComponent(file)}`, { + method: "DELETE", + }); + if (resp.status !== 204) { + throw new Error(`Error removing user data file '${file}': ${resp.status} ${(resp).statusText}`); + } + } + + /** + * Move a user data file for the current user + * @param { string } source The userdata file to move + * @param { string } dest The destination for the file + */ + async moveUserData(source, dest, options = { overwrite: false }) { + const resp = await this.fetchApi(`/userdata/${encodeURIComponent(source)}/move/${encodeURIComponent(dest)}?overwrite=${options?.overwrite}`, { + method: "POST", + }); + return resp; + } + + /** + * @overload + * Lists user data files for the current user + * @param { string } dir The directory in which to list files + * @param { boolean } [recurse] If the listing should be recursive + * @param { true } [split] If the paths should be split based on the os path separator + * @returns { Promise> } The list of split file paths in the format [fullPath, ...splitPath] + */ + /** + * @overload + * Lists user data files for the current user + * @param { string } dir The directory in which to list files + * @param { boolean } [recurse] If the listing should be recursive + * @param { false | undefined } [split] If the paths should be split based on the os path separator + * @returns { Promise> } The list of files + */ + async listUserData(dir, recurse, split) { + const resp = await this.fetchApi( + `/userdata?${new URLSearchParams({ + recurse, + dir, + split, + })}` + ); + if (resp.status === 404) return []; + if (resp.status !== 200) { + throw new Error(`Error getting user data list '${dir}': ${resp.status} ${resp.statusText}`); + } + return resp.json(); } } diff --git a/web/scripts/app.js b/web/scripts/app.js index 58fb765c4..725538563 100644 --- a/web/scripts/app.js +++ b/web/scripts/app.js @@ -5,9 +5,11 @@ import { api } from "./api.js"; import { defaultGraph } from "./defaultGraph.js"; import { getPngMetadata, getWebpMetadata, importA1111, getLatentMetadata } from "./pnginfo.js"; import { addDomClippingSetting } from "./domWidget.js"; -import { createImageHost, calculateImageGrid } from "./ui/imagePreview.js" - -export const ANIM_PREVIEW_WIDGET = "$$comfy_animation_preview" +import { createImageHost, calculateImageGrid } from "./ui/imagePreview.js"; +import { ComfyAppMenu } from "./ui/menu/index.js"; +import { getStorageValue, setStorageValue } from "./utils.js"; +import { ComfyWorkflowManager } from "./workflows.js"; +export const ANIM_PREVIEW_WIDGET = "$$comfy_animation_preview"; function sanitizeNodeName(string) { let entityMap = { @@ -52,6 +54,12 @@ export class ComfyApp { constructor() { this.ui = new ComfyUI(this); this.logging = new ComfyLogging(this); + this.workflowManager = new ComfyWorkflowManager(this); + this.bodyTop = $el("div.comfyui-body-top", { parent: document.body }); + this.bodyLeft = $el("div.comfyui-body-left", { parent: document.body }); + this.bodyRight = $el("div.comfyui-body-right", { parent: document.body }); + this.bodyBottom = $el("div.comfyui-body-bottom", { parent: document.body }); + this.menu = new ComfyAppMenu(this); /** * List of extensions that are registered with the app @@ -1313,11 +1321,15 @@ export class ComfyApp { }); api.addEventListener("progress", ({ detail }) => { + if (this.workflowManager.activePrompt?.workflow + && this.workflowManager.activePrompt.workflow !== this.workflowManager.activeWorkflow) return; this.progress = detail; this.graph.setDirtyCanvas(true, false); }); api.addEventListener("executing", ({ detail }) => { + if (this.workflowManager.activePrompt ?.workflow + && this.workflowManager.activePrompt.workflow !== this.workflowManager.activeWorkflow) return; this.progress = null; this.runningNodeId = detail; this.graph.setDirtyCanvas(true, false); @@ -1325,6 +1337,8 @@ export class ComfyApp { }); api.addEventListener("executed", ({ detail }) => { + if (this.workflowManager.activePrompt ?.workflow + && this.workflowManager.activePrompt.workflow !== this.workflowManager.activeWorkflow) return; const output = this.nodeOutputs[detail.node]; if (detail.merge && output) { for (const k in detail.output ?? {}) { @@ -1433,6 +1447,11 @@ export class ComfyApp { }); await Promise.all(extensionPromises); + try { + this.menu.workflows.registerExtension(this); + } catch (error) { + console.error(error); + } } async #migrateSettings() { @@ -1520,15 +1539,17 @@ export class ComfyApp { */ async setup() { await this.#setUser(); - await this.ui.settings.load(); - await this.#loadExtensions(); // Create and mount the LiteGraph in the DOM const mainCanvas = document.createElement("canvas") mainCanvas.style.touchAction = "none" const canvasEl = (this.canvasEl = Object.assign(mainCanvas, { id: "graph-canvas" })); canvasEl.tabIndex = "1"; - document.body.prepend(canvasEl); + document.body.append(canvasEl); + this.resizeCanvas(); + + await Promise.all([this.workflowManager.loadWorkflows(), this.ui.settings.load()]); + await this.#loadExtensions(); addDomClippingSetting(); this.#addProcessMouseHandler(); @@ -1541,7 +1562,7 @@ export class ComfyApp { this.#addAfterConfigureHandler(); - const canvas = (this.canvas = new LGraphCanvas(canvasEl, this.graph)); + this.canvas = new LGraphCanvas(canvasEl, this.graph); this.ctx = canvasEl.getContext("2d"); LiteGraph.release_link_on_empty_shows_menu = true; @@ -1549,19 +1570,14 @@ export class ComfyApp { this.graph.start(); - function resizeCanvas() { - // Limit minimal scale to 1, see https://github.com/comfyanonymous/ComfyUI/pull/845 - const scale = Math.max(window.devicePixelRatio, 1); - const { width, height } = canvasEl.getBoundingClientRect(); - canvasEl.width = Math.round(width * scale); - canvasEl.height = Math.round(height * scale); - canvasEl.getContext("2d").scale(scale, scale); - canvas.draw(true, true); - } - // Ensure the canvas fills the window - resizeCanvas(); - window.addEventListener("resize", resizeCanvas); + this.resizeCanvas(); + window.addEventListener("resize", () => this.resizeCanvas()); + const ro = new ResizeObserver(() => this.resizeCanvas()); + ro.observe(this.bodyTop); + ro.observe(this.bodyLeft); + ro.observe(this.bodyRight); + ro.observe(this.bodyBottom); await this.#invokeExtensionsAsync("init"); await this.registerNodes(); @@ -1573,7 +1589,8 @@ export class ComfyApp { const loadWorkflow = async (json) => { if (json) { const workflow = JSON.parse(json); - await this.loadGraphData(workflow); + const workflowName = getStorageValue("Comfy.PreviousWorkflow"); + await this.loadGraphData(workflow, true, workflowName); return true; } }; @@ -1609,6 +1626,19 @@ export class ComfyApp { await this.#invokeExtensionsAsync("setup"); } + resizeCanvas() { + // Limit minimal scale to 1, see https://github.com/comfyanonymous/ComfyUI/pull/845 + const scale = Math.max(window.devicePixelRatio, 1); + + // Clear fixed width and height while calculating rect so it uses 100% instead + this.canvasEl.height = this.canvasEl.width = ""; + const { width, height } = this.canvasEl.getBoundingClientRect(); + this.canvasEl.width = Math.round(width * scale); + this.canvasEl.height = Math.round(height * scale); + this.canvasEl.getContext("2d").scale(scale, scale); + this.canvas?.draw(true, true); + } + /** * Registers nodes with the graph */ @@ -1795,12 +1825,29 @@ export class ComfyApp { }); } + async changeWorkflow(callback, workflow = null) { + try { + this.workflowManager.activeWorkflow?.changeTracker?.store() + } catch (error) { + console.error(error); + } + await callback(); + try { + this.workflowManager.setWorkflow(workflow); + this.workflowManager.activeWorkflow?.track() + } catch (error) { + console.error(error); + } + } + /** * Populates the graph with the specified workflow data * @param {*} graphData A serialized graph object * @param { boolean } clean If the graph state, e.g. images, should be cleared + * @param { boolean } restore_view If the graph position should be restored + * @param { import("./workflows.js").ComfyWorkflowInstance | null } workflow The workflow */ - async loadGraphData(graphData, clean = true, restore_view = true) { + async loadGraphData(graphData, clean = true, restore_view = true, workflow = null) { if (clean !== false) { this.clean(); } @@ -1818,6 +1865,12 @@ export class ComfyApp { { graphData = structuredClone(graphData); } + + try { + this.workflowManager.setWorkflow(workflow); + } catch (error) { + console.error(error); + } const missingNodeTypes = []; await this.#invokeExtensionsAsync("beforeConfigureGraph", graphData, missingNodeTypes); @@ -1840,6 +1893,11 @@ export class ComfyApp { this.canvas.ds.offset = graphData.extra.ds.offset; this.canvas.ds.scale = graphData.extra.ds.scale; } + + try { + this.workflowManager.activeWorkflow?.track() + } catch (error) { + } } catch (error) { let errorHint = []; // Try extracting filename to see if it was caused by an extension script @@ -1927,14 +1985,17 @@ export class ComfyApp { this.showMissingNodesError(missingNodeTypes); } await this.#invokeExtensionsAsync("afterConfigureGraph", missingNodeTypes); + requestAnimationFrame(() => { + this.graph.setDirtyCanvas(true, true); + }); } /** * Converts the current graph workflow for sending to the API * @returns The workflow and node links */ - async graphToPrompt() { - for (const outerNode of this.graph.computeExecutionOrder(false)) { + async graphToPrompt(graph = this.graph, clean = true) { + for (const outerNode of graph.computeExecutionOrder(false)) { if (outerNode.widgets) { for (const widget of outerNode.widgets) { // Allow widgets to run callbacks before a prompt has been queued @@ -1954,10 +2015,10 @@ export class ComfyApp { } } - const workflow = this.graph.serialize(); + const workflow = graph.serialize(); const output = {}; // Process nodes in order of execution - for (const outerNode of this.graph.computeExecutionOrder(false)) { + for (const outerNode of graph.computeExecutionOrder(false)) { const skipNode = outerNode.mode === 2 || outerNode.mode === 4; const innerNodes = (!skipNode && outerNode.getInnerNodes) ? outerNode.getInnerNodes() : [outerNode]; for (const node of innerNodes) { @@ -2049,13 +2110,14 @@ export class ComfyApp { } // Remove inputs connected to removed nodes - - for (const o in output) { - for (const i in output[o].inputs) { - if (Array.isArray(output[o].inputs[i]) - && output[o].inputs[i].length === 2 - && !output[output[o].inputs[i][0]]) { - delete output[o].inputs[i]; + if(clean) { + for (const o in output) { + for (const i in output[o].inputs) { + if (Array.isArray(output[o].inputs[i]) + && output[o].inputs[i].length === 2 + && !output[output[o].inputs[i][0]]) { + delete output[o].inputs[i]; + } } } } @@ -2123,6 +2185,14 @@ export class ComfyApp { this.lastNodeErrors = res.node_errors; if (this.lastNodeErrors.length > 0) { this.canvas.draw(true, true); + } else { + try { + this.workflowManager.storePrompt({ + id: res.prompt_id, + nodes: Object.keys(p.output) + }); + } catch (error) { + } } } catch (error) { const formattedError = this.#formatPromptError(error) @@ -2155,6 +2225,7 @@ export class ComfyApp { this.#processingQueue = false; } api.dispatchEvent(new CustomEvent("promptQueued", { detail: { number, batchCount } })); + return !this.lastNodeErrors; } showErrorOnFileLoad(file) { @@ -2170,14 +2241,24 @@ export class ComfyApp { * @param {File} file */ async handleFile(file) { + const removeExt = f => { + if(!f) return f; + const p = f.lastIndexOf("."); + if(p === -1) return f; + return f.substring(0, p); + }; + + const fileName = removeExt(file.name); if (file.type === "image/png") { const pngInfo = await getPngMetadata(file); if (pngInfo?.workflow) { - await this.loadGraphData(JSON.parse(pngInfo.workflow)); + await this.loadGraphData(JSON.parse(pngInfo.workflow), true, true, fileName); } else if (pngInfo?.prompt) { - this.loadApiJson(JSON.parse(pngInfo.prompt)); + this.loadApiJson(JSON.parse(pngInfo.prompt), fileName); } else if (pngInfo?.parameters) { - importA1111(this.graph, pngInfo.parameters); + this.changeWorkflow(() => { + importA1111(this.graph, pngInfo.parameters); + }, fileName) } else { this.showErrorOnFileLoad(file); } @@ -2188,9 +2269,9 @@ export class ComfyApp { const prompt = pngInfo?.prompt || pngInfo?.Prompt; if (workflow) { - this.loadGraphData(JSON.parse(workflow)); + this.loadGraphData(JSON.parse(workflow), true, true, fileName); } else if (prompt) { - this.loadApiJson(JSON.parse(prompt)); + this.loadApiJson(JSON.parse(prompt), fileName); } else { this.showErrorOnFileLoad(file); } @@ -2201,16 +2282,16 @@ export class ComfyApp { if (jsonContent?.templates) { this.loadTemplateData(jsonContent); } else if(this.isApiJson(jsonContent)) { - this.loadApiJson(jsonContent); + this.loadApiJson(jsonContent, fileName); } else { - await this.loadGraphData(jsonContent); + await this.loadGraphData(jsonContent, true, fileName); } }; reader.readAsText(file); } else if (file.name?.endsWith(".latent") || file.name?.endsWith(".safetensors")) { const info = await getLatentMetadata(file); if (info.workflow) { - await this.loadGraphData(JSON.parse(info.workflow)); + await this.loadGraphData(JSON.parse(info.workflow), true, fileName); } else if (info.prompt) { this.loadApiJson(JSON.parse(info.prompt)); } else { @@ -2225,7 +2306,7 @@ export class ComfyApp { return Object.values(data).every((v) => v.class_type); } - loadApiJson(apiData) { + loadApiJson(apiData, fileName) { const missingNodeTypes = Object.values(apiData).filter((n) => !LiteGraph.registered_node_types[n.class_type]); if (missingNodeTypes.length) { this.showMissingNodesError(missingNodeTypes.map(t => t.class_type), false); @@ -2240,40 +2321,42 @@ export class ComfyApp { node.id = isNaN(+id) ? id : +id; node.title = data._meta?.title ?? node.title app.graph.add(node); + graph.add(node); } - for (const id of ids) { - const data = apiData[id]; - const node = app.graph.getNodeById(id); - for (const input in data.inputs ?? {}) { - const value = data.inputs[input]; - if (value instanceof Array) { - const [fromId, fromSlot] = value; - const fromNode = app.graph.getNodeById(fromId); - let toSlot = node.inputs?.findIndex((inp) => inp.name === input); - if (toSlot == null || toSlot === -1) { - try { - // Target has no matching input, most likely a converted widget - const widget = node.widgets?.find((w) => w.name === input); - if (widget && node.convertWidgetToInput?.(widget)) { - toSlot = node.inputs?.length - 1; - } - } catch (error) {} - } - if (toSlot != null || toSlot !== -1) { - fromNode.connect(fromSlot, node, toSlot); - } - } else { - const widget = node.widgets?.find((w) => w.name === input); - if (widget) { - widget.value = value; - widget.callback?.(value); + this.changeWorkflow(() => { + for (const id of ids) { + const data = apiData[id]; + const node = app.graph.getNodeById(id); + for (const input in data.inputs ?? {}) { + const value = data.inputs[input]; + if (value instanceof Array) { + const [fromId, fromSlot] = value; + const fromNode = app.graph.getNodeById(fromId); + let toSlot = node.inputs?.findIndex((inp) => inp.name === input); + if (toSlot == null || toSlot === -1) { + try { + // Target has no matching input, most likely a converted widget + const widget = node.widgets?.find((w) => w.name === input); + if (widget && node.convertWidgetToInput?.(widget)) { + toSlot = node.inputs?.length - 1; + } + } catch (error) {} + } + if (toSlot != null || toSlot !== -1) { + fromNode.connect(fromSlot, node, toSlot); + } + } else { + const widget = node.widgets?.find((w) => w.name === input); + if (widget) { + widget.value = value; + widget.callback?.(value); + } } } } - } - - app.graph.arrange(); + app.graph.arrange(); + }, fileName); } /** diff --git a/web/scripts/changeTracker.js b/web/scripts/changeTracker.js new file mode 100644 index 000000000..59901d5fc --- /dev/null +++ b/web/scripts/changeTracker.js @@ -0,0 +1,242 @@ +// @ts-check + +import { api } from "./api.js"; +import { clone } from "./utils.js"; + + +export class ChangeTracker { + static MAX_HISTORY = 50; + #app; + undo = []; + redo = []; + activeState = null; + isOurLoad = false; + /** @type { import("./workflows").ComfyWorkflow | null } */ + workflow; + + ds; + nodeOutputs; + + get app() { + return this.#app ?? this.workflow.manager.app; + } + + constructor(workflow) { + this.workflow = workflow; + } + + #setApp(app) { + this.#app = app; + } + + store() { + this.ds = { scale: this.app.canvas.ds.scale, offset: [...this.app.canvas.ds.offset] }; + } + + restore() { + if (this.ds) { + this.app.canvas.ds.scale = this.ds.scale; + this.app.canvas.ds.offset = this.ds.offset; + } + if (this.nodeOutputs) { + this.app.nodeOutputs = this.nodeOutputs; + } + } + + checkState() { + if (!this.app.graph) return; + + const currentState = this.app.graph.serialize(); + if (!this.activeState) { + this.activeState = clone(currentState); + return; + } + if (!ChangeTracker.graphEqual(this.activeState, currentState)) { + this.undo.push(this.activeState); + if (this.undo.length > ChangeTracker.MAX_HISTORY) { + this.undo.shift(); + } + this.activeState = clone(currentState); + this.redo.length = 0; + this.workflow.unsaved = true; + api.dispatchEvent(new CustomEvent("graphChanged", { detail: this.activeState })); + } + } + + async updateState(source, target) { + const prevState = source.pop(); + if (prevState) { + target.push(this.activeState); + this.isOurLoad = true; + await this.app.loadGraphData(prevState, false, false, this.workflow); + this.activeState = prevState; + } + } + + async undoRedo(e) { + if (e.ctrlKey || e.metaKey) { + if (e.key === "y") { + this.updateState(this.redo, this.undo); + return true; + } else if (e.key === "z") { + this.updateState(this.undo, this.redo); + return true; + } + } + } + + /** @param { import("./app.js").ComfyApp } app */ + static init(app) { + const changeTracker = () => app.workflowManager.activeWorkflow?.changeTracker ?? globalTracker; + globalTracker.#setApp(app); + + const loadGraphData = app.loadGraphData; + app.loadGraphData = async function () { + const v = await loadGraphData.apply(this, arguments); + const ct = changeTracker(); + if (ct.isOurLoad) { + ct.isOurLoad = false; + } else { + ct.checkState(); + } + return v; + }; + + let keyIgnored = false; + window.addEventListener( + "keydown", + (e) => { + requestAnimationFrame(async () => { + let activeEl; + // If we are auto queue in change mode then we do want to trigger on inputs + if (!app.ui.autoQueueEnabled || app.ui.autoQueueMode === "instant") { + activeEl = document.activeElement; + if (activeEl?.tagName === "INPUT" || activeEl?.["type"] === "textarea") { + // Ignore events on inputs, they have their native history + return; + } + } + + keyIgnored = e.key === "Control" || e.key === "Shift" || e.key === "Alt" || e.key === "Meta"; + if (keyIgnored) return; + + // Check if this is a ctrl+z ctrl+y + if (await changeTracker().undoRedo(e)) return; + + // If our active element is some type of input then handle changes after they're done + if (ChangeTracker.bindInput(activeEl)) return; + changeTracker().checkState(); + }); + }, + true + ); + + window.addEventListener("keyup", (e) => { + if (keyIgnored) { + keyIgnored = false; + changeTracker().checkState(); + } + }); + + // Handle clicking DOM elements (e.g. widgets) + window.addEventListener("mouseup", () => { + changeTracker().checkState(); + }); + + // Handle prompt queue event for dynamic widget changes + api.addEventListener("promptQueued", () => { + changeTracker().checkState(); + }); + + // Handle litegraph clicks + const processMouseUp = LGraphCanvas.prototype.processMouseUp; + LGraphCanvas.prototype.processMouseUp = function (e) { + const v = processMouseUp.apply(this, arguments); + changeTracker().checkState(); + return v; + }; + const processMouseDown = LGraphCanvas.prototype.processMouseDown; + LGraphCanvas.prototype.processMouseDown = function (e) { + const v = processMouseDown.apply(this, arguments); + changeTracker().checkState(); + return v; + }; + + // Handle litegraph context menu for COMBO widgets + const close = LiteGraph.ContextMenu.prototype.close; + LiteGraph.ContextMenu.prototype.close = function (e) { + const v = close.apply(this, arguments); + changeTracker().checkState(); + return v; + }; + + // Store node outputs + api.addEventListener("executed", ({ detail }) => { + const prompt = app.workflowManager.queuedPrompts[detail.prompt_id]; + if (!prompt?.workflow) return; + const nodeOutputs = (prompt.workflow.changeTracker.nodeOutputs ??= {}); + const output = nodeOutputs[detail.node]; + if (detail.merge && output) { + for (const k in detail.output ?? {}) { + const v = output[k]; + if (v instanceof Array) { + output[k] = v.concat(detail.output[k]); + } else { + output[k] = detail.output[k]; + } + } + } else { + nodeOutputs[detail.node] = detail.output; + } + }); + } + + static bindInput(app, activeEl) { + if (activeEl && activeEl.tagName !== "CANVAS" && activeEl.tagName !== "BODY") { + for (const evt of ["change", "input", "blur"]) { + if (`on${evt}` in activeEl) { + const listener = () => { + app.workflowManager.activeWorkflow.changeTracker.checkState(); + activeEl.removeEventListener(evt, listener); + }; + activeEl.addEventListener(evt, listener); + return true; + } + } + } + } + + static graphEqual(a, b, path = "") { + if (a === b) return true; + + if (typeof a == "object" && a && typeof b == "object" && b) { + const keys = Object.getOwnPropertyNames(a); + + if (keys.length != Object.getOwnPropertyNames(b).length) { + return false; + } + + for (const key of keys) { + let av = a[key]; + let bv = b[key]; + if (!path && key === "nodes") { + // Nodes need to be sorted as the order changes when selecting nodes + av = [...av].sort((a, b) => a.id - b.id); + bv = [...bv].sort((a, b) => a.id - b.id); + } else if (path === "extra.ds") { + // Ignore view changes + continue; + } + if (!ChangeTracker.graphEqual(av, bv, path + (path ? "." : "") + key)) { + return false; + } + } + + return true; + } + + return false; + } +} + +const globalTracker = new ChangeTracker({}); \ No newline at end of file diff --git a/web/scripts/domWidget.js b/web/scripts/domWidget.js index b7f437ad2..d97122f9d 100644 --- a/web/scripts/domWidget.js +++ b/web/scripts/domWidget.js @@ -34,8 +34,8 @@ function getClipPath(node, element) { } const widgetRect = element.getBoundingClientRect(); - const clipX = intersection[0] - widgetRect.x / scale + "px"; - const clipY = intersection[1] - widgetRect.y / scale + "px"; + const clipX = elRect.left + intersection[0] - widgetRect.x / scale + "px"; + const clipY = elRect.top + intersection[1] - widgetRect.y / scale + "px"; const clipWidth = intersection[2] + "px"; const clipHeight = intersection[3] + "px"; const path = `polygon(0% 0%, 0% 100%, ${clipX} 100%, ${clipX} ${clipY}, calc(${clipX} + ${clipWidth}) ${clipY}, calc(${clipX} + ${clipWidth}) calc(${clipY} + ${clipHeight}), ${clipX} calc(${clipY} + ${clipHeight}), ${clipX} 100%, 100% 100%, 100% 0%)`; @@ -210,7 +210,9 @@ LGraphNode.prototype.addDOMWidget = function (name, type, element, options) { if (!element.parentElement) { document.body.append(element); } - + element.hidden = true; + element.style.display = "none"; + let mouseDownHandler; if (element.blur) { mouseDownHandler = (event) => { @@ -254,15 +256,15 @@ LGraphNode.prototype.addDOMWidget = function (name, type, element, options) { const transform = new DOMMatrix() .scaleSelf(elRect.width / ctx.canvas.width, elRect.height / ctx.canvas.height) .multiplySelf(ctx.getTransform()) - .translateSelf(margin, margin + y); + .translateSelf(margin, margin + y ); const scale = new DOMMatrix().scaleSelf(transform.a, transform.d); Object.assign(element.style, { transformOrigin: "0 0", transform: scale, - left: `${transform.a + transform.e}px`, - top: `${transform.d + transform.f}px`, + left: `${transform.a + transform.e + elRect.left}px`, + top: `${transform.d + transform.f + elRect.top}px`, width: `${widgetWidth - margin * 2}px`, height: `${(widget.computedHeight ?? 50) - margin * 2}px`, position: "absolute", diff --git a/web/scripts/ui.js b/web/scripts/ui.js index 72e43d357..87b4887eb 100644 --- a/web/scripts/ui.js +++ b/web/scripts/ui.js @@ -6,17 +6,22 @@ import { ComfySettingsDialog } from "./ui/settings.js"; export const ComfyDialog = _ComfyDialog; /** - * - * @param { string } tag HTML Element Tag and optional classes e.g. div.class1.class2 - * @param { string | Element | Element[] | { + * @template { string | (keyof HTMLElementTagNameMap) } K + * @typedef { K extends keyof HTMLElementTagNameMap ? HTMLElementTagNameMap[K] : HTMLElement } ElementType + */ + +/** + * @template { string | (keyof HTMLElementTagNameMap) } K + * @param { K } tag HTML Element Tag and optional classes e.g. div.class1.class2 + * @param { string | Element | Element[] | ({ * parent?: Element, - * $?: (el: Element) => void, + * $?: (el: ElementType) => void, * dataset?: DOMStringMap, - * style?: CSSStyleDeclaration, + * style?: Partial, * for?: string - * } | undefined } propsOrChildren - * @param { Element[] | undefined } [children] - * @returns + * } & Omit>, "style">) | undefined } [propsOrChildren] + * @param { string | Element | Element[] | undefined } [children] + * @returns { ElementType } */ export function $el(tag, propsOrChildren, children) { const split = tag.split("."); @@ -54,7 +59,7 @@ export function $el(tag, propsOrChildren, children) { Object.assign(element, propsOrChildren); if (children) { - element.append(...(children instanceof Array ? children : [children])); + element.append(...(children instanceof Array ? children.filter(Boolean) : [children])); } if (parent) { @@ -102,6 +107,8 @@ function dragElement(dragEl, settings) { } function positionElement() { + if(dragEl.style.display === "none") return; + const halfWidth = document.body.clientWidth / 2; const anchorRight = newPosX + dragEl.clientWidth / 2 > halfWidth; @@ -191,6 +198,8 @@ function dragElement(dragEl, settings) { document.onmouseup = null; document.onmousemove = null; } + + return restorePos; } class ComfyList { @@ -372,6 +381,8 @@ export class ComfyUI { }, }); + this.loadFile = () => fileInput.click(); + const autoQueueModeEl = toggleSwitch( "autoQueueMode", [ @@ -592,6 +603,7 @@ export class ComfyUI { onclick: () => app.refreshComboInNodes() }), $el("button", {id: "comfy-clipspace-button", textContent: "Clipspace", onclick: () => app.openClipspace()}), + $el("button", {id: "comfy-reset-view-button", textContent: "Reset View", onclick: () => app.resetView()}), $el("button", { id: "comfy-clear-button", textContent: "Clear", onclick: () => { if (!confirmClear.value || confirm("Clear workflow?")) { @@ -621,10 +633,10 @@ export class ComfyUI { name: "Enable Dev mode Options", type: "boolean", defaultValue: false, - onChange: function(value) { document.getElementById("comfy-dev-save-api-button").style.display = value ? "block" : "none"}, + onChange: function(value) { document.getElementById("comfy-dev-save-api-button").style.display = value ? "flex" : "none"}, }); - dragElement(this.menuContainer, this.settings); + this.restoreMenuPosition = dragElement(this.menuContainer, this.settings); this.setStatus({exec_info: {queue_remaining: "X"}}); } diff --git a/web/scripts/ui/components/asyncDialog.js b/web/scripts/ui/components/asyncDialog.js new file mode 100644 index 000000000..434ce4b30 --- /dev/null +++ b/web/scripts/ui/components/asyncDialog.js @@ -0,0 +1,64 @@ +import { ComfyDialog } from "../dialog.js"; +import { $el } from "../../ui.js"; + +export class ComfyAsyncDialog extends ComfyDialog { + #resolve; + + constructor(actions) { + super( + "dialog.comfy-dialog.comfyui-dialog", + actions?.map((opt) => { + if (typeof opt === "string") { + opt = { text: opt }; + } + return $el("button.comfyui-button", { + type: "button", + textContent: opt.text, + onclick: () => this.close(opt.value ?? opt.text), + }); + }) + ); + } + + show(html) { + this.element.addEventListener("close", () => { + this.close(); + }); + + super.show(html); + + return new Promise((resolve) => { + this.#resolve = resolve; + }); + } + + showModal(html) { + this.element.addEventListener("close", () => { + this.close(); + }); + + super.show(html); + this.element.showModal(); + + return new Promise((resolve) => { + this.#resolve = resolve; + }); + } + + close(result = null) { + this.#resolve(result); + this.element.close(); + super.close(); + } + + static async prompt({ title = null, message, actions }) { + const dialog = new ComfyAsyncDialog(actions); + const content = [$el("span", message)]; + if (title) { + content.unshift($el("h3", title)); + } + const res = await dialog.showModal(content); + dialog.element.remove(); + return res; + } +} diff --git a/web/scripts/ui/components/button.js b/web/scripts/ui/components/button.js new file mode 100644 index 000000000..25e5aeebd --- /dev/null +++ b/web/scripts/ui/components/button.js @@ -0,0 +1,163 @@ +// @ts-check + +import { $el } from "../../ui.js"; +import { applyClasses, toggleElement } from "../utils.js"; +import { prop } from "../../utils.js"; + +/** + * @typedef {{ + * icon?: string; + * overIcon?: string; + * iconSize?: number; + * content?: string | HTMLElement; + * tooltip?: string; + * enabled?: boolean; + * action?: (e: Event, btn: ComfyButton) => void, + * classList?: import("../utils.js").ClassList, + * visibilitySetting?: { id: string, showValue: any }, + * app?: import("../../app.js").ComfyApp + * }} ComfyButtonProps + */ +export class ComfyButton { + #over = 0; + #popupOpen = false; + isOver = false; + iconElement = $el("i.mdi"); + contentElement = $el("span"); + /** + * @type {import("./popup.js").ComfyPopup} + */ + popup; + + /** + * @param {ComfyButtonProps} opts + */ + constructor({ + icon, + overIcon, + iconSize, + content, + tooltip, + action, + classList = "comfyui-button", + visibilitySetting, + app, + enabled = true, + }) { + this.element = $el("button", { + onmouseenter: () => { + this.isOver = true; + if(this.overIcon) { + this.updateIcon(); + } + }, + onmouseleave: () => { + this.isOver = false; + if(this.overIcon) { + this.updateIcon(); + } + } + + }, [this.iconElement, this.contentElement]); + + this.icon = prop(this, "icon", icon, toggleElement(this.iconElement, { onShow: this.updateIcon })); + this.overIcon = prop(this, "overIcon", overIcon, () => { + if(this.isOver) { + this.updateIcon(); + } + }); + this.iconSize = prop(this, "iconSize", iconSize, this.updateIcon); + this.content = prop( + this, + "content", + content, + toggleElement(this.contentElement, { + onShow: (el, v) => { + if (typeof v === "string") { + el.textContent = v; + } else { + el.replaceChildren(v); + } + }, + }) + ); + + this.tooltip = prop(this, "tooltip", tooltip, (v) => { + if (v) { + this.element.title = v; + } else { + this.element.removeAttribute("title"); + } + }); + this.classList = prop(this, "classList", classList, this.updateClasses); + this.hidden = prop(this, "hidden", false, this.updateClasses); + this.enabled = prop(this, "enabled", enabled, () => { + this.updateClasses(); + this.element.disabled = !this.enabled; + }); + this.action = prop(this, "action", action); + this.element.addEventListener("click", (e) => { + if (this.popup) { + // we are either a touch device or triggered by click not hover + if (!this.#over) { + this.popup.toggle(); + } + } + this.action?.(e, this); + }); + + if (visibilitySetting?.id) { + const settingUpdated = () => { + this.hidden = app.ui.settings.getSettingValue(visibilitySetting.id) !== visibilitySetting.showValue; + }; + app.ui.settings.addEventListener(visibilitySetting.id + ".change", settingUpdated); + settingUpdated(); + } + } + + updateIcon = () => (this.iconElement.className = `mdi mdi-${(this.isOver && this.overIcon) || this.icon}${this.iconSize ? " mdi-" + this.iconSize + "px" : ""}`); + updateClasses = () => { + const internalClasses = []; + if (this.hidden) { + internalClasses.push("hidden"); + } + if (!this.enabled) { + internalClasses.push("disabled"); + } + if (this.popup) { + if (this.#popupOpen) { + internalClasses.push("popup-open"); + } else { + internalClasses.push("popup-closed"); + } + } + applyClasses(this.element, this.classList, ...internalClasses); + }; + + /** + * + * @param { import("./popup.js").ComfyPopup } popup + * @param { "click" | "hover" } mode + */ + withPopup(popup, mode = "click") { + this.popup = popup; + + if (mode === "hover") { + for (const el of [this.element, this.popup.element]) { + el.addEventListener("mouseenter", () => { + this.popup.open = !!++this.#over; + }); + el.addEventListener("mouseleave", () => { + this.popup.open = !!--this.#over; + }); + } + } + + popup.addEventListener("change", () => { + this.#popupOpen = popup.open; + this.updateClasses(); + }); + + return this; + } +} diff --git a/web/scripts/ui/components/buttonGroup.js b/web/scripts/ui/components/buttonGroup.js new file mode 100644 index 000000000..573572fd0 --- /dev/null +++ b/web/scripts/ui/components/buttonGroup.js @@ -0,0 +1,45 @@ +// @ts-check + +import { $el } from "../../ui.js"; +import { ComfyButton } from "./button.js"; +import { prop } from "../../utils.js"; + +export class ComfyButtonGroup { + element = $el("div.comfyui-button-group"); + + /** @param {Array} buttons */ + constructor(...buttons) { + this.buttons = prop(this, "buttons", buttons, () => this.update()); + } + + /** + * @param {ComfyButton} button + * @param {number} index + */ + insert(button, index) { + this.buttons.splice(index, 0, button); + this.update(); + } + + /** @param {ComfyButton} button */ + append(button) { + this.buttons.push(button); + this.update(); + } + + /** @param {ComfyButton|number} indexOrButton */ + remove(indexOrButton) { + if (typeof indexOrButton !== "number") { + indexOrButton = this.buttons.indexOf(indexOrButton); + } + if (indexOrButton > -1) { + const r = this.buttons.splice(indexOrButton, 1); + this.update(); + return r; + } + } + + update() { + this.element.replaceChildren(...this.buttons.map((b) => b["element"] ?? b)); + } +} diff --git a/web/scripts/ui/components/popup.js b/web/scripts/ui/components/popup.js new file mode 100644 index 000000000..ee59b35d9 --- /dev/null +++ b/web/scripts/ui/components/popup.js @@ -0,0 +1,128 @@ +// @ts-check + +import { prop } from "../../utils.js"; +import { $el } from "../../ui.js"; +import { applyClasses } from "../utils.js"; + +export class ComfyPopup extends EventTarget { + element = $el("div.comfyui-popup"); + + /** + * @param {{ + * target: HTMLElement, + * container?: HTMLElement, + * classList?: import("../utils.js").ClassList, + * ignoreTarget?: boolean, + * closeOnEscape?: boolean, + * position?: "absolute" | "relative", + * horizontal?: "left" | "right" + * }} param0 + * @param {...HTMLElement} children + */ + constructor( + { + target, + container = document.body, + classList = "", + ignoreTarget = true, + closeOnEscape = true, + position = "absolute", + horizontal = "left", + }, + ...children + ) { + super(); + this.target = target; + this.ignoreTarget = ignoreTarget; + this.container = container; + this.position = position; + this.closeOnEscape = closeOnEscape; + this.horizontal = horizontal; + + container.append(this.element); + + this.children = prop(this, "children", children, () => { + this.element.replaceChildren(...this.children); + this.update(); + }); + this.classList = prop(this, "classList", classList, () => applyClasses(this.element, this.classList, "comfyui-popup", horizontal)); + this.open = prop(this, "open", false, (v, o) => { + if (v === o) return; + if (v) { + this.#show(); + } else { + this.#hide(); + } + }); + } + + toggle() { + this.open = !this.open; + } + + #hide() { + this.element.classList.remove("open"); + window.removeEventListener("resize", this.update); + window.removeEventListener("click", this.#clickHandler, { capture: true }); + window.removeEventListener("keydown", this.#escHandler, { capture: true }); + + this.dispatchEvent(new CustomEvent("close")); + this.dispatchEvent(new CustomEvent("change")); + } + + #show() { + this.element.classList.add("open"); + this.update(); + + window.addEventListener("resize", this.update); + window.addEventListener("click", this.#clickHandler, { capture: true }); + if (this.closeOnEscape) { + window.addEventListener("keydown", this.#escHandler, { capture: true }); + } + + this.dispatchEvent(new CustomEvent("open")); + this.dispatchEvent(new CustomEvent("change")); + } + + #escHandler = (e) => { + if (e.key === "Escape") { + this.open = false; + e.preventDefault(); + e.stopImmediatePropagation(); + } + }; + + #clickHandler = (e) => { + /** @type {any} */ + const target = e.target; + if (!this.element.contains(target) && this.ignoreTarget && !this.target.contains(target)) { + this.open = false; + } + }; + + update = () => { + const rect = this.target.getBoundingClientRect(); + this.element.style.setProperty("--bottom", "unset"); + if (this.position === "absolute") { + if (this.horizontal === "left") { + this.element.style.setProperty("--left", rect.left + "px"); + } else { + this.element.style.setProperty("--left", rect.right - this.element.clientWidth + "px"); + } + this.element.style.setProperty("--top", rect.bottom + "px"); + this.element.style.setProperty("--limit", rect.bottom + "px"); + } else { + this.element.style.setProperty("--left", 0 + "px"); + this.element.style.setProperty("--top", rect.height + "px"); + this.element.style.setProperty("--limit", rect.height + "px"); + } + + const thisRect = this.element.getBoundingClientRect(); + if (thisRect.height < 30) { + // Move up instead + this.element.style.setProperty("--top", "unset"); + this.element.style.setProperty("--bottom", rect.height + 5 + "px"); + this.element.style.setProperty("--limit", rect.height + 5 + "px"); + } + }; +} diff --git a/web/scripts/ui/components/splitButton.js b/web/scripts/ui/components/splitButton.js new file mode 100644 index 000000000..2b4e6d9f8 --- /dev/null +++ b/web/scripts/ui/components/splitButton.js @@ -0,0 +1,43 @@ +// @ts-check + +import { $el } from "../../ui.js"; +import { ComfyButton } from "./button.js"; +import { prop } from "../../utils.js"; +import { ComfyPopup } from "./popup.js"; + +export class ComfySplitButton { + /** + * @param {{ + * primary: ComfyButton, + * mode?: "hover" | "click", + * horizontal?: "left" | "right", + * position?: "relative" | "absolute" + * }} param0 + * @param {Array | Array} items + */ + constructor({ primary, mode, horizontal = "left", position = "relative" }, ...items) { + this.arrow = new ComfyButton({ + icon: "chevron-down", + }); + this.element = $el("div.comfyui-split-button" + (mode === "hover" ? ".hover" : ""), [ + $el("div.comfyui-split-primary", primary.element), + $el("div.comfyui-split-arrow", this.arrow.element), + ]); + this.popup = new ComfyPopup({ + target: this.element, + container: position === "relative" ? this.element : document.body, + classList: "comfyui-split-button-popup" + (mode === "hover" ? " hover" : ""), + closeOnEscape: mode === "click", + position, + horizontal, + }); + + this.arrow.withPopup(this.popup, mode); + + this.items = prop(this, "items", items, () => this.update()); + } + + update() { + this.popup.element.replaceChildren(...this.items.map((b) => b.element ?? b)); + } +} diff --git a/web/scripts/ui/dialog.js b/web/scripts/ui/dialog.js index aee93b3c8..803a97a2b 100644 --- a/web/scripts/ui/dialog.js +++ b/web/scripts/ui/dialog.js @@ -1,20 +1,26 @@ import { $el } from "../ui.js"; -export class ComfyDialog { - constructor() { - this.element = $el("div.comfy-modal", { parent: document.body }, [ +export class ComfyDialog extends EventTarget { + #buttons; + + constructor(type = "div", buttons = null) { + super(); + this.#buttons = buttons; + this.element = $el(type + ".comfy-modal", { parent: document.body }, [ $el("div.comfy-modal-content", [$el("p", { $: (p) => (this.textElement = p) }), ...this.createButtons()]), ]); } createButtons() { - return [ - $el("button", { - type: "button", - textContent: "Close", - onclick: () => this.close(), - }), - ]; + return ( + this.#buttons ?? [ + $el("button", { + type: "button", + textContent: "Close", + onclick: () => this.close(), + }), + ] + ); } close() { @@ -25,7 +31,7 @@ export class ComfyDialog { if (typeof html === "string") { this.textElement.innerHTML = html; } else { - this.textElement.replaceChildren(html); + this.textElement.replaceChildren(...(html instanceof Array ? html : [html])); } this.element.style.display = "flex"; } diff --git a/web/scripts/ui/menu/index.js b/web/scripts/ui/menu/index.js new file mode 100644 index 000000000..1e00b3d22 --- /dev/null +++ b/web/scripts/ui/menu/index.js @@ -0,0 +1,302 @@ +// @ts-check + +import { $el } from "../../ui.js"; +import { downloadBlob } from "../../utils.js"; +import { ComfyButton } from "../components/button.js"; +import { ComfyButtonGroup } from "../components/buttonGroup.js"; +import { ComfySplitButton } from "../components/splitButton.js"; +import { ComfyViewHistoryButton } from "./viewHistory.js"; +import { ComfyQueueButton } from "./queueButton.js"; +import { ComfyWorkflowsMenu } from "./workflows.js"; +import { ComfyViewQueueButton } from "./viewQueue.js"; +import { getInteruptButton } from "./interruptButton.js"; + +const collapseOnMobile = (t) => { + (t.element ?? t).classList.add("comfyui-menu-mobile-collapse"); + return t; +}; +const showOnMobile = (t) => { + (t.element ?? t).classList.add("lt-lg-show"); + return t; +}; + +export class ComfyAppMenu { + #sizeBreak = "lg"; + #lastSizeBreaks = { + lg: null, + md: null, + sm: null, + xs: null, + }; + #sizeBreaks = Object.keys(this.#lastSizeBreaks); + #cachedInnerSize = null; + #cacheTimeout = null; + + /** + * @param { import("../../app.js").ComfyApp } app + */ + constructor(app) { + this.app = app; + + this.workflows = new ComfyWorkflowsMenu(app); + const getSaveButton = (t) => + new ComfyButton({ + icon: "content-save", + tooltip: "Save the current workflow", + action: () => app.workflowManager.activeWorkflow.save(), + content: t, + }); + + this.logo = $el("h1.comfyui-logo.nlg-hide", { title: "ComfyUI" }, "ComfyUI"); + this.saveButton = new ComfySplitButton( + { + primary: getSaveButton(), + mode: "hover", + position: "absolute", + }, + getSaveButton("Save"), + new ComfyButton({ + icon: "content-save-edit", + content: "Save As", + tooltip: "Save the current graph as a new workflow", + action: () => app.workflowManager.activeWorkflow.save(true), + }), + new ComfyButton({ + icon: "download", + content: "Export", + tooltip: "Export the current workflow as JSON", + action: () => this.exportWorkflow("workflow", "workflow"), + }), + new ComfyButton({ + icon: "api", + content: "Export (API Format)", + tooltip: "Export the current workflow as JSON for use with the ComfyUI API", + action: () => this.exportWorkflow("workflow_api", "output"), + visibilitySetting: { id: "Comfy.DevMode", showValue: true }, + app, + }) + ); + this.actionsGroup = new ComfyButtonGroup( + new ComfyButton({ + icon: "refresh", + content: "Refresh", + tooltip: "Refresh widgets in nodes to find new models or files", + action: () => app.refreshComboInNodes(), + }), + new ComfyButton({ + icon: "clipboard-edit-outline", + content: "Clipspace", + tooltip: "Open Clipspace window", + action: () => app["openClipspace"](), + }), + new ComfyButton({ + icon: "fit-to-page-outline", + content: "Reset View", + tooltip: "Reset the canvas view", + action: () => app.resetView(), + }), + new ComfyButton({ + icon: "cancel", + content: "Clear", + tooltip: "Clears current workflow", + action: () => { + if (!app.ui.settings.getSettingValue("Comfy.ConfirmClear", true) || confirm("Clear workflow?")) { + app.clean(); + app.graph.clear(); + } + }, + }) + ); + this.settingsGroup = new ComfyButtonGroup( + new ComfyButton({ + icon: "cog", + content: "Settings", + tooltip: "Open settings", + action: () => { + app.ui.settings.show(); + }, + }) + ); + this.viewGroup = new ComfyButtonGroup( + new ComfyViewHistoryButton(app).element, + new ComfyViewQueueButton(app).element, + getInteruptButton("nlg-hide").element + ); + this.mobileMenuButton = new ComfyButton({ + icon: "menu", + action: (_, btn) => { + btn.icon = this.element.classList.toggle("expanded") ? "menu-open" : "menu"; + window.dispatchEvent(new Event("resize")); + }, + classList: "comfyui-button comfyui-menu-button", + }); + + this.element = $el("nav.comfyui-menu.lg", { style: { display: "none" } }, [ + this.logo, + this.workflows.element, + this.saveButton.element, + collapseOnMobile(this.actionsGroup).element, + $el("section.comfyui-menu-push"), + collapseOnMobile(this.settingsGroup).element, + collapseOnMobile(this.viewGroup).element, + + getInteruptButton("lt-lg-show").element, + new ComfyQueueButton(app).element, + showOnMobile(this.mobileMenuButton).element, + ]); + + let resizeHandler; + this.menuPositionSetting = app.ui.settings.addSetting({ + id: "Comfy.UseNewMenu", + defaultValue: "Disabled", + name: "[Beta] Use new menu and workflow management. Note: On small screens the menu will always be at the top.", + type: "combo", + options: ["Disabled", "Top", "Bottom"], + onChange: async (v) => { + if (v && v !== "Disabled") { + if (!resizeHandler) { + resizeHandler = () => { + this.calculateSizeBreak(); + }; + window.addEventListener("resize", resizeHandler); + } + this.updatePosition(v); + } else { + if (resizeHandler) { + window.removeEventListener("resize", resizeHandler); + resizeHandler = null; + } + document.body.style.removeProperty("display"); + app.ui.menuContainer.style.removeProperty("display"); + this.element.style.display = "none"; + app.ui.restoreMenuPosition(); + } + window.dispatchEvent(new Event("resize")); + }, + }); + } + + updatePosition(v) { + document.body.style.display = "grid"; + this.app.ui.menuContainer.style.display = "none"; + this.element.style.removeProperty("display"); + this.position = v; + if (v === "Bottom") { + this.app.bodyBottom.append(this.element); + } else { + this.app.bodyTop.prepend(this.element); + } + this.calculateSizeBreak(); + } + + updateSizeBreak(idx, prevIdx, direction) { + const newSize = this.#sizeBreaks[idx]; + if (newSize === this.#sizeBreak) return; + this.#cachedInnerSize = null; + clearTimeout(this.#cacheTimeout); + + this.#sizeBreak = this.#sizeBreaks[idx]; + for (let i = 0; i < this.#sizeBreaks.length; i++) { + const sz = this.#sizeBreaks[i]; + if (sz === this.#sizeBreak) { + this.element.classList.add(sz); + } else { + this.element.classList.remove(sz); + } + if (i < idx) { + this.element.classList.add("lt-" + sz); + } else { + this.element.classList.remove("lt-" + sz); + } + } + + if (idx) { + // We're on a small screen, force the menu at the top + if (this.position !== "Top") { + this.updatePosition("Top"); + } + } else if (this.position != this.menuPositionSetting.value) { + // Restore user position + this.updatePosition(this.menuPositionSetting.value); + } + + // Allow multiple updates, but prevent bouncing + if (!direction) { + direction = prevIdx - idx; + } else if (direction != prevIdx - idx) { + return; + } + this.calculateSizeBreak(direction); + } + + calculateSizeBreak(direction = 0) { + let idx = this.#sizeBreaks.indexOf(this.#sizeBreak); + const currIdx = idx; + const innerSize = this.calculateInnerSize(idx); + if (window.innerWidth >= this.#lastSizeBreaks[this.#sizeBreaks[idx - 1]]) { + if (idx > 0) { + idx--; + } + } else if (innerSize > this.element.clientWidth) { + this.#lastSizeBreaks[this.#sizeBreak] = Math.max(window.innerWidth, innerSize); + // We need to shrink + if (idx < this.#sizeBreaks.length - 1) { + idx++; + } + } + + this.updateSizeBreak(idx, currIdx, direction); + } + + calculateInnerSize(idx) { + // Cache the inner size to prevent too much calculation when resizing the window + clearTimeout(this.#cacheTimeout); + if (this.#cachedInnerSize) { + // Extend cache time + this.#cacheTimeout = setTimeout(() => (this.#cachedInnerSize = null), 100); + } else { + let innerSize = 0; + let count = 1; + for (const c of this.element.children) { + if (c.classList.contains("comfyui-menu-push")) continue; // ignore right push + if (idx && c.classList.contains("comfyui-menu-mobile-collapse")) continue; // ignore collapse items + innerSize += c.clientWidth; + count++; + } + innerSize += 8 * count; + this.#cachedInnerSize = innerSize; + this.#cacheTimeout = setTimeout(() => (this.#cachedInnerSize = null), 100); + } + return this.#cachedInnerSize; + } + + /** + * @param {string} defaultName + */ + getFilename(defaultName) { + if (this.app.ui.settings.getSettingValue("Comfy.PromptFilename", true)) { + defaultName = prompt("Save workflow as:", defaultName); + if (!defaultName) return; + if (!defaultName.toLowerCase().endsWith(".json")) { + defaultName += ".json"; + } + } + return defaultName; + } + + /** + * @param {string} [filename] + * @param { "workflow" | "output" } [promptProperty] + */ + async exportWorkflow(filename, promptProperty) { + if (this.app.workflowManager.activeWorkflow?.path) { + filename = this.app.workflowManager.activeWorkflow.name; + } + const p = await this.app.graphToPrompt(); + const json = JSON.stringify(p[promptProperty], null, 2); + const blob = new Blob([json], { type: "application/json" }); + const file = this.getFilename(filename); + if (!file) return; + downloadBlob(file, blob); + } +} diff --git a/web/scripts/ui/menu/interruptButton.js b/web/scripts/ui/menu/interruptButton.js new file mode 100644 index 000000000..4db3328db --- /dev/null +++ b/web/scripts/ui/menu/interruptButton.js @@ -0,0 +1,23 @@ +// @ts-check + +import { api } from "../../api.js"; +import { ComfyButton } from "../components/button.js"; + +export function getInteruptButton(visibility) { + const btn = new ComfyButton({ + icon: "close", + tooltip: "Cancel current generation", + enabled: false, + action: () => { + api.interrupt(); + }, + classList: ["comfyui-button", "comfyui-interrupt-button", visibility], + }); + + api.addEventListener("status", ({ detail }) => { + const sz = detail?.exec_info?.queue_remaining; + btn.enabled = sz > 0; + }); + + return btn; +} diff --git a/web/scripts/ui/menu/menu.css b/web/scripts/ui/menu/menu.css new file mode 100644 index 000000000..20eeab2cf --- /dev/null +++ b/web/scripts/ui/menu/menu.css @@ -0,0 +1,701 @@ +.relative { + position: relative; +} +.hidden { + display: none !important; +} +.mdi.rotate270::before { + transform: rotate(270deg); +} + +/* Generic */ +.comfyui-button { + display: flex; + align-items: center; + gap: 0.5em; + cursor: pointer; + border: none; + border-radius: 4px; + padding: 4px 8px; + box-sizing: border-box; + margin: 0; +} + +.comfyui-button:disabled { + opacity: 0.5; + cursor: not-allowed; +} +.primary .comfyui-button, +.primary.comfyui-button { + background-color: var(--primary-bg) !important; + color: var(--primary-fg) !important; +} + +.primary .comfyui-button:not(:disabled):hover, +.primary.comfyui-button:not(:disabled):hover { + background-color: var(--primary-hover-bg) !important; + color: var(--primary-hover-fg) !important; +} + +/* Popup */ +.comfyui-popup { + position: absolute; + left: var(--left); + right: var(--right); + top: var(--top); + bottom: var(--bottom); + z-index: 2000; + max-height: calc(100vh - var(--limit) - 10px); + box-shadow: 3px 3px 5px 0px rgba(0, 0, 0, 0.3); +} + +.comfyui-popup:not(.open) { + display: none; +} + +.comfyui-popup.right.open { + border-top-left-radius: 4px; + border-bottom-right-radius: 4px; + border-bottom-left-radius: 4px; + overflow: hidden; +} +/* Split button */ +.comfyui-split-button { + position: relative; + display: flex; +} + +.comfyui-split-primary { + flex: auto; +} + +.comfyui-split-primary .comfyui-button { + border-top-right-radius: 0; + border-bottom-right-radius: 0; + border-right: 1px solid var(--comfy-menu-bg); + width: 100%; +} + +.comfyui-split-arrow .comfyui-button { + border-top-left-radius: 0; + border-bottom-left-radius: 0; + padding-left: 2px; + padding-right: 2px; +} + +.comfyui-split-button-popup { + white-space: nowrap; + background-color: var(--content-bg); + color: var(--content-fg); + display: flex; + flex-direction: column; + overflow: auto; +} + +.comfyui-split-button-popup.hover { + z-index: 2001; +} +.comfyui-split-button-popup > .comfyui-button { + border: none; + background-color: transparent; + color: var(--fg-color); + padding: 8px 12px 8px 8px; +} + +.comfyui-split-button-popup > .comfyui-button:not(:disabled):hover { + background-color: var(--comfy-input-bg); +} + +/* Button group */ +.comfyui-button-group { + display: flex; + border-radius: 4px; + overflow: hidden; +} + +.comfyui-button-group > .comfyui-button, +.comfyui-button-group > .comfyui-button-wrapper > .comfyui-button { + padding: 4px 10px; + border-radius: 0; +} + +/* Menu */ +.comfyui-menu { + width: 100vw; + background: var(--comfy-menu-bg); + color: var(--fg-color); + font-family: Arial, Helvetica, sans-serif; + font-size: 0.8em; + display: flex; + padding: 4px 8px; + align-items: center; + gap: 8px; + box-sizing: border-box; + z-index: 1000; + order: 0; + grid-column: 1/-1; + overflow: auto; + max-height: 90vh; +} + +.comfyui-menu>* { + flex-shrink: 0; +} +.comfyui-menu .mdi::before { + font-size: 18px; +} + +.comfyui-menu .comfyui-button { + background: var(--comfy-input-bg); + color: var(--fg-color); + white-space: nowrap; +} + +.comfyui-menu .comfyui-button:not(:disabled):hover { + background: var(--border-color); + color: var(--content-fg); +} + +.comfyui-menu .comfyui-split-button-popup > .comfyui-button { + border-radius: 0; + background-color: transparent; +} + +.comfyui-menu .comfyui-split-button-popup > .comfyui-button:not(:disabled):hover { + background-color: var(--comfy-input-bg); +} + +.comfyui-menu .comfyui-split-button-popup.left { + border-top-right-radius: 4px; + border-bottom-left-radius: 4px; + border-bottom-right-radius: 4px; +} + +.comfyui-menu .comfyui-button.popup-open { + background-color: var(--content-bg); + color: var(--content-fg); +} + +.comfyui-menu-push { + margin-left: -0.8em; + flex: auto; +} + +.comfyui-logo { + font-size: 1.2em; + margin: 0; + user-select: none; + cursor: default; +} + +/* Workflows */ +.comfyui-workflows-button { + flex-direction: row-reverse; + max-width: 200px; + position: relative; + z-index: 0; +} + +.comfyui-workflows-button.popup-open { + border-bottom-left-radius: 0; + border-bottom-right-radius: 0; +} +.comfyui-workflows-button.unsaved { + font-style: italic; +} +.comfyui-workflows-button-progress { + position: absolute; + top: 0; + left: 0; + background-color: green; + height: 100%; + border-radius: 4px; + z-index: -1; +} + +.comfyui-workflows-button > span { + flex: auto; + text-align: left; + overflow: hidden; +} +.comfyui-workflows-button-inner { + display: flex; + align-items: center; + gap: 7px; + width: 150px; +} +.comfyui-workflows-label { + overflow: hidden; + text-overflow: ellipsis; + direction: rtl; + flex: auto; + position: relative; +} + +.comfyui-workflows-button.unsaved .comfyui-workflows-label { + padding-left: 8px; +} + +.comfyui-workflows-button.unsaved .comfyui-workflows-label:after { + content: "*"; + position: absolute; + top: 0; + left: 0; +} +.comfyui-workflows-button-inner .mdi-graph::before { + transform: rotate(-90deg); +} + +.comfyui-workflows-popup { + font-family: Arial, Helvetica, sans-serif; + font-size: 0.8em; + padding: 10px; + overflow: auto; + background-color: var(--content-bg); + color: var(--content-fg); + border-top-right-radius: 4px; + border-bottom-right-radius: 4px; + border-bottom-left-radius: 4px; + z-index: 400; +} + +.comfyui-workflows-panel { + min-height: 150px; +} + +.comfyui-workflows-panel .lds-ring { + transform: translate(-50%); + position: absolute; + left: 50%; + top: 75px; +} + +.comfyui-workflows-panel h3 { + margin: 10px 0 10px 0; + font-size: 11px; + opacity: 0.8; +} + +.comfyui-workflows-panel section header { + display: flex; + justify-content: space-between; + align-items: center; +} +.comfy-ui-workflows-search .mdi { + position: relative; + top: 2px; + pointer-events: none; +} +.comfy-ui-workflows-search input { + background-color: var(--comfy-input-bg); + color: var(--input-text); + border: none; + border-radius: 4px; + padding: 4px 10px; + margin-left: -24px; + text-indent: 18px; +} +.comfy-ui-workflows-search input:placeholder-shown { + width: 10px; +} +.comfy-ui-workflows-search input:placeholder-shown:focus { + width: auto; +} +.comfyui-workflows-actions { + display: flex; + gap: 10px; + margin-bottom: 10px; +} + +.comfyui-workflows-actions .comfyui-button { + background: var(--comfy-input-bg); + color: var(--input-text); +} + +.comfyui-workflows-actions .comfyui-button:not(:disabled):hover { + background: var(--primary-bg); + color: var(--primary-fg); +} + +.comfyui-workflows-favorites, +.comfyui-workflows-open { + border-bottom: 1px solid var(--comfy-input-bg); + padding-bottom: 5px; + margin-bottom: 5px; +} + +.comfyui-workflows-open .active { + font-weight: bold; +} + +.comfyui-workflows-favorites:empty { + display: none; +} + +.comfyui-workflows-tree { + padding: 0; + margin: 0; +} + +.comfyui-workflows-tree:empty::after { + content: "No saved workflows"; + display: block; + text-align: center; +} +.comfyui-workflows-tree > ul { + padding: 0; +} + +.comfyui-workflows-tree > ul ul { + margin: 0; + padding: 0 0 0 25px; +} + +.comfyui-workflows-tree:not(.filtered) .closed > ul { + display: none; +} + +.comfyui-workflows-tree li, +.comfyui-workflows-tree-file { + --item-height: 32px; + list-style-type: none; + height: var(--item-height); + display: flex; + align-items: center; + gap: 5px; + cursor: pointer; + user-select: none; +} + +.comfyui-workflows-tree-file.active::before, +.comfyui-workflows-tree li:hover::before, +.comfyui-workflows-tree-file:hover::before { + content: ""; + position: absolute; + width: 100%; + left: 0; + height: var(--item-height); + background-color: var(--content-hover-bg); + color: var(--content-hover-fg); + z-index: -1; +} + +.comfyui-workflows-tree-file.active::before { + background-color: var(--primary-bg); + color: var(--primary-fg); +} + +.comfyui-workflows-tree-file.running:not(:hover)::before { + content: ""; + position: absolute; + width: var(--progress, 0); + left: 0; + height: var(--item-height); + background-color: green; + z-index: -1; +} + +.comfyui-workflows-tree-file.unsaved span { + font-style: italic; +} + +.comfyui-workflows-tree-file span { + flex: auto; +} + +.comfyui-workflows-tree-file span + .comfyui-workflows-file-action { + margin-left: 10px; +} + +.comfyui-workflows-tree-file .comfyui-workflows-file-action { + background-color: transparent; + color: var(--fg-color); + padding: 2px 4px; +} + +.lg ~ .comfyui-workflows-popup .comfyui-workflows-tree-file:not(:hover) .comfyui-workflows-file-action { + opacity: 0; +} + +.comfyui-workflows-tree-file .comfyui-workflows-file-action:hover { + background-color: var(--primary-bg); + color: var(--primary-fg); +} + +.comfyui-workflows-tree-file .comfyui-workflows-file-action-primary { + background-color: transparent; + color: var(--fg-color); + padding: 2px 4px; + margin: 0 -4px; +} + +.comfyui-workflows-file-action-favorite .mdi-star { + color: orange; +} + +/* View List */ +.comfyui-view-list-popup { + padding: 10px; + background-color: var(--content-bg); + color: var(--content-fg); + min-width: 170px; + min-height: 435px; + display: flex; + flex-direction: column; + align-items: center; + box-sizing: border-box; +} +.comfyui-view-list-popup h3 { + margin: 0 0 5px 0; +} +.comfyui-view-list-items { + width: 100%; + background: var(--comfy-menu-bg); + border-radius: 5px; + display: flex; + justify-content: center; + flex: auto; + align-items: center; + flex-direction: column; +} +.comfyui-view-list-items section { + max-height: 400px; + overflow: auto; + width: 100%; + display: grid; + grid-template-columns: auto auto auto; + align-items: center; + justify-content: center; + gap: 5px; + padding: 5px 0; +} +.comfyui-view-list-items section + section { + border-top: 1px solid var(--border-color); + margin-top: 10px; + padding-top: 5px; +} +.comfyui-view-list-items section h5 { + grid-column: 1 / 4; + text-align: center; + margin: 5px; +} +.comfyui-view-list-items span { + text-align: center; + padding: 0 2px; +} +.comfyui-view-list-popup header { + margin-bottom: 10px; + display: flex; + gap: 5px; +} +.comfyui-view-list-popup header .comfyui-button { + border: 1px solid transparent; +} +.comfyui-view-list-popup header .comfyui-button:not(:disabled):hover { + border: 1px solid var(--comfy-menu-bg); +} +/* Queue button */ +.comfyui-queue-button .comfyui-split-primary .comfyui-button { + padding-right: 12px; +} +.comfyui-queue-count { + margin-left: 5px; + border-radius: 10px; + background-color: rgb(8, 80, 153); + padding: 2px 4px; + font-size: 10px; + min-width: 1em; + display: inline-block; +} +/* Queue options*/ +.comfyui-queue-options { + padding: 10px; + font-family: Arial, Helvetica, sans-serif; + font-size: 12px; + display: flex; + gap: 10px; +} + +.comfyui-queue-batch { + display: flex; + flex-direction: column; + border-right: 1px solid var(--comfy-menu-bg); + padding-right: 10px; + gap: 5px; +} + +.comfyui-queue-batch input { + width: 145px; +} + +.comfyui-queue-batch .comfyui-queue-batch-value { + width: 70px; +} + +.comfyui-queue-mode { + display: flex; + flex-direction: column; +} + +.comfyui-queue-mode span { + font-weight: bold; + margin-bottom: 2px; +} + +.comfyui-queue-mode label { + display: flex; + flex-direction: row-reverse; + justify-content: start; + gap: 5px; + padding: 2px 0; +} + +.comfyui-queue-mode label input { + padding: 0; + margin: 0; +} + +/** Send to workflow widget selection dialog */ +.comfy-widget-selection-dialog { + border: none; +} + +.comfy-widget-selection-dialog div { + color: var(--fg-color); + font-family: Arial, Helvetica, sans-serif; +} + +.comfy-widget-selection-dialog h2 { + margin-top: 0; +} + +.comfy-widget-selection-dialog section { + width: fit-content; + display: flex; + flex-direction: column; +} + +.comfy-widget-selection-item { + display: flex; + gap: 10px; + align-items: center; +} + +.comfy-widget-selection-item span { + margin-right: auto; +} + +.comfy-widget-selection-item span::before { + content: '#' attr(data-id); + opacity: 0.5; + margin-right: 5px; +} + +.comfy-modal .comfy-widget-selection-item button { + font-size: 1em; +} + +/***** Responsive *****/ +.lg.comfyui-menu .lt-lg-show { + display: none !important; +} +.comfyui-menu:not(.lg) .nlg-hide { + display: none !important; +} +/** Large screen */ +.lg.comfyui-menu>.comfyui-menu-mobile-collapse .comfyui-button span, +.lg.comfyui-menu>.comfyui-menu-mobile-collapse.comfyui-button span { + display: none; +} +.lg.comfyui-menu>.comfyui-menu-mobile-collapse .comfyui-popup .comfyui-button span { + display: unset; +} + +/** Non large screen */ +.lt-lg.comfyui-menu { + flex-wrap: wrap; +} + +.lt-lg.comfyui-menu > *:not(.comfyui-menu-mobile-collapse) { + order: 1; +} + +.lt-lg.comfyui-menu > .comfyui-menu-mobile-collapse { + order: 9999; + width: 100%; +} + +.comfyui-body-bottom .lt-lg.comfyui-menu > .comfyui-menu-mobile-collapse { + order: -1; +} + +.comfyui-body-bottom .lt-lg.comfyui-menu > .comfyui-menu-button { + top: unset; + bottom: 4px; +} + +.lt-lg.comfyui-menu > .comfyui-menu-mobile-collapse.comfyui-button-group { + flex-wrap: wrap; +} + +.lt-lg.comfyui-menu > .comfyui-menu-mobile-collapse .comfyui-button, +.lt-lg.comfyui-menu > .comfyui-menu-mobile-collapse.comfyui-button { + padding: 10px; +} +.lt-lg.comfyui-menu > .comfyui-menu-mobile-collapse .comfyui-button, +.lt-lg.comfyui-menu > .comfyui-menu-mobile-collapse .comfyui-button-wrapper { + width: 100%; +} + +.lt-lg.comfyui-menu > .comfyui-menu-mobile-collapse .comfyui-popup { + position: static; + background-color: var(--comfy-input-bg); + max-width: unset; + max-height: 50vh; + overflow: auto; +} + +.lt-lg.comfyui-menu:not(.expanded) > .comfyui-menu-mobile-collapse { + display: none; +} + +.lt-lg .comfyui-queue-button { + margin-right: 44px; +} + +.lt-lg .comfyui-menu-button { + position: absolute; + top: 4px; + right: 8px; +} + +.lt-lg.comfyui-menu > .comfyui-menu-mobile-collapse .comfyui-view-list-popup { + border-radius: 0; +} + +.lt-lg.comfyui-menu .comfyui-workflows-popup { + width: 100vw; +} + +/** Small */ +.lt-md .comfyui-workflows-button-inner { + width: unset !important; +} +.lt-md .comfyui-workflows-label { + display: none; +} + +/** Extra small */ +.lt-sm .comfyui-queue-button { + margin-right: 0; + width: 100%; +} +.lt-sm .comfyui-queue-button .comfyui-button { + justify-content: center; +} +.lt-sm .comfyui-interrupt-button { + margin-right: 45px; +} +.comfyui-body-bottom .lt-sm.comfyui-menu > .comfyui-menu-button{ + bottom: 41px; +} \ No newline at end of file diff --git a/web/scripts/ui/menu/queueButton.js b/web/scripts/ui/menu/queueButton.js new file mode 100644 index 000000000..3c29ab090 --- /dev/null +++ b/web/scripts/ui/menu/queueButton.js @@ -0,0 +1,93 @@ +// @ts-check + +import { ComfyButton } from "../components/button.js"; +import { $el } from "../../ui.js"; +import { api } from "../../api.js"; +import { ComfySplitButton } from "../components/splitButton.js"; +import { ComfyQueueOptions } from "./queueOptions.js"; +import { prop } from "../../utils.js"; + +export class ComfyQueueButton { + element = $el("div.comfyui-queue-button"); + #internalQueueSize = 0; + + queuePrompt = async (e) => { + this.#internalQueueSize += this.queueOptions.batchCount; + // Hold shift to queue front + await this.app.queuePrompt(-e.shiftKey, this.queueOptions.batchCount); + }; + + constructor(app) { + this.app = app; + this.queueSizeElement = $el("span.comfyui-queue-count", { + textContent: "?", + }); + + const queue = new ComfyButton({ + content: $el("div", [ + $el("span", { + textContent: "Queue", + }), + this.queueSizeElement, + ]), + icon: "play", + classList: "comfyui-button", + action: this.queuePrompt, + }); + + this.queueOptions = new ComfyQueueOptions(app); + + const btn = new ComfySplitButton( + { + primary: queue, + mode: "click", + position: "absolute", + horizontal: "right", + }, + this.queueOptions.element + ); + btn.element.classList.add("primary"); + this.element.append(btn.element); + + this.autoQueueMode = prop(this, "autoQueueMode", "", () => { + switch (this.autoQueueMode) { + case "instant": + queue.icon = "infinity"; + break; + case "change": + queue.icon = "auto-mode"; + break; + default: + queue.icon = "play"; + break; + } + }); + + this.queueOptions.addEventListener("autoQueueMode", (e) => (this.autoQueueMode = e["detail"])); + + api.addEventListener("graphChanged", () => { + if (this.autoQueueMode === "change") { + if (this.#internalQueueSize) { + this.graphHasChanged = true; + } else { + this.graphHasChanged = false; + this.queuePrompt(); + } + } + }); + + api.addEventListener("status", ({ detail }) => { + this.#internalQueueSize = detail?.exec_info?.queue_remaining; + if (this.#internalQueueSize != null) { + this.queueSizeElement.textContent = this.#internalQueueSize > 99 ? "99+" : this.#internalQueueSize + ""; + this.queueSizeElement.title = `${this.#internalQueueSize} prompts in queue`; + if (!this.#internalQueueSize && !app.lastExecutionError) { + if (this.autoQueueMode === "instant" || (this.autoQueueMode === "change" && this.graphHasChanged)) { + this.graphHasChanged = false; + this.queuePrompt(); + } + } + } + }); + } +} diff --git a/web/scripts/ui/menu/queueOptions.js b/web/scripts/ui/menu/queueOptions.js new file mode 100644 index 000000000..f3d34e74e --- /dev/null +++ b/web/scripts/ui/menu/queueOptions.js @@ -0,0 +1,77 @@ +// @ts-check + +import { $el } from "../../ui.js"; +import { prop } from "../../utils.js"; + +export class ComfyQueueOptions extends EventTarget { + element = $el("div.comfyui-queue-options"); + + constructor(app) { + super(); + this.app = app; + + this.batchCountInput = $el("input", { + className: "comfyui-queue-batch-value", + type: "number", + min: "1", + value: "1", + oninput: () => (this.batchCount = +this.batchCountInput.value), + }); + + this.batchCountRange = $el("input", { + type: "range", + min: "1", + max: "100", + value: "1", + oninput: () => (this.batchCount = +this.batchCountRange.value), + }); + + this.element.append( + $el("div.comfyui-queue-batch", [ + $el( + "label", + { + textContent: "Batch count: ", + }, + this.batchCountInput + ), + this.batchCountRange, + ]) + ); + + const createOption = (text, value, checked = false) => + $el( + "label", + { textContent: text }, + $el("input", { + type: "radio", + name: "AutoQueueMode", + checked, + value, + oninput: (e) => (this.autoQueueMode = e.target["value"]), + }) + ); + + this.autoQueueEl = $el("div.comfyui-queue-mode", [ + $el("span", "Auto Queue:"), + createOption("Disabled", "", true), + createOption("Instant", "instant"), + createOption("On Change", "change"), + ]); + + this.element.append(this.autoQueueEl); + + this.batchCount = prop(this, "batchCount", 1, () => { + this.batchCountInput.value = this.batchCount + ""; + this.batchCountRange.value = this.batchCount + ""; + }); + + this.autoQueueMode = prop(this, "autoQueueMode", "Disabled", () => { + this.dispatchEvent( + new CustomEvent("autoQueueMode", { + detail: this.autoQueueMode, + }) + ); + }); + } +} diff --git a/web/scripts/ui/menu/viewHistory.js b/web/scripts/ui/menu/viewHistory.js new file mode 100644 index 000000000..de6b343dc --- /dev/null +++ b/web/scripts/ui/menu/viewHistory.js @@ -0,0 +1,27 @@ +// @ts-check + +import { ComfyButton } from "../components/button.js"; +import { ComfyViewList, ComfyViewListButton } from "./viewList.js"; + +export class ComfyViewHistoryButton extends ComfyViewListButton { + constructor(app) { + super(app, { + button: new ComfyButton({ + content: "View History", + icon: "history", + tooltip: "View history", + classList: "comfyui-button comfyui-history-button", + }), + list: ComfyViewHistoryList, + mode: "History", + }); + } +} + +export class ComfyViewHistoryList extends ComfyViewList { + async loadItems() { + const items = await super.loadItems(); + items["History"].reverse(); + return items; + } +} diff --git a/web/scripts/ui/menu/viewList.js b/web/scripts/ui/menu/viewList.js new file mode 100644 index 000000000..693ca335c --- /dev/null +++ b/web/scripts/ui/menu/viewList.js @@ -0,0 +1,203 @@ +// @ts-check + +import { ComfyButton } from "../components/button.js"; +import { $el } from "../../ui.js"; +import { api } from "../../api.js"; +import { ComfyPopup } from "../components/popup.js"; + +export class ComfyViewListButton { + get open() { + return this.popup.open; + } + + set open(open) { + this.popup.open = open; + } + + constructor(app, { button, list, mode }) { + this.app = app; + this.button = button; + this.element = $el("div.comfyui-button-wrapper", this.button.element); + this.popup = new ComfyPopup({ + target: this.element, + container: this.element, + horizontal: "right", + }); + this.list = new (list ?? ComfyViewList)(app, mode, this.popup); + this.popup.children = [this.list.element]; + this.popup.addEventListener("open", () => { + this.list.update(); + }); + this.popup.addEventListener("close", () => { + this.list.close(); + }); + this.button.withPopup(this.popup); + + api.addEventListener("status", () => { + if (this.popup.open) { + this.popup.update(); + } + }); + } +} + +export class ComfyViewList { + popup; + + constructor(app, mode, popup) { + this.app = app; + this.mode = mode; + this.popup = popup; + this.type = mode.toLowerCase(); + + this.items = $el(`div.comfyui-${this.type}-items.comfyui-view-list-items`); + this.clear = new ComfyButton({ + icon: "cancel", + content: "Clear", + action: async () => { + this.showSpinner(false); + await api.clearItems(this.type); + await this.update(); + }, + }); + + this.refresh = new ComfyButton({ + icon: "refresh", + content: "Refresh", + action: async () => { + await this.update(false); + }, + }); + + this.element = $el(`div.comfyui-${this.type}-popup.comfyui-view-list-popup`, [ + $el("h3", mode), + $el("header", [this.clear.element, this.refresh.element]), + this.items, + ]); + + api.addEventListener("status", () => { + if (this.popup.open) { + this.update(); + } + }); + } + + async close() { + this.items.replaceChildren(); + } + + async update(resize = true) { + this.showSpinner(resize); + const res = await this.loadItems(); + let any = false; + + const names = Object.keys(res); + const sections = names + .map((section) => { + const items = res[section]; + if (items?.length) { + any = true; + } else { + return; + } + + const rows = []; + if (names.length > 1) { + rows.push($el("h5", section)); + } + rows.push(...items.flatMap((item) => this.createRow(item, section))); + return $el("section", rows); + }) + .filter(Boolean); + + if (any) { + this.items.replaceChildren(...sections); + } else { + this.items.replaceChildren($el("h5", "None")); + } + + this.popup.update(); + this.clear.enabled = this.refresh.enabled = true; + this.element.style.removeProperty("height"); + } + + showSpinner(resize = true) { + // if (!this.spinner) { + // this.spinner = createSpinner(); + // } + // if (!resize) { + // this.element.style.height = this.element.clientHeight + "px"; + // } + // this.clear.enabled = this.refresh.enabled = false; + // this.items.replaceChildren( + // $el( + // "div", + // { + // style: { + // fontSize: "18px", + // }, + // }, + // this.spinner + // ) + // ); + // this.popup.update(); + } + + async loadItems() { + return await api.getItems(this.type); + } + + getRow(item, section) { + return { + text: item.prompt[0] + "", + actions: [ + { + text: "Load", + action: async () => { + try { + await this.app.loadGraphData(item.prompt[3].extra_pnginfo.workflow); + if (item.outputs) { + this.app.nodeOutputs = item.outputs; + } + } catch (error) { + alert("Error loading workflow: " + error.message); + console.error(error); + } + }, + }, + { + text: "Delete", + action: async () => { + try { + await api.deleteItem(this.type, item.prompt[1]); + this.update(); + } catch (error) {} + }, + }, + ], + }; + } + + createRow = (item, section) => { + const row = this.getRow(item, section); + return [ + $el("span", row.text), + ...row.actions.map( + (a) => + new ComfyButton({ + content: a.text, + action: async (e, btn) => { + btn.enabled = false; + try { + await a.action(); + } catch (error) { + throw error; + } finally { + btn.enabled = true; + } + }, + }).element + ), + ]; + }; +} diff --git a/web/scripts/ui/menu/viewQueue.js b/web/scripts/ui/menu/viewQueue.js new file mode 100644 index 000000000..97d012986 --- /dev/null +++ b/web/scripts/ui/menu/viewQueue.js @@ -0,0 +1,55 @@ +// @ts-check + +import { ComfyButton } from "../components/button.js"; +import { ComfyViewList, ComfyViewListButton } from "./viewList.js"; +import { api } from "../../api.js"; + +export class ComfyViewQueueButton extends ComfyViewListButton { + constructor(app) { + super(app, { + button: new ComfyButton({ + content: "View Queue", + icon: "format-list-numbered", + tooltip: "View queue", + classList: "comfyui-button comfyui-queue-button", + }), + list: ComfyViewQueueList, + mode: "Queue", + }); + } +} + +export class ComfyViewQueueList extends ComfyViewList { + getRow = (item, section) => { + if (section !== "Running") { + return super.getRow(item, section); + } + return { + text: item.prompt[0] + "", + actions: [ + { + text: "Load", + action: async () => { + try { + await this.app.loadGraphData(item.prompt[3].extra_pnginfo.workflow); + if (item.outputs) { + this.app.nodeOutputs = item.outputs; + } + } catch (error) { + alert("Error loading workflow: " + error.message); + console.error(error); + } + }, + }, + { + text: "Cancel", + action: async () => { + try { + await api.interrupt(); + } catch (error) {} + }, + }, + ], + }; + } +} diff --git a/web/scripts/ui/menu/workflows.js b/web/scripts/ui/menu/workflows.js new file mode 100644 index 000000000..afdff538a --- /dev/null +++ b/web/scripts/ui/menu/workflows.js @@ -0,0 +1,764 @@ +// @ts-check + +import { ComfyButton } from "../components/button.js"; +import { prop, getStorageValue, setStorageValue } from "../../utils.js"; +import { $el } from "../../ui.js"; +import { api } from "../../api.js"; +import { ComfyPopup } from "../components/popup.js"; +import { createSpinner } from "../spinner.js"; +import { ComfyWorkflow, trimJsonExt } from "../../workflows.js"; +import { ComfyAsyncDialog } from "../components/asyncDialog.js"; + +export class ComfyWorkflowsMenu { + #first = true; + element = $el("div.comfyui-workflows"); + + get open() { + return this.popup.open; + } + + set open(open) { + this.popup.open = open; + } + + /** + * @param {import("../../app.js").ComfyApp} app + */ + constructor(app) { + this.app = app; + this.#bindEvents(); + + const classList = { + "comfyui-workflows-button": true, + "comfyui-button": true, + unsaved: getStorageValue("Comfy.PreviousWorkflowUnsaved") === "true", + running: false, + }; + this.buttonProgress = $el("div.comfyui-workflows-button-progress"); + this.workflowLabel = $el("span.comfyui-workflows-label", ""); + this.button = new ComfyButton({ + content: $el("div.comfyui-workflows-button-inner", [$el("i.mdi.mdi-graph"), this.workflowLabel, this.buttonProgress]), + icon: "chevron-down", + classList, + }); + + this.element.append(this.button.element); + + this.popup = new ComfyPopup({ target: this.element, classList: "comfyui-workflows-popup" }); + this.content = new ComfyWorkflowsContent(app, this.popup); + this.popup.children = [this.content.element]; + this.popup.addEventListener("change", () => { + this.button.icon = "chevron-" + (this.popup.open ? "up" : "down"); + }); + this.button.withPopup(this.popup); + + this.unsaved = prop(this, "unsaved", classList.unsaved, (v) => { + classList.unsaved = v; + this.button.classList = classList; + setStorageValue("Comfy.PreviousWorkflowUnsaved", v); + }); + } + + #updateProgress = () => { + const prompt = this.app.workflowManager.activePrompt; + let percent = 0; + if (this.app.workflowManager.activeWorkflow === prompt?.workflow) { + const total = Object.values(prompt.nodes); + const done = total.filter(Boolean); + percent = (done.length / total.length) * 100; + } + this.buttonProgress.style.width = percent + "%"; + }; + + #updateActive = () => { + const active = this.app.workflowManager.activeWorkflow; + this.button.tooltip = active.path; + this.workflowLabel.textContent = active.name; + this.unsaved = active.unsaved; + + if (this.#first) { + this.#first = false; + this.content.load(); + } + + this.#updateProgress(); + }; + + #bindEvents() { + this.app.workflowManager.addEventListener("changeWorkflow", this.#updateActive); + this.app.workflowManager.addEventListener("rename", this.#updateActive); + this.app.workflowManager.addEventListener("delete", this.#updateActive); + + this.app.workflowManager.addEventListener("save", () => { + this.unsaved = this.app.workflowManager.activeWorkflow.unsaved; + }); + + this.app.workflowManager.addEventListener("execute", (e) => { + this.#updateProgress(); + }); + + api.addEventListener("graphChanged", () => { + this.unsaved = true; + }); + } + + #getMenuOptions(callback) { + const menu = []; + const directories = new Map(); + for (const workflow of this.app.workflowManager.workflows || []) { + const path = workflow.pathParts; + if (!path) continue; + let parent = menu; + let currentPath = ""; + for (let i = 0; i < path.length - 1; i++) { + currentPath += "/" + path[i]; + let newParent = directories.get(currentPath); + if (!newParent) { + newParent = { + title: path[i], + has_submenu: true, + submenu: { + options: [], + }, + }; + parent.push(newParent); + newParent = newParent.submenu.options; + directories.set(currentPath, newParent); + } + parent = newParent; + } + parent.push({ + title: trimJsonExt(path[path.length - 1]), + callback: () => callback(workflow), + }); + } + return menu; + } + + #getFavoriteMenuOptions(callback) { + const menu = []; + for (const workflow of this.app.workflowManager.workflows || []) { + if (workflow.isFavorite) { + menu.push({ + title: "⭐ " + workflow.name, + callback: () => callback(workflow), + }); + } + } + return menu; + } + + /** + * @param {import("../../app.js").ComfyApp} app + */ + registerExtension(app) { + const self = this; + app.registerExtension({ + name: "Comfy.Workflows", + async beforeRegisterNodeDef(nodeType) { + function getImageWidget(node) { + const inputs = { ...node.constructor?.nodeData?.input?.required, ...node.constructor?.nodeData?.input?.optional }; + for (const input in inputs) { + if (inputs[input][0] === "IMAGEUPLOAD") { + const imageWidget = node.widgets.find((w) => w.name === (inputs[input]?.[1]?.widget ?? "image")); + if (imageWidget) return imageWidget; + } + } + } + + function setWidgetImage(node, widget, img) { + const url = new URL(img.src); + const filename = url.searchParams.get("filename"); + const subfolder = url.searchParams.get("subfolder"); + const type = url.searchParams.get("type"); + const imageId = `${subfolder ? subfolder + "/" : ""}${filename} [${type}]`; + widget.value = imageId; + node.imgs = [img]; + app.graph.setDirtyCanvas(true, true); + } + + /** + * @param {HTMLImageElement} img + * @param {ComfyWorkflow} workflow + */ + async function sendToWorkflow(img, workflow) { + await workflow.load(); + let options = []; + const nodes = app.graph.computeExecutionOrder(false); + for (const node of nodes) { + const widget = getImageWidget(node); + if (widget == null) continue; + + if (node.title?.toLowerCase().includes("input")) { + options = [{ widget, node }]; + break; + } else { + options.push({ widget, node }); + } + } + + if (!options.length) { + alert("No image nodes have been found in this workflow!"); + return; + } else if (options.length > 1) { + const dialog = new WidgetSelectionDialog(options); + const res = await dialog.show(app); + if (!res) return; + options = [res]; + } + + setWidgetImage(options[0].node, options[0].widget, img); + } + + const getExtraMenuOptions = nodeType.prototype["getExtraMenuOptions"]; + nodeType.prototype["getExtraMenuOptions"] = function (_, options) { + const r = getExtraMenuOptions?.apply?.(this, arguments); + + if (app.ui.settings.getSettingValue("Comfy.UseNewMenu", false) === true) { + const t = /** @type { {imageIndex?: number, overIndex?: number, imgs: string[]} } */ /** @type {any} */ (this); + let img; + if (t.imageIndex != null) { + // An image is selected so select that + img = t.imgs?.[t.imageIndex]; + } else if (t.overIndex != null) { + // No image is selected but one is hovered + img = t.img?.s[t.overIndex]; + } + + if (img) { + let pos = options.findIndex((o) => o.content === "Save Image"); + if (pos === -1) { + pos = 0; + } else { + pos++; + } + + options.splice(pos, 0, { + content: "Send to workflow", + has_submenu: true, + submenu: { + options: [ + { + callback: () => sendToWorkflow(img, app.workflowManager.activeWorkflow), + title: "[Current workflow]", + }, + ...self.#getFavoriteMenuOptions(sendToWorkflow.bind(null, img)), + null, + ...self.#getMenuOptions(sendToWorkflow.bind(null, img)), + ], + }, + }); + } + } + + return r; + }; + }, + }); + } +} + +export class ComfyWorkflowsContent { + element = $el("div.comfyui-workflows-panel"); + treeState = {}; + treeFiles = {}; + /** @type { Map } */ + openFiles = new Map(); + /** @type {WorkflowElement} */ + activeElement = null; + + /** + * @param {import("../../app.js").ComfyApp} app + * @param {ComfyPopup} popup + */ + constructor(app, popup) { + this.app = app; + this.popup = popup; + this.actions = $el("div.comfyui-workflows-actions", [ + new ComfyButton({ + content: "Default", + icon: "file-code", + iconSize: 18, + classList: "comfyui-button primary", + tooltip: "Load default workflow", + action: () => { + popup.open = false; + app.loadGraphData(); + app.resetView(); + }, + }).element, + new ComfyButton({ + content: "Browse", + icon: "folder", + iconSize: 18, + tooltip: "Browse for an image or exported workflow", + action: () => { + popup.open = false; + app.ui.loadFile(); + }, + }).element, + new ComfyButton({ + content: "Blank", + icon: "plus-thick", + iconSize: 18, + tooltip: "Create a new blank workflow", + action: () => { + app.workflowManager.setWorkflow(null); + app.clean(); + app.graph.clear(); + app.workflowManager.activeWorkflow.track(); + popup.open = false; + }, + }).element, + ]); + + this.spinner = createSpinner(); + this.element.replaceChildren(this.actions, this.spinner); + + this.popup.addEventListener("open", () => this.load()); + this.popup.addEventListener("close", () => this.element.replaceChildren(this.actions, this.spinner)); + + this.app.workflowManager.addEventListener("favorite", (e) => { + const workflow = e["detail"]; + const button = this.treeFiles[workflow.path]?.primary; + if (!button) return; // Can happen when a workflow is renamed + button.icon = this.#getFavoriteIcon(workflow); + button.overIcon = this.#getFavoriteOverIcon(workflow); + this.updateFavorites(); + }); + + for (const e of ["save", "open", "close", "changeWorkflow"]) { + // TODO: dont be lazy and just update the specific element + app.workflowManager.addEventListener(e, () => this.updateOpen()); + } + this.app.workflowManager.addEventListener("rename", () => this.load()); + this.app.workflowManager.addEventListener("execute", (e) => this.#updateActive()); + } + + async load() { + await this.app.workflowManager.loadWorkflows(); + this.updateTree(); + this.updateFavorites(); + this.updateOpen(); + this.element.replaceChildren(this.actions, this.openElement, this.favoritesElement, this.treeElement); + } + + updateOpen() { + const current = this.openElement; + this.openFiles.clear(); + + this.openElement = $el("div.comfyui-workflows-open", [ + $el("h3", "Open"), + ...this.app.workflowManager.openWorkflows.map((w) => { + const wrapper = new WorkflowElement(this, w, { + primary: { element: $el("i.mdi.mdi-18px.mdi-progress-pencil") }, + buttons: [ + this.#getRenameButton(w), + new ComfyButton({ + icon: "close", + iconSize: 18, + classList: "comfyui-button comfyui-workflows-file-action", + tooltip: "Close workflow", + action: (e) => { + e.stopImmediatePropagation(); + this.app.workflowManager.closeWorkflow(w); + }, + }), + ], + }); + if (w.unsaved) { + wrapper.element.classList.add("unsaved"); + } + if(w === this.app.workflowManager.activeWorkflow) { + wrapper.element.classList.add("active"); + } + + this.openFiles.set(w, wrapper); + return wrapper.element; + }), + ]); + + this.#updateActive(); + current?.replaceWith(this.openElement); + } + + updateFavorites() { + const current = this.favoritesElement; + const favorites = [...this.app.workflowManager.workflows.filter((w) => w.isFavorite)]; + + this.favoritesElement = $el("div.comfyui-workflows-favorites", [ + $el("h3", "Favorites"), + ...favorites + .map((w) => { + return this.#getWorkflowElement(w).element; + }) + .filter(Boolean), + ]); + + current?.replaceWith(this.favoritesElement); + } + + filterTree() { + if (!this.filterText) { + this.treeRoot.classList.remove("filtered"); + // Unfilter whole tree + for (const item of Object.values(this.treeFiles)) { + item.element.parentElement.style.removeProperty("display"); + this.showTreeParents(item.element.parentElement); + } + return; + } + this.treeRoot.classList.add("filtered"); + const searchTerms = this.filterText.toLocaleLowerCase().split(" "); + for (const item of Object.values(this.treeFiles)) { + const parts = item.workflow.pathParts; + let termIndex = 0; + let valid = false; + for (const part of parts) { + let currentIndex = 0; + do { + currentIndex = part.indexOf(searchTerms[termIndex], currentIndex); + if (currentIndex > -1) currentIndex += searchTerms[termIndex].length; + } while (currentIndex !== -1 && ++termIndex < searchTerms.length); + + if (termIndex >= searchTerms.length) { + valid = true; + break; + } + } + if (valid) { + item.element.parentElement.style.removeProperty("display"); + this.showTreeParents(item.element.parentElement); + } else { + item.element.parentElement.style.display = "none"; + this.hideTreeParents(item.element.parentElement); + } + } + } + + hideTreeParents(element) { + // Hide all parents if no children are visible + if (element.parentElement?.classList.contains("comfyui-workflows-tree") === false) { + for (let i = 1; i < element.parentElement.children.length; i++) { + const c = element.parentElement.children[i]; + if (c.style.display !== "none") { + return; + } + } + element.parentElement.style.display = "none"; + this.hideTreeParents(element.parentElement); + } + } + + showTreeParents(element) { + if (element.parentElement?.classList.contains("comfyui-workflows-tree") === false) { + element.parentElement.style.removeProperty("display"); + this.showTreeParents(element.parentElement); + } + } + + updateTree() { + const current = this.treeElement; + const nodes = {}; + let typingTimeout; + + this.treeFiles = {}; + this.treeRoot = $el("ul.comfyui-workflows-tree"); + this.treeElement = $el("section", [ + $el("header", [ + $el("h3", "Browse"), + $el("div.comfy-ui-workflows-search", [ + $el("i.mdi.mdi-18px.mdi-magnify"), + $el("input", { + placeholder: "Search", + value: this.filterText ?? "", + oninput: (e) => { + this.filterText = e.target["value"]?.trim(); + clearTimeout(typingTimeout); + typingTimeout = setTimeout(() => this.filterTree(), 250); + }, + }), + ]), + ]), + this.treeRoot, + ]); + + for (const workflow of this.app.workflowManager.workflows) { + if (!workflow.pathParts) continue; + + let currentPath = ""; + let currentRoot = this.treeRoot; + + for (let i = 0; i < workflow.pathParts.length; i++) { + currentPath += (currentPath ? "\\" : "") + workflow.pathParts[i]; + const parentNode = nodes[currentPath] ?? this.#createNode(currentPath, workflow, i, currentRoot); + + nodes[currentPath] = parentNode; + currentRoot = parentNode; + } + } + + current?.replaceWith(this.treeElement); + this.filterTree(); + } + + #expandNode(el, workflow, thisPath, i) { + const expanded = !el.classList.toggle("closed"); + if (expanded) { + let c = ""; + for (let j = 0; j <= i; j++) { + c += (c ? "\\" : "") + workflow.pathParts[j]; + this.treeState[c] = true; + } + } else { + let c = thisPath; + for (let j = i + 1; j < workflow.pathParts.length; j++) { + c += (c ? "\\" : "") + workflow.pathParts[j]; + delete this.treeState[c]; + } + delete this.treeState[thisPath]; + } + } + + #updateActive() { + this.#removeActive(); + + const active = this.app.workflowManager.activePrompt; + if (!active?.workflow) return; + + const open = this.openFiles.get(active.workflow); + if (!open) return; + + this.activeElement = open; + + const total = Object.values(active.nodes); + const done = total.filter(Boolean); + const percent = done.length / total.length; + open.element.classList.add("running"); + open.element.style.setProperty("--progress", percent * 100 + "%"); + open.primary.element.classList.remove("mdi-progress-pencil"); + open.primary.element.classList.add("mdi-play"); + } + + #removeActive() { + if (!this.activeElement) return; + this.activeElement.element.classList.remove("running"); + this.activeElement.element.style.removeProperty("--progress"); + this.activeElement.primary.element.classList.add("mdi-progress-pencil"); + this.activeElement.primary.element.classList.remove("mdi-play"); + } + + /** @param {ComfyWorkflow} workflow */ + #getFavoriteIcon(workflow) { + return workflow.isFavorite ? "star" : "file-outline"; + } + + /** @param {ComfyWorkflow} workflow */ + #getFavoriteOverIcon(workflow) { + return workflow.isFavorite ? "star-off" : "star-outline"; + } + + /** @param {ComfyWorkflow} workflow */ + #getFavoriteTooltip(workflow) { + return workflow.isFavorite ? "Remove this workflow from your favorites" : "Add this workflow to your favorites"; + } + + /** @param {ComfyWorkflow} workflow */ + #getFavoriteButton(workflow, primary) { + return new ComfyButton({ + icon: this.#getFavoriteIcon(workflow), + overIcon: this.#getFavoriteOverIcon(workflow), + iconSize: 18, + classList: "comfyui-button comfyui-workflows-file-action-favorite" + (primary ? " comfyui-workflows-file-action-primary" : ""), + tooltip: this.#getFavoriteTooltip(workflow), + action: (e) => { + e.stopImmediatePropagation(); + workflow.favorite(!workflow.isFavorite); + }, + }); + } + + /** @param {ComfyWorkflow} workflow */ + #getDeleteButton(workflow) { + const deleteButton = new ComfyButton({ + icon: "delete", + tooltip: "Delete this workflow", + classList: "comfyui-button comfyui-workflows-file-action", + iconSize: 18, + action: async (e, btn) => { + e.stopImmediatePropagation(); + + if (btn.icon === "delete-empty") { + btn.enabled = false; + await workflow.delete(); + await this.load(); + } else { + btn.icon = "delete-empty"; + btn.element.style.background = "red"; + } + }, + }); + deleteButton.element.addEventListener("mouseleave", () => { + deleteButton.icon = "delete"; + deleteButton.element.style.removeProperty("background"); + }); + return deleteButton; + } + + /** @param {ComfyWorkflow} workflow */ + #getInsertButton(workflow) { + return new ComfyButton({ + icon: "file-move-outline", + iconSize: 18, + tooltip: "Insert this workflow into the current workflow", + classList: "comfyui-button comfyui-workflows-file-action", + action: (e) => { + if (!this.app.shiftDown) { + this.popup.open = false; + } + e.stopImmediatePropagation(); + if (!this.app.shiftDown) { + this.popup.open = false; + } + workflow.insert(); + }, + }); + } + + /** @param {ComfyWorkflow} workflow */ + #getRenameButton(workflow) { + return new ComfyButton({ + icon: "pencil", + tooltip: workflow.path ? "Rename this workflow" : "This workflow can't be renamed as it hasn't been saved.", + classList: "comfyui-button comfyui-workflows-file-action", + iconSize: 18, + enabled: !!workflow.path, + action: async (e) => { + e.stopImmediatePropagation(); + const newName = prompt("Enter new name", workflow.path); + if (newName) { + await workflow.rename(newName); + } + }, + }); + } + + /** @param {ComfyWorkflow} workflow */ + #getWorkflowElement(workflow) { + return new WorkflowElement(this, workflow, { + primary: this.#getFavoriteButton(workflow, true), + buttons: [this.#getInsertButton(workflow), this.#getRenameButton(workflow), this.#getDeleteButton(workflow)], + }); + } + + /** @param {ComfyWorkflow} workflow */ + #createLeafNode(workflow) { + const fileNode = this.#getWorkflowElement(workflow); + this.treeFiles[workflow.path] = fileNode; + return fileNode; + } + + #createNode(currentPath, workflow, i, currentRoot) { + const part = workflow.pathParts[i]; + + const parentNode = $el("ul" + (this.treeState[currentPath] ? "" : ".closed"), { + $: (el) => { + el.onclick = (e) => { + this.#expandNode(el, workflow, currentPath, i); + e.stopImmediatePropagation(); + }; + }, + }); + currentRoot.append(parentNode); + + // Create a node for the current part and an inner UL for its children if it isnt a leaf node + const leaf = i === workflow.pathParts.length - 1; + let nodeElement; + if (leaf) { + nodeElement = this.#createLeafNode(workflow).element; + } else { + nodeElement = $el("li", [$el("i.mdi.mdi-18px.mdi-folder"), $el("span", part)]); + } + parentNode.append(nodeElement); + return parentNode; + } +} + +class WorkflowElement { + /** + * @param { ComfyWorkflowsContent } parent + * @param { ComfyWorkflow } workflow + */ + constructor(parent, workflow, { tagName = "li", primary, buttons }) { + this.parent = parent; + this.workflow = workflow; + this.primary = primary; + this.buttons = buttons; + + this.element = $el( + tagName + ".comfyui-workflows-tree-file", + { + onclick: () => { + workflow.load(); + this.parent.popup.open = false; + }, + title: this.workflow.path, + }, + [this.primary?.element, $el("span", workflow.name), ...buttons.map((b) => b.element)] + ); + } +} + +class WidgetSelectionDialog extends ComfyAsyncDialog { + #options; + + /** + * @param {Array<{widget: {name: string}, node: {pos: [number, number], title: string, id: string, type: string}}>} options + */ + constructor(options) { + super(); + this.#options = options; + } + + show(app) { + this.element.classList.add("comfy-widget-selection-dialog"); + return super.show( + $el("div", [ + $el("h2", "Select image target"), + $el( + "p", + "This workflow has multiple image loader nodes, you can rename a node to include 'input' in the title for it to be automatically selected, or select one below." + ), + $el( + "section", + this.#options.map((opt) => { + return $el("div.comfy-widget-selection-item", [ + $el("span", { dataset: { id: opt.node.id } }, `${opt.node.title ?? opt.node.type} ${opt.widget.name}`), + $el( + "button.comfyui-button", + { + onclick: () => { + app.canvas.ds.offset[0] = -opt.node.pos[0] + 50; + app.canvas.ds.offset[1] = -opt.node.pos[1] + 50; + app.canvas.selectNode(opt.node); + app.graph.setDirtyCanvas(true, true); + }, + }, + "Show" + ), + $el( + "button.comfyui-button.primary", + { + onclick: () => { + this.close(opt); + }, + }, + "Select" + ), + ]); + }) + ), + ]) + ); + } +} \ No newline at end of file diff --git a/web/scripts/ui/settings.js b/web/scripts/ui/settings.js index 9e9d13af0..819e4e7d6 100644 --- a/web/scripts/ui/settings.js +++ b/web/scripts/ui/settings.js @@ -47,6 +47,17 @@ export class ComfySettingsDialog extends ComfyDialog { return Object.values(this.settingsLookup); } + #dispatchChange(id, value, oldValue) { + this.dispatchEvent( + new CustomEvent(id + ".change", { + detail: { + value, + oldValue + }, + }) + ); + } + async load() { if (this.app.storageLocation === "browser") { this.settingsValues = localStorage; @@ -56,7 +67,9 @@ export class ComfySettingsDialog extends ComfyDialog { // Trigger onChange for any settings added before load for (const id in this.settingsLookup) { - this.settingsLookup[id].onChange?.(this.settingsValues[this.getId(id)]); + const value = this.settingsValues[this.getId(id)]; + this.settingsLookup[id].onChange?.(value); + this.#dispatchChange(id, value); } } @@ -90,6 +103,7 @@ export class ComfySettingsDialog extends ComfyDialog { if (id in this.settingsLookup) { this.settingsLookup[id].onChange?.(value, oldValue); } + this.#dispatchChange(id, value, oldValue); await api.storeSetting(id, value); } @@ -136,6 +150,8 @@ export class ComfySettingsDialog extends ComfyDialog { onChange, name, render: () => { + if (type === "hidden") return; + const setter = (v) => { if (onChange) { onChange(v, value); @@ -310,7 +326,7 @@ export class ComfySettingsDialog extends ComfyDialog { }, [$el("th"), $el("th", { style: { width: "33%" } })] ), - ...this.settings.sort((a, b) => a.name.localeCompare(b.name)).map((s) => s.render()) + ...this.settings.sort((a, b) => a.name.localeCompare(b.name)).map((s) => s.render()).filter(Boolean) ); this.element.showModal(); } diff --git a/web/scripts/ui/utils.js b/web/scripts/ui/utils.js new file mode 100644 index 000000000..e37d8b41e --- /dev/null +++ b/web/scripts/ui/utils.js @@ -0,0 +1,56 @@ +/** + * @typedef { string | string[] | Record } ClassList + */ + +/** + * @param { HTMLElement } element + * @param { ClassList } classList + * @param { string[] } requiredClasses + */ +export function applyClasses(element, classList, ...requiredClasses) { + classList ??= ""; + + let str; + if (typeof classList === "string") { + str = classList; + } else if (classList instanceof Array) { + str = classList.join(" "); + } else { + str = Object.entries(classList).reduce((p, c) => { + if (c[1]) { + p += (p.length ? " " : "") + c[0]; + } + return p; + }, ""); + } + element.className = str; + if (requiredClasses) { + element.classList.add(...requiredClasses); + } +} + +/** + * @param { HTMLElement } element + * @param { { onHide?: (el: HTMLElement) => void, onShow?: (el: HTMLElement, value) => void } } [param1] + * @returns + */ +export function toggleElement(element, { onHide, onShow } = {}) { + let placeholder; + let hidden; + return (value) => { + if (value) { + if (hidden) { + hidden = false; + placeholder.replaceWith(element); + } + onShow?.(element, value); + } else { + if (!placeholder) { + placeholder = document.createComment(""); + } + hidden = true; + element.replaceWith(placeholder); + onHide?.(element); + } + }; +} diff --git a/web/scripts/utils.js b/web/scripts/utils.js index 01b988462..cda7600f6 100644 --- a/web/scripts/utils.js +++ b/web/scripts/utils.js @@ -1,4 +1,5 @@ import { $el } from "./ui.js"; +import { api } from "./api.js"; // Simple date formatter const parts = { @@ -25,6 +26,19 @@ function formatDate(text, date) { }); } + +export function clone(obj) { + try { + if (typeof structuredClone !== "undefined") { + return structuredClone(obj); + } + } catch (error) { + // structuredClone is stricter than using JSON.parse/stringify so fallback to that + } + + return JSON.parse(JSON.stringify(obj)); +} + export function applyTextReplacements(app, value) { return value.replace(/%([^%]+)%/g, function (match, text) { const split = text.split("."); @@ -86,3 +100,57 @@ export async function addStylesheet(urlOrFile, relativeTo) { }); }); } + +/** + * @param { string } filename + * @param { Blob } blob + */ +export function downloadBlob(filename, blob) { + const url = URL.createObjectURL(blob); + const a = $el("a", { + href: url, + download: filename, + style: { display: "none" }, + parent: document.body, + }); + a.click(); + setTimeout(function () { + a.remove(); + window.URL.revokeObjectURL(url); + }, 0); +} + +/** + * @template T + * @param {string} name + * @param {T} [defaultValue] + * @param {(currentValue: any, previousValue: any)=>void} [onChanged] + * @returns {T} + */ +export function prop(target, name, defaultValue, onChanged) { + let currentValue; + Object.defineProperty(target, name, { + get() { + return currentValue; + }, + set(newValue) { + const prevValue = currentValue; + currentValue = newValue; + onChanged?.(currentValue, prevValue, target, name); + }, + }); + return defaultValue; +} + +export function getStorageValue(id) { + const clientId = api.clientId ?? api.initialClientId; + return (clientId && sessionStorage.getItem(`${id}:${clientId}`)) ?? localStorage.getItem(id); +} + +export function setStorageValue(id, value) { + const clientId = api.clientId ?? api.initialClientId; + if (clientId) { + sessionStorage.setItem(`${id}:${clientId}`, value); + } + localStorage.setItem(id, value); +} \ No newline at end of file diff --git a/web/scripts/workflows.js b/web/scripts/workflows.js new file mode 100644 index 000000000..16bbc9976 --- /dev/null +++ b/web/scripts/workflows.js @@ -0,0 +1,450 @@ +// @ts-check + +import { api } from "./api.js"; +import { ChangeTracker } from "./changeTracker.js"; +import { ComfyAsyncDialog } from "./ui/components/asyncDialog.js"; +import { getStorageValue, setStorageValue } from "./utils.js"; + +function appendJsonExt(path) { + if (!path.toLowerCase().endsWith(".json")) { + path += ".json"; + } + return path; +} + +export function trimJsonExt(path) { + return path?.replace(/\.json$/, ""); +} + +export class ComfyWorkflowManager extends EventTarget { + /** @type {string | null} */ + #activePromptId = null; + #unsavedCount = 0; + #activeWorkflow; + + /** @type {Record} */ + workflowLookup = {}; + /** @type {Array} */ + workflows = []; + /** @type {Array} */ + openWorkflows = []; + /** @type {Record}>} */ + queuedPrompts = {}; + + get activeWorkflow() { + return this.#activeWorkflow ?? this.openWorkflows[0]; + } + + get activePromptId() { + return this.#activePromptId; + } + + get activePrompt() { + return this.queuedPrompts[this.#activePromptId]; + } + + /** + * @param {import("./app.js").ComfyApp} app + */ + constructor(app) { + super(); + this.app = app; + ChangeTracker.init(app); + + this.#bindExecutionEvents(); + } + + #bindExecutionEvents() { + // TODO: on reload, set active prompt based on the latest ws message + + const emit = () => this.dispatchEvent(new CustomEvent("execute", { detail: this.activePrompt })); + let executing = null; + api.addEventListener("execution_start", (e) => { + this.#activePromptId = e.detail.prompt_id; + + // This event can fire before the event is stored, so put a placeholder + this.queuedPrompts[this.#activePromptId] ??= { nodes: {} }; + emit(); + }); + api.addEventListener("execution_cached", (e) => { + if (!this.activePrompt) return; + for (const n of e.detail.nodes) { + this.activePrompt.nodes[n] = true; + } + emit(); + }); + api.addEventListener("executed", (e) => { + if (!this.activePrompt) return; + this.activePrompt.nodes[e.detail.node] = true; + emit(); + }); + api.addEventListener("executing", (e) => { + if (!this.activePrompt) return; + + if (executing) { + // Seems sometimes nodes that are cached fire executing but not executed + this.activePrompt.nodes[executing] = true; + } + executing = e.detail; + if (!executing) { + delete this.queuedPrompts[this.#activePromptId]; + this.#activePromptId = null; + } + emit(); + }); + } + + async loadWorkflows() { + try { + let favorites; + const resp = await api.getUserData("workflows/.index.json"); + let info; + if (resp.status === 200) { + info = await resp.json(); + favorites = new Set(info?.favorites ?? []); + } else { + favorites = new Set(); + } + + const workflows = (await api.listUserData("workflows", true, true)).map((w) => { + let workflow = this.workflowLookup[w[0]]; + if (!workflow) { + workflow = new ComfyWorkflow(this, w[0], w.slice(1), favorites.has(w[0])); + this.workflowLookup[workflow.path] = workflow; + } + return workflow; + }); + + this.workflows = workflows; + } catch (error) { + alert("Error loading workflows: " + (error.message ?? error)); + this.workflows = []; + } + } + + async saveWorkflowMetadata() { + await api.storeUserData("workflows/.index.json", { + favorites: [...this.workflows.filter((w) => w.isFavorite).map((w) => w.path)], + }); + } + + /** + * @param {string | ComfyWorkflow | null} workflow + */ + setWorkflow(workflow) { + if (workflow && typeof workflow === "string") { + // Selected by path, i.e. on reload of last workflow + const found = this.workflows.find((w) => w.path === workflow); + if (found) { + workflow = found; + workflow.unsaved = !workflow || getStorageValue("Comfy.PreviousWorkflowUnsaved") === "true"; + } + } + + if (!(workflow instanceof ComfyWorkflow)) { + // Still not found, either reloading a deleted workflow or blank + workflow = new ComfyWorkflow(this, workflow || "Unsaved Workflow" + (this.#unsavedCount++ ? ` (${this.#unsavedCount})` : "")); + } + + const index = this.openWorkflows.indexOf(workflow); + if (index === -1) { + // Opening a new workflow + this.openWorkflows.push(workflow); + } + + this.#activeWorkflow = workflow; + + setStorageValue("Comfy.PreviousWorkflow", this.activeWorkflow.path ?? ""); + this.dispatchEvent(new CustomEvent("changeWorkflow")); + } + + storePrompt({ nodes, id }) { + this.queuedPrompts[id] ??= {}; + this.queuedPrompts[id].nodes = { + ...nodes.reduce((p, n) => { + p[n] = false; + return p; + }, {}), + ...this.queuedPrompts[id].nodes, + }; + this.queuedPrompts[id].workflow = this.activeWorkflow; + } + + /** + * @param {ComfyWorkflow} workflow + */ + async closeWorkflow(workflow, warnIfUnsaved = true) { + if (!workflow.isOpen) { + return true; + } + if (workflow.unsaved && warnIfUnsaved) { + const res = await ComfyAsyncDialog.prompt({ + title: "Save Changes?", + message: `Do you want to save changes to "${workflow.path ?? workflow.name}" before closing?`, + actions: ["Yes", "No", "Cancel"], + }); + if (res === "Yes") { + const active = this.activeWorkflow; + if (active !== workflow) { + // We need to switch to the workflow to save it + await workflow.load(); + } + + if (!(await workflow.save())) { + // Save was canceled, restore the previous workflow + if (active !== workflow) { + await active.load(); + } + return; + } + } else if (res === "Cancel") { + return; + } + } + workflow.changeTracker = null; + this.openWorkflows.splice(this.openWorkflows.indexOf(workflow), 1); + if (this.openWorkflows.length) { + this.#activeWorkflow = this.openWorkflows[0]; + await this.#activeWorkflow.load(); + } else { + // Load default + await this.app.loadGraphData(); + } + } +} + +export class ComfyWorkflow { + #name; + #path; + #pathParts; + #isFavorite = false; + /** @type {ChangeTracker | null} */ + changeTracker = null; + unsaved = false; + + get name() { + return this.#name; + } + + get path() { + return this.#path; + } + + get pathParts() { + return this.#pathParts; + } + + get isFavorite() { + return this.#isFavorite; + } + + get isOpen() { + return !!this.changeTracker; + } + + /** + * @overload + * @param {ComfyWorkflowManager} manager + * @param {string} path + */ + /** + * @overload + * @param {ComfyWorkflowManager} manager + * @param {string} path + * @param {string[]} pathParts + * @param {boolean} isFavorite + */ + /** + * @param {ComfyWorkflowManager} manager + * @param {string} path + * @param {string[]} [pathParts] + * @param {boolean} [isFavorite] + */ + constructor(manager, path, pathParts, isFavorite) { + this.manager = manager; + if (pathParts) { + this.#updatePath(path, pathParts); + this.#isFavorite = isFavorite; + } else { + this.#name = path; + this.unsaved = true; + } + } + + /** + * @param {string} path + * @param {string[]} [pathParts] + */ + #updatePath(path, pathParts) { + this.#path = path; + + if (!pathParts) { + if (!path.includes("\\")) { + pathParts = path.split("/"); + } else { + pathParts = path.split("\\"); + } + } + + this.#pathParts = pathParts; + this.#name = trimJsonExt(pathParts[pathParts.length - 1]); + } + + async getWorkflowData() { + const resp = await api.getUserData("workflows/" + this.path); + if (resp.status !== 200) { + alert(`Error loading workflow file '${this.path}': ${resp.status} ${resp.statusText}`); + return; + } + return await resp.json(); + } + + load = async () => { + if (this.isOpen) { + await this.manager.app.loadGraphData(this.changeTracker.activeState, true, this); + } else { + const data = await this.getWorkflowData(); + if (!data) return; + await this.manager.app.loadGraphData(data, true, this); + } + }; + + async save(saveAs = false) { + if (!this.path || saveAs) { + return !!(await this.#save(null, false)); + } else { + return !!(await this.#save(this.path, true)); + } + } + + /** + * @param {boolean} value + */ + async favorite(value) { + try { + if (this.#isFavorite === value) return; + this.#isFavorite = value; + await this.manager.saveWorkflowMetadata(); + this.manager.dispatchEvent(new CustomEvent("favorite", { detail: this })); + } catch (error) { + alert("Error favoriting workflow " + this.path + "\n" + (error.message ?? error)); + } + } + + /** + * @param {string} path + */ + async rename(path) { + path = appendJsonExt(path); + let resp = await api.moveUserData("workflows/" + this.path, "workflows/" + path); + + if (resp.status === 409) { + if (!confirm(`Workflow '${path}' already exists, do you want to overwrite it?`)) return resp; + resp = await api.moveUserData("workflows/" + this.path, "workflows/" + path, { overwrite: true }); + } + + if (resp.status !== 200) { + alert(`Error renaming workflow file '${this.path}': ${resp.status} ${resp.statusText}`); + return; + } + + const isFav = this.isFavorite; + if (isFav) { + await this.favorite(false); + } + path = (await resp.json()).substring("workflows/".length); + this.#updatePath(path, null); + if (isFav) { + await this.favorite(true); + } + this.manager.dispatchEvent(new CustomEvent("rename", { detail: this })); + setStorageValue("Comfy.PreviousWorkflow", this.path ?? ""); + } + + async insert() { + const data = await this.getWorkflowData(); + if (!data) return; + + const old = localStorage.getItem("litegrapheditor_clipboard"); + const graph = new LGraph(data); + const canvas = new LGraphCanvas(null, graph, { skip_events: true, skip_render: true }); + canvas.selectNodes(); + canvas.copyToClipboard(); + this.manager.app.canvas.pasteFromClipboard(); + localStorage.setItem("litegrapheditor_clipboard", old); + } + + async delete() { + // TODO: fix delete of current workflow - should mark workflow as unsaved and when saving use old name by default + + try { + if (this.isFavorite) { + await this.favorite(false); + } + await api.deleteUserData("workflows/" + this.path); + this.unsaved = true; + this.#path = null; + this.#pathParts = null; + this.manager.workflows.splice(this.manager.workflows.indexOf(this), 1); + this.manager.dispatchEvent(new CustomEvent("delete", { detail: this })); + } catch (error) { + alert(`Error deleting workflow: ${error.message || error}`); + } + } + + track() { + if (this.changeTracker) { + this.changeTracker.restore(); + } else { + this.changeTracker = new ChangeTracker(this); + } + } + + /** + * @param {string|null} path + * @param {boolean} overwrite + */ + async #save(path, overwrite) { + if (!path) { + path = prompt("Save workflow as:", trimJsonExt(this.path) ?? this.name ?? "workflow"); + if (!path) return; + } + + path = appendJsonExt(path); + + const p = await this.manager.app.graphToPrompt(); + const json = JSON.stringify(p.workflow, null, 2); + let resp = await api.storeUserData("workflows/" + path, json, { stringify: false, throwOnError: false, overwrite }); + if (resp.status === 409) { + if (!confirm(`Workflow '${path}' already exists, do you want to overwrite it?`)) return; + resp = await api.storeUserData("workflows/" + path, json, { stringify: false }); + } + + if (resp.status !== 200) { + alert(`Error saving workflow '${this.path}': ${resp.status} ${resp.statusText}`); + return; + } + + path = (await resp.json()).substring("workflows/".length); + + if (!this.path) { + // Saved new workflow, patch this instance + this.#updatePath(path, null); + await this.manager.loadWorkflows(); + this.unsaved = false; + this.manager.dispatchEvent(new CustomEvent("rename", { detail: this })); + setStorageValue("Comfy.PreviousWorkflow", this.path ?? ""); + } else if (path !== this.path) { + // Saved as, open the new copy + await this.manager.loadWorkflows(); + const workflow = this.manager.workflowLookup[path]; + await workflow.load(); + } else { + // Normal save + this.unsaved = false; + this.manager.dispatchEvent(new CustomEvent("save", { detail: this })); + } + + return true; + } +} diff --git a/web/style.css b/web/style.css index cf7a8b9ea..8091a489f 100644 --- a/web/style.css +++ b/web/style.css @@ -1,3 +1,5 @@ +@import url("scripts/ui/menu/menu.css"); + :root { --fg-color: #000; --bg-color: #fff; @@ -10,12 +12,24 @@ --border-color: #4e4e4e; --tr-even-bg-color: #222; --tr-odd-bg-color: #353535; + --primary-bg: #236692; + --primary-fg: #ffffff; + --primary-hover-bg: #3485bb; + --primary-hover-fg: #ffffff; + --content-bg: #e0e0e0; + --content-fg: #000; + --content-hover-bg: #adadad; + --content-hover-fg: #000; } @media (prefers-color-scheme: dark) { :root { --fg-color: #fff; --bg-color: #202020; + --content-bg: #4e4e4e; + --content-fg: #fff; + --content-hover-bg: #222; + --content-hover-fg: #fff; } } @@ -26,11 +40,41 @@ body { overflow: hidden; background-color: var(--bg-color); color: var(--fg-color); + grid-template-columns: auto 1fr auto; + grid-template-rows: auto auto 1fr auto; + min-height: -webkit-fill-available; + max-height: -webkit-fill-available; + min-width: -webkit-fill-available; + max-width: -webkit-fill-available; +} + +.comfyui-body-top { + order: 0; + grid-column: 1/-1; + z-index: 10; +} + +.comfyui-body-left { + order: 1; + z-index: 10; } #graph-canvas { width: 100%; height: 100%; + order: 2; + grid-column: 1/-1; +} + +.comfyui-body-right { + order: 3; + z-index: 10; +} + +.comfyui-body-bottom { + order: 4; + grid-column: 1/-1; + z-index: 10; } .comfy-multiline-input { @@ -364,6 +408,37 @@ dialog::backdrop { background: rgba(0, 0, 0, 0.5); } +.comfy-dialog.comfyui-dialog { + top: 0; +} + +.comfy-dialog.comfy-modal { + font-family: Arial, sans-serif; + border-color: var(--bg-color); + box-shadow: none; + border: 2px solid var(--border-color); +} + +.comfy-dialog .comfy-modal-content { + flex-direction: row; + flex-wrap: wrap; + gap: 10px; + color: var(--fg-color); +} + +.comfy-dialog .comfy-modal-content h3 { + margin-top: 0; +} + +.comfy-dialog .comfy-modal-content > p { + width: 100%; +} + +.comfy-dialog .comfy-modal-content > .comfyui-button { + flex: 1; + justify-content: center; +} + #comfy-settings-dialog { padding: 0; width: 41rem; diff --git a/web/types/comfy.d.ts b/web/types/comfy.d.ts index f7129b555..9a338b349 100644 --- a/web/types/comfy.d.ts +++ b/web/types/comfy.d.ts @@ -10,24 +10,24 @@ export interface ComfyExtension { * Allows any initialisation, e.g. loading resources. Called after the canvas is created but before nodes are added * @param app The ComfyUI app instance */ - init(app: ComfyApp): Promise; + init?(app: ComfyApp): Promise; /** * Allows any additonal setup, called after the application is fully set up and running * @param app The ComfyUI app instance */ - setup(app: ComfyApp): Promise; + setup?(app: ComfyApp): Promise; /** * Called before nodes are registered with the graph * @param defs The collection of node definitions, add custom ones or edit existing ones * @param app The ComfyUI app instance */ - addCustomNodeDefs(defs: Record, app: ComfyApp): Promise; + addCustomNodeDefs?(defs: Record, app: ComfyApp): Promise; /** * Allows the extension to add custom widgets * @param app The ComfyUI app instance * @returns An array of {[widget name]: widget data} */ - getCustomWidgets( + getCustomWidgets?( app: ComfyApp ): Promise< Record { widget?: IWidget; minWidth?: number; minHeight?: number }> @@ -38,12 +38,12 @@ export interface ComfyExtension { * @param nodeData The original node object info config object * @param app The ComfyUI app instance */ - beforeRegisterNodeDef(nodeType: typeof LGraphNode, nodeData: ComfyObjectInfo, app: ComfyApp): Promise; + beforeRegisterNodeDef?(nodeType: typeof LGraphNode, nodeData: ComfyObjectInfo, app: ComfyApp): Promise; /** * Allows the extension to register additional nodes with LGraph after standard nodes are added * @param app The ComfyUI app instance */ - registerCustomNodes(app: ComfyApp): Promise; + registerCustomNodes?(app: ComfyApp): Promise; /** * Allows the extension to modify a node that has been reloaded onto the graph. * If you break something in the backend and want to patch workflows in the frontend @@ -51,13 +51,13 @@ export interface ComfyExtension { * @param node The node that has been loaded * @param app The ComfyUI app instance */ - loadedGraphNode(node: LGraphNode, app: ComfyApp); + loadedGraphNode?(node: LGraphNode, app: ComfyApp); /** * Allows the extension to run code after the constructor of the node * @param node The node that has been created * @param app The ComfyUI app instance */ - nodeCreated(node: LGraphNode, app: ComfyApp); + nodeCreated?(node: LGraphNode, app: ComfyApp); } export type ComfyObjectInfo = { From 69d710e40f43b87dd7124b9ee1e8982f987827e9 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Tue, 25 Jun 2024 07:41:52 -0400 Subject: [PATCH 004/133] Implement my alternative take on CFG++ as the euler_pp sampler. Add euler_ancestral_pp which is the ancestral version of euler with the same modification. --- comfy/k_diffusion/sampling.py | 55 ++++++++++++++++++++++++- comfy/samplers.py | 2 +- comfy_extras/nodes_advanced_samplers.py | 25 +---------- 3 files changed, 56 insertions(+), 26 deletions(-) diff --git a/comfy/k_diffusion/sampling.py b/comfy/k_diffusion/sampling.py index 78896b8b5..9b58cb1dc 100644 --- a/comfy/k_diffusion/sampling.py +++ b/comfy/k_diffusion/sampling.py @@ -7,7 +7,7 @@ import torchsde from tqdm.auto import trange, tqdm from . import utils - +import comfy.model_patcher def append_zero(x): return torch.cat([x, x.new_zeros([1])]) @@ -945,3 +945,56 @@ def sample_ipndm_v(model, x, sigmas, extra_args=None, callback=None, disable=Non buffer_model.append(d_cur.detach()) return x_next + + +@torch.no_grad() +def sample_euler_pp(model, x, sigmas, extra_args=None, callback=None, disable=None): + extra_args = {} if extra_args is None else extra_args + + temp = [0] + def post_cfg_function(args): + temp[0] = args["uncond_denoised"] + return args["denoised"] + + model_options = extra_args.get("model_options", {}).copy() + extra_args["model_options"] = comfy.model_patcher.set_model_options_post_cfg_function(model_options, post_cfg_function, disable_cfg1_optimization=True) + + s_in = x.new_ones([x.shape[0]]) + for i in trange(len(sigmas) - 1, disable=disable): + sigma_hat = sigmas[i] + denoised = model(x, sigma_hat * s_in, **extra_args) + d = to_d(x - denoised + temp[0], sigma_hat, denoised) + if callback is not None: + callback({'x': x, 'i': i, 'sigma': sigmas[i], 'sigma_hat': sigma_hat, 'denoised': denoised}) + dt = sigmas[i + 1] - sigma_hat + # Euler method + x = x + d * dt + return x + +@torch.no_grad() +def sample_euler_ancestral_pp(model, x, sigmas, extra_args=None, callback=None, disable=None, eta=1., s_noise=1., noise_sampler=None): + """Ancestral sampling with Euler method steps.""" + extra_args = {} if extra_args is None else extra_args + noise_sampler = default_noise_sampler(x) if noise_sampler is None else noise_sampler + + temp = [0] + def post_cfg_function(args): + temp[0] = args["uncond_denoised"] + return args["denoised"] + + model_options = extra_args.get("model_options", {}).copy() + extra_args["model_options"] = comfy.model_patcher.set_model_options_post_cfg_function(model_options, post_cfg_function, disable_cfg1_optimization=True) + + s_in = x.new_ones([x.shape[0]]) + for i in trange(len(sigmas) - 1, disable=disable): + denoised = model(x, sigmas[i] * s_in, **extra_args) + sigma_down, sigma_up = get_ancestral_step(sigmas[i], sigmas[i + 1], eta=eta) + if callback is not None: + callback({'x': x, 'i': i, 'sigma': sigmas[i], 'sigma_hat': sigmas[i], 'denoised': denoised}) + d = to_d(x - denoised + temp[0], sigmas[i], denoised) + # Euler method + dt = sigma_down - sigmas[i] + x = x + d * dt + if sigmas[i + 1] > 0: + x = x + noise_sampler(sigmas[i], sigmas[i + 1]) * s_noise * sigma_up + return x diff --git a/comfy/samplers.py b/comfy/samplers.py index 55b1486b4..c3a80dde0 100644 --- a/comfy/samplers.py +++ b/comfy/samplers.py @@ -537,7 +537,7 @@ class Sampler: sigma = float(sigmas[0]) return math.isclose(max_sigma, sigma, rel_tol=1e-05) or sigma > max_sigma -KSAMPLER_NAMES = ["euler", "euler_ancestral", "heun", "heunpp2","dpm_2", "dpm_2_ancestral", +KSAMPLER_NAMES = ["euler", "euler_pp", "euler_ancestral", "euler_ancestral_pp", "heun", "heunpp2","dpm_2", "dpm_2_ancestral", "lms", "dpm_fast", "dpm_adaptive", "dpmpp_2s_ancestral", "dpmpp_sde", "dpmpp_sde_gpu", "dpmpp_2m", "dpmpp_2m_sde", "dpmpp_2m_sde_gpu", "dpmpp_3m_sde", "dpmpp_3m_sde_gpu", "ddpm", "lcm", "ipndm", "ipndm_v"] diff --git a/comfy_extras/nodes_advanced_samplers.py b/comfy_extras/nodes_advanced_samplers.py index 7aa89c644..cee3a10c4 100644 --- a/comfy_extras/nodes_advanced_samplers.py +++ b/comfy_extras/nodes_advanced_samplers.py @@ -82,29 +82,6 @@ def sample_euler_cfgpp(model, x, sigmas, extra_args=None, callback=None, disable x = denoised + sigmas[i + 1] * d return x -@torch.no_grad() -def sample_euler_cfgpp_alt(model, x, sigmas, extra_args=None, callback=None, disable=None): - extra_args = {} if extra_args is None else extra_args - - temp = [0] - def post_cfg_function(args): - temp[0] = args["uncond_denoised"] - return args["denoised"] - - model_options = extra_args.get("model_options", {}).copy() - extra_args["model_options"] = comfy.model_patcher.set_model_options_post_cfg_function(model_options, post_cfg_function, disable_cfg1_optimization=True) - - s_in = x.new_ones([x.shape[0]]) - for i in trange(len(sigmas) - 1, disable=disable): - sigma_hat = sigmas[i] - denoised = model(x, sigma_hat * s_in, **extra_args) - d = to_d(x - denoised + temp[0], sigma_hat, denoised) - if callback is not None: - callback({'x': x, 'i': i, 'sigma': sigmas[i], 'sigma_hat': sigma_hat, 'denoised': denoised}) - dt = sigmas[i + 1] - sigma_hat - # Euler method - x = x + d * dt - return x class SamplerEulerCFGpp: @classmethod @@ -122,7 +99,7 @@ class SamplerEulerCFGpp: if version == "regular": sampler = comfy.samplers.KSAMPLER(sample_euler_cfgpp) else: - sampler = comfy.samplers.KSAMPLER(sample_euler_cfgpp_alt) + sampler = comfy.samplers.ksampler("euler_pp") return (sampler, ) NODE_CLASS_MAPPINGS = { From e99d97a9d943c3601ccdf411608bffb771db5bf1 Mon Sep 17 00:00:00 2001 From: Chenlei Hu Date: Wed, 26 Jun 2024 01:23:55 -0400 Subject: [PATCH 005/133] Remove duplicated Reset View button (#3865) * Remove duplicated Reset View button * Disable flaky test --- .github/workflows/test-browser.yml | 2 +- web/scripts/ui.js | 1 - 2 files changed, 1 insertion(+), 2 deletions(-) diff --git a/.github/workflows/test-browser.yml b/.github/workflows/test-browser.yml index 049b1cde2..323c96cf3 100644 --- a/.github/workflows/test-browser.yml +++ b/.github/workflows/test-browser.yml @@ -24,7 +24,7 @@ jobs: with: repository: "huchenlei/ComfyUI_frontend" path: "ComfyUI_frontend" - ref: "23a4ee83144d9bf22e7218b9c78c71f8544c8b27" + ref: "577aea9dfb680a14b3ae4fa626a85098c3207030" - uses: actions/setup-node@v3 with: node-version: lts/* diff --git a/web/scripts/ui.js b/web/scripts/ui.js index 87b4887eb..bb094d8b4 100644 --- a/web/scripts/ui.js +++ b/web/scripts/ui.js @@ -603,7 +603,6 @@ export class ComfyUI { onclick: () => app.refreshComboInNodes() }), $el("button", {id: "comfy-clipspace-button", textContent: "Clipspace", onclick: () => app.openClipspace()}), - $el("button", {id: "comfy-reset-view-button", textContent: "Reset View", onclick: () => app.resetView()}), $el("button", { id: "comfy-clear-button", textContent: "Clear", onclick: () => { if (!confirmClear.value || confirm("Clear workflow?")) { From edfce78c86c7615039dd8d74e89957a0eebbdc03 Mon Sep 17 00:00:00 2001 From: "Alex \"mcmonkey\" Goodwin" <4000772+mcmonkey4eva@users.noreply.github.com> Date: Tue, 25 Jun 2024 22:37:27 -0700 Subject: [PATCH 006/133] add issue templates for ComfyUI Issues Page (#3868) --- .github/ISSUE_TEMPLATE/bug-report.yml | 45 ++++++++++++++++++++++ .github/ISSUE_TEMPLATE/config.yml | 8 ++++ .github/ISSUE_TEMPLATE/feature-request.yml | 32 +++++++++++++++ .github/ISSUE_TEMPLATE/user-support.yml | 32 +++++++++++++++ 4 files changed, 117 insertions(+) create mode 100644 .github/ISSUE_TEMPLATE/bug-report.yml create mode 100644 .github/ISSUE_TEMPLATE/config.yml create mode 100644 .github/ISSUE_TEMPLATE/feature-request.yml create mode 100644 .github/ISSUE_TEMPLATE/user-support.yml diff --git a/.github/ISSUE_TEMPLATE/bug-report.yml b/.github/ISSUE_TEMPLATE/bug-report.yml new file mode 100644 index 000000000..87bef3681 --- /dev/null +++ b/.github/ISSUE_TEMPLATE/bug-report.yml @@ -0,0 +1,45 @@ +name: Bug Report +description: "Something is broken inside of ComfyUI. (Do not use this if you're just having issues and need help, or if the issue relates to a custom node)" +labels: [ "Potential Bug" ] +body: + - type: markdown + attributes: + value: | + Before submitting a **Bug Report**, please ensure the following: + + **1:** You are running the latest version of ComfyUI. + **2:** You have looked at the existing bug reports and made sure this isn't already reported. + **3:** This is an actual bug in ComfyUI, not just a support question and not caused by an custom node. A bug is when you can specify exact steps to replicate what went wrong and others will be able to repeat your steps and see the same issue happen. + + If unsure, ask on the [ComfyUI Matrix Space](https://app.element.io/#/room/%23comfyui_space%3Amatrix.org) or the [Comfy Org Discord](https://discord.gg/comfyorg) first. + - type: textarea + attributes: + label: Expected Behavior + description: "What you expected to happen." + validations: + required: true + - type: textarea + attributes: + label: Actual Behavior + description: "What actually happened. Please include a screenshot of the issue if possible." + validations: + required: true + - type: textarea + attributes: + label: Steps to Reproduce + description: "Describe how to reproduce the issue. Please be sure to attach a workflow JSON or PNG, ideally one that doesn't require custom nodes to test. If the bug open happens when certain custom nodes are used, most likely that custom node is what has the bug rather than ComfyUI, in which case it should be reported to the node's author." + validations: + required: true + - type: textarea + attributes: + label: Debug Logs + description: "Please copy the output from your terminal logs here." + render: powershell + validations: + required: true + - type: textarea + attributes: + label: Other + description: "Any other additional information you think might be helpful." + validations: + required: false diff --git a/.github/ISSUE_TEMPLATE/config.yml b/.github/ISSUE_TEMPLATE/config.yml new file mode 100644 index 000000000..2c519ede5 --- /dev/null +++ b/.github/ISSUE_TEMPLATE/config.yml @@ -0,0 +1,8 @@ +blank_issues_enabled: true +contact_links: + - name: ComfyUI Matrix Space + url: https://app.element.io/#/room/%23comfyui_space%3Amatrix.org + about: The ComfyUI Matrix Space is available for support and general discussion related to ComfyUI (Matrix is like Discord but open source). + - name: Comfy Org Discord + url: https://discord.gg/comfyorg + about: The Comfy Org Discord is available for support and general discussion related to ComfyUI. diff --git a/.github/ISSUE_TEMPLATE/feature-request.yml b/.github/ISSUE_TEMPLATE/feature-request.yml new file mode 100644 index 000000000..419721b63 --- /dev/null +++ b/.github/ISSUE_TEMPLATE/feature-request.yml @@ -0,0 +1,32 @@ +name: Feature Request +description: "You have an idea for something new you would like to see added to ComfyUI's core." +labels: [ "Feature" ] +body: + - type: markdown + attributes: + value: | + Before submitting a **Feature Request**, please ensure the following: + + **1:** You are running the latest version of ComfyUI. + **2:** You have looked to make sure there is not already a feature that does what you need, and there is not already a Feature Request listed for the same idea. + **3:** This is something that makes sense to add to ComfyUI Core, and wouldn't make more sense as a custom node. + + If unsure, ask on the [ComfyUI Matrix Space](https://app.element.io/#/room/%23comfyui_space%3Amatrix.org) or the [Comfy Org Discord](https://discord.gg/comfyorg) first. + - type: textarea + attributes: + label: Feature Idea + description: "Describe the feature you want to see." + validations: + required: true + - type: textarea + attributes: + label: Existing Solutions + description: "Please search through available custom nodes / extensions to see if there are existing custom solutions for this. If so, please link the options you found here as a reference." + validations: + required: false + - type: textarea + attributes: + label: Other + description: "Any other additional information you think might be helpful." + validations: + required: false diff --git a/.github/ISSUE_TEMPLATE/user-support.yml b/.github/ISSUE_TEMPLATE/user-support.yml new file mode 100644 index 000000000..df28804c6 --- /dev/null +++ b/.github/ISSUE_TEMPLATE/user-support.yml @@ -0,0 +1,32 @@ +name: User Support +description: "Use this if you need help with something, or you're experiencing an issue." +labels: [ "User Support" ] +body: + - type: markdown + attributes: + value: | + Before submitting a **User Report** issue, please ensure the following: + + **1:** You are running the latest version of ComfyUI. + **2:** You have made an effort to find public answers to your question before asking here. In other words, you googled it first, and scrolled through recent help topics. + + If unsure, ask on the [ComfyUI Matrix Space](https://app.element.io/#/room/%23comfyui_space%3Amatrix.org) or the [Comfy Org Discord](https://discord.gg/comfyorg) first. + - type: textarea + attributes: + label: Your question + description: "Post your question here. Please be as detailed as possible." + validations: + required: true + - type: textarea + attributes: + label: Logs + description: "If your question relates to an issue you're experiencing, please go to `Server` -> `Logs` -> potentially set `View Type` to `Debug` as well, then copypaste all the text into here." + render: powershell + validations: + required: false + - type: textarea + attributes: + label: Other + description: "Any other additional information you think might be helpful." + validations: + required: false From e3579f33600fea742611cc62503b446833d45735 Mon Sep 17 00:00:00 2001 From: pythongosssss <125205205+pythongosssss@users.noreply.github.com> Date: Wed, 26 Jun 2024 14:08:48 +0100 Subject: [PATCH 007/133] Fix merge issue breaking api json loading (#3876) --- web/scripts/app.js | 1 - 1 file changed, 1 deletion(-) diff --git a/web/scripts/app.js b/web/scripts/app.js index 725538563..a354ff805 100644 --- a/web/scripts/app.js +++ b/web/scripts/app.js @@ -2321,7 +2321,6 @@ export class ComfyApp { node.id = isNaN(+id) ? id : +id; node.title = data._meta?.title ?? node.title app.graph.add(node); - graph.add(node); } this.changeWorkflow(() => { From f12fa1d8d7b42888b6491aa6aa4956aefca3aba5 Mon Sep 17 00:00:00 2001 From: Chenlei Hu Date: Wed, 26 Jun 2024 09:09:21 -0400 Subject: [PATCH 008/133] Enable browser tests on push (#3878) --- .github/workflows/test-browser.yml | 2 ++ 1 file changed, 2 insertions(+) diff --git a/.github/workflows/test-browser.yml b/.github/workflows/test-browser.yml index 323c96cf3..987a72ae3 100644 --- a/.github/workflows/test-browser.yml +++ b/.github/workflows/test-browser.yml @@ -7,6 +7,8 @@ name: Playwright Browser Tests CI on: + push: + branches: [ main, master ] pull_request: branches: [ main, master ] From a3e83f695d6588bc06fdd40e039cd1e5b5e169dd Mon Sep 17 00:00:00 2001 From: Chenlei Hu Date: Wed, 26 Jun 2024 19:58:56 -0400 Subject: [PATCH 009/133] Update test ref (#3882) * Update ref * Disable some tests --- .github/workflows/test-browser.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/test-browser.yml b/.github/workflows/test-browser.yml index 987a72ae3..65483b00f 100644 --- a/.github/workflows/test-browser.yml +++ b/.github/workflows/test-browser.yml @@ -26,7 +26,7 @@ jobs: with: repository: "huchenlei/ComfyUI_frontend" path: "ComfyUI_frontend" - ref: "577aea9dfb680a14b3ae4fa626a85098c3207030" + ref: "fcc54d803e5b6a9b08a462a1d94899318c96dcbb" - uses: actions/setup-node@v3 with: node-version: lts/* From bc5a0f10db34a5c942fa3c531864da9665faaaa5 Mon Sep 17 00:00:00 2001 From: Chenlei Hu Date: Wed, 26 Jun 2024 19:59:09 -0400 Subject: [PATCH 010/133] Ignore *.log (#3880) --- .gitignore | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/.gitignore b/.gitignore index 9f0389241..9473f43ab 100644 --- a/.gitignore +++ b/.gitignore @@ -15,4 +15,5 @@ venv/ !/web/extensions/logging.js.example !/web/extensions/core/ /tests-ui/data/object_info.json -/user/ \ No newline at end of file +/user/ +*.log \ No newline at end of file From 175fe02522751c9f5e9a8309b3aaa5d07a542296 Mon Sep 17 00:00:00 2001 From: Chenlei Hu Date: Wed, 26 Jun 2024 19:59:19 -0400 Subject: [PATCH 011/133] Ignore .vscode/ (#3879) --- .gitignore | 1 + 1 file changed, 1 insertion(+) diff --git a/.gitignore b/.gitignore index 9473f43ab..a9beebe73 100644 --- a/.gitignore +++ b/.gitignore @@ -9,6 +9,7 @@ __pycache__/ !custom_nodes/example_node.py.example extra_model_paths.yaml /.vs +.vscode/ .idea/ venv/ /web/extensions/* From 44947e7ad489eaadb38007ca7aabd71aef7fa10e Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Wed, 26 Jun 2024 22:40:05 -0400 Subject: [PATCH 012/133] Add DEIS order 3 sampler. Order 4 seems to give bad results. --- comfy/k_diffusion/deis.py | 122 ++++++++++++++++++++++++++++++++++ comfy/k_diffusion/sampling.py | 50 ++++++++++++++ comfy/samplers.py | 2 +- 3 files changed, 173 insertions(+), 1 deletion(-) create mode 100644 comfy/k_diffusion/deis.py diff --git a/comfy/k_diffusion/deis.py b/comfy/k_diffusion/deis.py new file mode 100644 index 000000000..0be2036c3 --- /dev/null +++ b/comfy/k_diffusion/deis.py @@ -0,0 +1,122 @@ +#Taken from: https://github.com/zju-pi/diff-sampler/blob/main/gits-main/solver_utils.py +#under Apache 2 license +import torch +import numpy as np + +# A pytorch reimplementation of DEIS (https://github.com/qsh-zh/deis). +############################# +### Utils for DEIS solver ### +############################# +#---------------------------------------------------------------------------- +# Transfer from the input time (sigma) used in EDM to that (t) used in DEIS. + +def edm2t(edm_steps, epsilon_s=1e-3, sigma_min=0.002, sigma_max=80): + vp_sigma = lambda beta_d, beta_min: lambda t: (np.e ** (0.5 * beta_d * (t ** 2) + beta_min * t) - 1) ** 0.5 + vp_sigma_inv = lambda beta_d, beta_min: lambda sigma: ((beta_min ** 2 + 2 * beta_d * (sigma ** 2 + 1).log()).sqrt() - beta_min) / beta_d + vp_beta_d = 2 * (np.log(torch.tensor(sigma_min).cpu() ** 2 + 1) / epsilon_s - np.log(torch.tensor(sigma_max).cpu() ** 2 + 1)) / (epsilon_s - 1) + vp_beta_min = np.log(torch.tensor(sigma_max).cpu() ** 2 + 1) - 0.5 * vp_beta_d + t_steps = vp_sigma_inv(vp_beta_d.clone().detach().cpu(), vp_beta_min.clone().detach().cpu())(edm_steps.clone().detach().cpu()) + return t_steps, vp_beta_min, vp_beta_d + vp_beta_min + +#---------------------------------------------------------------------------- + +def cal_poly(prev_t, j, taus): + poly = 1 + for k in range(prev_t.shape[0]): + if k == j: + continue + poly *= (taus - prev_t[k]) / (prev_t[j] - prev_t[k]) + return poly + +#---------------------------------------------------------------------------- +# Transfer from t to alpha_t. + +def t2alpha_fn(beta_0, beta_1, t): + return torch.exp(-0.5 * t ** 2 * (beta_1 - beta_0) - t * beta_0) + +#---------------------------------------------------------------------------- + +def cal_intergrand(beta_0, beta_1, taus): + with torch.inference_mode(mode=False): + taus = taus.clone() + beta_0 = beta_0.clone() + beta_1 = beta_1.clone() + with torch.enable_grad(): + taus.requires_grad_(True) + alpha = t2alpha_fn(beta_0, beta_1, taus) + log_alpha = alpha.log() + log_alpha.sum().backward() + d_log_alpha_dtau = taus.grad + integrand = -0.5 * d_log_alpha_dtau / torch.sqrt(alpha * (1 - alpha)) + return integrand + +#---------------------------------------------------------------------------- + +def get_deis_coeff_list(t_steps, max_order, N=10000, deis_mode='tab'): + """ + Get the coefficient list for DEIS sampling. + + Args: + t_steps: A pytorch tensor. The time steps for sampling. + max_order: A `int`. Maximum order of the solver. 1 <= max_order <= 4 + N: A `int`. Use how many points to perform the numerical integration when deis_mode=='tab'. + deis_mode: A `str`. Select between 'tab' and 'rhoab'. Type of DEIS. + Returns: + A pytorch tensor. A batch of generated samples or sampling trajectories if return_inters=True. + """ + if deis_mode == 'tab': + t_steps, beta_0, beta_1 = edm2t(t_steps) + C = [] + for i, (t_cur, t_next) in enumerate(zip(t_steps[:-1], t_steps[1:])): + order = min(i+1, max_order) + if order == 1: + C.append([]) + else: + taus = torch.linspace(t_cur, t_next, N) # split the interval for integral appximation + dtau = (t_next - t_cur) / N + prev_t = t_steps[[i - k for k in range(order)]] + coeff_temp = [] + integrand = cal_intergrand(beta_0, beta_1, taus) + for j in range(order): + poly = cal_poly(prev_t, j, taus) + coeff_temp.append(torch.sum(integrand * poly) * dtau) + C.append(coeff_temp) + + elif deis_mode == 'rhoab': + # Analytical solution, second order + def get_def_intergral_2(a, b, start, end, c): + coeff = (end**3 - start**3) / 3 - (end**2 - start**2) * (a + b) / 2 + (end - start) * a * b + return coeff / ((c - a) * (c - b)) + + # Analytical solution, third order + def get_def_intergral_3(a, b, c, start, end, d): + coeff = (end**4 - start**4) / 4 - (end**3 - start**3) * (a + b + c) / 3 \ + + (end**2 - start**2) * (a*b + a*c + b*c) / 2 - (end - start) * a * b * c + return coeff / ((d - a) * (d - b) * (d - c)) + + C = [] + for i, (t_cur, t_next) in enumerate(zip(t_steps[:-1], t_steps[1:])): + order = min(i, max_order) + if order == 0: + C.append([]) + else: + prev_t = t_steps[[i - k for k in range(order+1)]] + if order == 1: + coeff_cur = ((t_next - prev_t[1])**2 - (t_cur - prev_t[1])**2) / (2 * (t_cur - prev_t[1])) + coeff_prev1 = (t_next - t_cur)**2 / (2 * (prev_t[1] - t_cur)) + coeff_temp = [coeff_cur, coeff_prev1] + elif order == 2: + coeff_cur = get_def_intergral_2(prev_t[1], prev_t[2], t_cur, t_next, t_cur) + coeff_prev1 = get_def_intergral_2(t_cur, prev_t[2], t_cur, t_next, prev_t[1]) + coeff_prev2 = get_def_intergral_2(t_cur, prev_t[1], t_cur, t_next, prev_t[2]) + coeff_temp = [coeff_cur, coeff_prev1, coeff_prev2] + elif order == 3: + coeff_cur = get_def_intergral_3(prev_t[1], prev_t[2], prev_t[3], t_cur, t_next, t_cur) + coeff_prev1 = get_def_intergral_3(t_cur, prev_t[2], prev_t[3], t_cur, t_next, prev_t[1]) + coeff_prev2 = get_def_intergral_3(t_cur, prev_t[1], prev_t[3], t_cur, t_next, prev_t[2]) + coeff_prev3 = get_def_intergral_3(t_cur, prev_t[1], prev_t[2], t_cur, t_next, prev_t[3]) + coeff_temp = [coeff_cur, coeff_prev1, coeff_prev2, coeff_prev3] + C.append(coeff_temp) + print(C) + return C + diff --git a/comfy/k_diffusion/sampling.py b/comfy/k_diffusion/sampling.py index 9b58cb1dc..f8091bb3f 100644 --- a/comfy/k_diffusion/sampling.py +++ b/comfy/k_diffusion/sampling.py @@ -7,6 +7,7 @@ import torchsde from tqdm.auto import trange, tqdm from . import utils +from . import deis import comfy.model_patcher def append_zero(x): @@ -946,6 +947,55 @@ def sample_ipndm_v(model, x, sigmas, extra_args=None, callback=None, disable=Non return x_next +#From https://github.com/zju-pi/diff-sampler/blob/main/diff-solvers-main/solvers.py +#under Apache 2 license +@torch.no_grad() +def sample_deis(model, x, sigmas, extra_args=None, callback=None, disable=None, max_order=3, deis_mode='tab'): + extra_args = {} if extra_args is None else extra_args + s_in = x.new_ones([x.shape[0]]) + + x_next = x + t_steps = sigmas + + coeff_list = deis.get_deis_coeff_list(t_steps, max_order, deis_mode=deis_mode) + + buffer_model = [] + for i in trange(len(sigmas) - 1, disable=disable): + t_cur = sigmas[i] + t_next = sigmas[i + 1] + + x_cur = x_next + + denoised = model(x_cur, t_cur * s_in, **extra_args) + if callback is not None: + callback({'x': x, 'i': i, 'sigma': sigmas[i], 'sigma_hat': sigmas[i], 'denoised': denoised}) + + d_cur = (x_cur - denoised) / t_cur + + order = min(max_order, i+1) + if t_next <= 0: + order = 1 + + if order == 1: # First Euler step. + x_next = x_cur + (t_next - t_cur) * d_cur + elif order == 2: # Use one history point. + coeff_cur, coeff_prev1 = coeff_list[i] + x_next = x_cur + coeff_cur * d_cur + coeff_prev1 * buffer_model[-1] + elif order == 3: # Use two history points. + coeff_cur, coeff_prev1, coeff_prev2 = coeff_list[i] + x_next = x_cur + coeff_cur * d_cur + coeff_prev1 * buffer_model[-1] + coeff_prev2 * buffer_model[-2] + elif order == 4: # Use three history points. + coeff_cur, coeff_prev1, coeff_prev2, coeff_prev3 = coeff_list[i] + x_next = x_cur + coeff_cur * d_cur + coeff_prev1 * buffer_model[-1] + coeff_prev2 * buffer_model[-2] + coeff_prev3 * buffer_model[-3] + + if len(buffer_model) == max_order - 1: + for k in range(max_order - 2): + buffer_model[k] = buffer_model[k+1] + buffer_model[-1] = d_cur.detach() + else: + buffer_model.append(d_cur.detach()) + + return x_next @torch.no_grad() def sample_euler_pp(model, x, sigmas, extra_args=None, callback=None, disable=None): diff --git a/comfy/samplers.py b/comfy/samplers.py index c3a80dde0..7f7114dbb 100644 --- a/comfy/samplers.py +++ b/comfy/samplers.py @@ -540,7 +540,7 @@ class Sampler: KSAMPLER_NAMES = ["euler", "euler_pp", "euler_ancestral", "euler_ancestral_pp", "heun", "heunpp2","dpm_2", "dpm_2_ancestral", "lms", "dpm_fast", "dpm_adaptive", "dpmpp_2s_ancestral", "dpmpp_sde", "dpmpp_sde_gpu", "dpmpp_2m", "dpmpp_2m_sde", "dpmpp_2m_sde_gpu", "dpmpp_3m_sde", "dpmpp_3m_sde_gpu", "ddpm", "lcm", - "ipndm", "ipndm_v"] + "ipndm", "ipndm_v", "deis"] class KSAMPLER(Sampler): def __init__(self, sampler_function, extra_options={}, inpaint_options={}): From 3b423afccab877b57fc24141690426ca1660e4bb Mon Sep 17 00:00:00 2001 From: Chenlei Hu Date: Thu, 27 Jun 2024 00:22:55 -0400 Subject: [PATCH 013/133] Add audio widget (#3863) * Add audio widget * Fix audio bugs * Add CSS * Populate audio widget when load history --- comfy_extras/nodes_audio.py | 11 +- web/extensions/core/uploadAudio.js | 176 +++++++++++++++++++++++++++++ web/scripts/app.js | 11 +- web/style.css | 4 + 4 files changed, 199 insertions(+), 3 deletions(-) create mode 100644 web/extensions/core/uploadAudio.js diff --git a/comfy_extras/nodes_audio.py b/comfy_extras/nodes_audio.py index 57d0a20ab..8efa7c0a8 100644 --- a/comfy_extras/nodes_audio.py +++ b/comfy_extras/nodes_audio.py @@ -93,11 +93,18 @@ class SaveAudio: return { "ui": { "audio": results } } class LoadAudio: + SUPPORTED_FORMATS = ('.wav', '.mp3', '.ogg', '.flac', '.aiff', '.aif') + @classmethod def INPUT_TYPES(s): input_dir = folder_paths.get_input_directory() - files = [f for f in os.listdir(input_dir) if os.path.isfile(os.path.join(input_dir, f))] - return {"required": {"audio": [sorted(files), ]}, } + files = [ + f for f in os.listdir(input_dir) + if (os.path.isfile(os.path.join(input_dir, f)) + and f.endswith(LoadAudio.SUPPORTED_FORMATS) + ) + ] + return {"required": {"audio": (sorted(files), {"audio_upload": True})}} CATEGORY = "_for_testing/audio" diff --git a/web/extensions/core/uploadAudio.js b/web/extensions/core/uploadAudio.js new file mode 100644 index 000000000..d3dfef4a7 --- /dev/null +++ b/web/extensions/core/uploadAudio.js @@ -0,0 +1,176 @@ +import { app } from "../../scripts/app.js" +import { api } from "../../scripts/api.js" + +function splitFilePath(path) { + const folder_separator = path.lastIndexOf("/") + if (folder_separator === -1) { + return ["", path] + } + return [ + path.substring(0, folder_separator), + path.substring(folder_separator + 1) + ] +} + +function getResourceURL(subfolder, filename, type = "input") { + const params = [ + "filename=" + encodeURIComponent(filename), + "type=" + type, + "subfolder=" + subfolder, + app.getPreviewFormatParam().substring(1), + app.getRandParam().substring(1) + ].join("&") + + return `/view?${params}` +} + +async function uploadFile( + audioWidget, + audioUIWidget, + file, + updateNode, + pasted = false +) { + try { + // Wrap file in formdata so it includes filename + const body = new FormData() + body.append("image", file) + if (pasted) body.append("subfolder", "pasted") + const resp = await api.fetchApi("/upload/image", { + method: "POST", + body + }) + + if (resp.status === 200) { + const data = await resp.json() + // Add the file to the dropdown list and update the widget value + let path = data.name + if (data.subfolder) path = data.subfolder + "/" + path + + if (!audioWidget.options.values.includes(path)) { + audioWidget.options.values.push(path) + } + + if (updateNode) { + audioUIWidget.element.src = api.apiURL( + getResourceURL(...splitFilePath(path)) + ) + audioWidget.value = path + } + } else { + alert(resp.status + " - " + resp.statusText) + } + } catch (error) { + alert(error) + } +} + +// AudioWidget MUST be registered first, as AUDIOUPLOAD depends on AUDIO_UI to be +// present. +app.registerExtension({ + name: "Comfy.AudioWidget", + async beforeRegisterNodeDef(nodeType, nodeData) { + if (["LoadAudio", "SaveAudio"].includes(nodeType.comfyClass)) { + nodeData.input.required.audioUI = ["AUDIO_UI"] + } + }, + getCustomWidgets() { + return { + AUDIO_UI(node, inputName) { + const audio = document.createElement("audio") + audio.controls = true + audio.classList.add("comfy-audio") + audio.setAttribute("name", "media") + + const audioUIWidget = node.addDOMWidget( + inputName, + /* name=*/ "audioUI", + audio + ) + // @ts-ignore + // TODO: Sort out the DOMWidget type. + audioUIWidget.serialize = false + + const isOutputNode = node.constructor.nodeData.output_node + if (isOutputNode) { + // Hide the audio widget when there is no audio initially. + audioUIWidget.element.classList.add("empty-audio-widget") + // Populate the audio widget UI on node execution. + const onExecuted = node.onExecuted + node.onExecuted = function(message) { + onExecuted?.apply(this, arguments) + const audios = message.audio + if (!audios) return + const audio = audios[0] + audioUIWidget.element.src = api.apiURL( + getResourceURL(audio.subfolder, audio.filename, "output") + ) + audioUIWidget.element.classList.remove("empty-audio-widget") + } + } + return { widget: audioUIWidget } + } + } + }, + onNodeOutputsUpdated(nodeOutputs) { + for (const [nodeId, output] of Object.entries(nodeOutputs)) { + const node = app.graph.getNodeById(Number.parseInt(nodeId)); + if ("audio" in output) { + const audioUIWidget = node.widgets.find((w) => w.name === "audioUI"); + const audio = output.audio[0]; + audioUIWidget.element.src = api.apiURL(getResourceURL(audio.subfolder, audio.filename, "output")); + audioUIWidget.element.classList.remove("empty-audio-widget"); + } + } + }, +}) + +app.registerExtension({ + name: "Comfy.UploadAudio", + async beforeRegisterNodeDef(nodeType, nodeData) { + if (nodeData?.input?.required?.audio?.[1]?.audio_upload === true) { + nodeData.input.required.upload = ["AUDIOUPLOAD"] + } + }, + getCustomWidgets() { + return { + AUDIOUPLOAD(node, inputName) { + // The widget that allows user to select file. + const audioWidget = node.widgets.find(w => w.name === "audio") + const audioUIWidget = node.widgets.find(w => w.name === "audioUI") + + const onAudioWidgetUpdate = () => { + audioUIWidget.element.src = api.apiURL( + getResourceURL(...splitFilePath(audioWidget.value)) + ) + } + // Initially load default audio file to audioUIWidget. + onAudioWidgetUpdate() + audioWidget.callback = onAudioWidgetUpdate + + const fileInput = document.createElement("input") + fileInput.type = "file" + fileInput.accept = "audio/*" + fileInput.style.display = "none" + fileInput.onchange = () => { + if (fileInput.files.length) { + uploadFile(audioWidget, audioUIWidget, fileInput.files[0], true) + } + } + // The widget to pop up the upload dialog. + const uploadWidget = node.addWidget( + "button", + inputName, + /* value=*/ "", + () => { + fileInput.click() + } + ) + uploadWidget.label = "choose file to upload" + uploadWidget.serialize = false + + return { widget: uploadWidget } + } + } + } +}) diff --git a/web/scripts/app.js b/web/scripts/app.js index a354ff805..5fc9b9c6c 100644 --- a/web/scripts/app.js +++ b/web/scripts/app.js @@ -71,7 +71,7 @@ export class ComfyApp { * Stores the execution output data for each node * @type {Record} */ - this.nodeOutputs = {}; + this._nodeOutputs = {}; /** * Stores the preview image data for each node @@ -86,6 +86,15 @@ export class ComfyApp { this.shiftDown = false; } + get nodeOutputs() { + return this._nodeOutputs; + } + + set nodeOutputs(value) { + this._nodeOutputs = value; + this.#invokeExtensions("onNodeOutputsUpdated", value); + } + getPreviewFormatParam() { let preview_format = this.ui.settings.getSettingValue("Comfy.PreviewFormat"); if(preview_format) diff --git a/web/style.css b/web/style.css index 8091a489f..e983b652a 100644 --- a/web/style.css +++ b/web/style.css @@ -632,3 +632,7 @@ dialog::backdrop { border-top: none; } } + +audio.comfy-audio.empty-audio-widget { + display: none; +} From 4650e7d6e9e846160906b94d575705151d59fdd1 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Thu, 27 Jun 2024 01:28:59 -0400 Subject: [PATCH 014/133] Save and load workflow from the flac files output by SaveAudio. --- comfy_extras/nodes_audio.py | 79 ++++++++++++++++++++++++++++++++++++- web/scripts/app.js | 15 ++++++- web/scripts/pnginfo.js | 72 +++++++++++++++++++++++++++++++++ web/scripts/ui.js | 2 +- 4 files changed, 164 insertions(+), 4 deletions(-) diff --git a/comfy_extras/nodes_audio.py b/comfy_extras/nodes_audio.py index 8efa7c0a8..34bcfa96d 100644 --- a/comfy_extras/nodes_audio.py +++ b/comfy_extras/nodes_audio.py @@ -3,6 +3,10 @@ import torch import comfy.model_management import folder_paths import os +import io +import json +import struct +from comfy.cli_args import args class EmptyLatentAudio: def __init__(self): @@ -53,6 +57,61 @@ class VAEDecodeAudio: audio = vae.decode(samples["samples"]).movedim(-1, 1) return ({"waveform": audio, "sample_rate": 44100}, ) + +def create_vorbis_comment_block(comment_dict, last_block): + vendor_string = b'ComfyUI' + vendor_length = len(vendor_string) + + comments = [] + for key, value in comment_dict.items(): + comment = f"{key}={value}".encode('utf-8') + comments.append(struct.pack('I', len(comment_data))[1:] + comment_data + + return comment_block + +def insert_or_replace_vorbis_comment(flac_io, comment_dict): + if len(comment_dict) == 0: + return flac_io + + flac_io.seek(4) + + blocks = [] + last_block = False + + while not last_block: + header = flac_io.read(4) + last_block = (header[0] & 0x80) != 0 + block_type = header[0] & 0x7F + block_length = struct.unpack('>I', b'\x00' + header[1:])[0] + block_data = flac_io.read(block_length) + + if block_type == 4 or block_type == 1: + pass + else: + header = bytes([(header[0] & (~0x80))]) + header[1:] + blocks.append(header + block_data) + + blocks.append(create_vorbis_comment_block(comment_dict, last_block=True)) + + new_flac_io = io.BytesIO() + new_flac_io.write(b'fLaC') + for block in blocks: + new_flac_io.write(block) + + new_flac_io.write(flac_io.read()) + return new_flac_io + + class SaveAudio: def __init__(self): self.output_dir = folder_paths.get_output_directory() @@ -78,11 +137,27 @@ class SaveAudio: filename_prefix += self.prefix_append full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, self.output_dir) results = list() + + metadata = {} + if not args.disable_metadata: + if prompt is not None: + metadata["prompt"] = json.dumps(prompt) + if extra_pnginfo is not None: + for x in extra_pnginfo: + metadata[x] = json.dumps(extra_pnginfo[x]) + for (batch_number, waveform) in enumerate(audio["waveform"]): - #TODO: metadata filename_with_batch_num = filename.replace("%batch_num%", str(batch_number)) file = f"{filename_with_batch_num}_{counter:05}_.flac" - torchaudio.save(os.path.join(full_output_folder, file), waveform, audio["sample_rate"], format="FLAC") + + buff = io.BytesIO() + torchaudio.save(buff, waveform, audio["sample_rate"], format="FLAC") + + buff = insert_or_replace_vorbis_comment(buff, metadata) + + with open(os.path.join(full_output_folder, file), 'wb') as f: + f.write(buff.getbuffer()) + results.append({ "filename": file, "subfolder": subfolder, diff --git a/web/scripts/app.js b/web/scripts/app.js index 5fc9b9c6c..43df61065 100644 --- a/web/scripts/app.js +++ b/web/scripts/app.js @@ -3,7 +3,7 @@ import { ComfyWidgets, initWidgets } from "./widgets.js"; import { ComfyUI, $el } from "./ui.js"; import { api } from "./api.js"; import { defaultGraph } from "./defaultGraph.js"; -import { getPngMetadata, getWebpMetadata, importA1111, getLatentMetadata } from "./pnginfo.js"; +import { getPngMetadata, getWebpMetadata, getFlacMetadata, importA1111, getLatentMetadata } from "./pnginfo.js"; import { addDomClippingSetting } from "./domWidget.js"; import { createImageHost, calculateImageGrid } from "./ui/imagePreview.js"; import { ComfyAppMenu } from "./ui/menu/index.js"; @@ -2277,6 +2277,19 @@ export class ComfyApp { const workflow = pngInfo?.workflow || pngInfo?.Workflow; const prompt = pngInfo?.prompt || pngInfo?.Prompt; + if (workflow) { + this.loadGraphData(JSON.parse(workflow), true, true, fileName); + } else if (prompt) { + this.loadApiJson(JSON.parse(prompt), fileName); + } else { + this.showErrorOnFileLoad(file); + } + } else if (file.type === "audio/flac") { + const pngInfo = await getFlacMetadata(file); + // Support loading workflows from that webp custom node. + const workflow = pngInfo?.workflow; + const prompt = pngInfo?.prompt; + if (workflow) { this.loadGraphData(JSON.parse(workflow), true, true, fileName); } else if (prompt) { diff --git a/web/scripts/pnginfo.js b/web/scripts/pnginfo.js index 7132fb60f..2c03cf74a 100644 --- a/web/scripts/pnginfo.js +++ b/web/scripts/pnginfo.js @@ -163,6 +163,78 @@ export function getLatentMetadata(file) { }); } + +function getString(dataView, offset, length) { + let string = ''; + for (let i = 0; i < length; i++) { + string += String.fromCharCode(dataView.getUint8(offset + i)); + } + return string; +} + +// Function to parse the Vorbis Comment block +function parseVorbisComment(dataView) { + let offset = 0; + const vendorLength = dataView.getUint32(offset, true); + offset += 4; + const vendorString = getString(dataView, offset, vendorLength); + offset += vendorLength; + + const userCommentListLength = dataView.getUint32(offset, true); + offset += 4; + const comments = {}; + for (let i = 0; i < userCommentListLength; i++) { + const commentLength = dataView.getUint32(offset, true); + offset += 4; + const comment = getString(dataView, offset, commentLength); + offset += commentLength; + + const [key, value] = comment.split('='); + + comments[key] = value; + } + + return comments; +} + +// Function to read a FLAC file and parse Vorbis comments +export function getFlacMetadata(file) { + return new Promise((r) => { + const reader = new FileReader(); + reader.onload = function(event) { + const arrayBuffer = event.target.result; + const dataView = new DataView(arrayBuffer); + + // Verify the FLAC signature + const signature = String.fromCharCode(...new Uint8Array(arrayBuffer, 0, 4)); + if (signature !== 'fLaC') { + console.error('Not a valid FLAC file'); + return; + } + + // Parse metadata blocks + let offset = 4; + let vorbisComment = null; + while (offset < dataView.byteLength) { + const isLastBlock = dataView.getUint8(offset) & 0x80; + const blockType = dataView.getUint8(offset) & 0x7F; + const blockSize = dataView.getUint32(offset, false) & 0xFFFFFF; + offset += 4; + + if (blockType === 4) { // Vorbis Comment block type + vorbisComment = parseVorbisComment(new DataView(arrayBuffer, offset, blockSize)); + } + + offset += blockSize; + if (isLastBlock) break; + } + + r(vorbisComment); + }; + reader.readAsArrayBuffer(file); + }); +} + export async function importA1111(graph, parameters) { const p = parameters.lastIndexOf("\nSteps:"); if (p > -1) { diff --git a/web/scripts/ui.js b/web/scripts/ui.js index bb094d8b4..2c47412c9 100644 --- a/web/scripts/ui.js +++ b/web/scripts/ui.js @@ -373,7 +373,7 @@ export class ComfyUI { const fileInput = $el("input", { id: "comfy-file-input", type: "file", - accept: ".json,image/png,.latent,.safetensors,image/webp", + accept: ".json,image/png,.latent,.safetensors,image/webp,audio/flac", style: {display: "none"}, parent: document.body, onchange: () => { From 4f9d2b057c97be22aa46b91ed8954a3cee424fb4 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Thu, 27 Jun 2024 02:54:15 -0400 Subject: [PATCH 015/133] Remove print. --- comfy/k_diffusion/deis.py | 1 - 1 file changed, 1 deletion(-) diff --git a/comfy/k_diffusion/deis.py b/comfy/k_diffusion/deis.py index 0be2036c3..607410656 100644 --- a/comfy/k_diffusion/deis.py +++ b/comfy/k_diffusion/deis.py @@ -117,6 +117,5 @@ def get_deis_coeff_list(t_steps, max_order, N=10000, deis_mode='tab'): coeff_prev3 = get_def_intergral_3(t_cur, prev_t[1], prev_t[2], t_cur, t_next, prev_t[3]) coeff_temp = [coeff_cur, coeff_prev1, coeff_prev2, coeff_prev3] C.append(coeff_temp) - print(C) return C From 5ff3d4eb3a91d1e66d35a919dd38c02b4652e96a Mon Sep 17 00:00:00 2001 From: Chenlei Hu Date: Thu, 27 Jun 2024 09:13:52 -0400 Subject: [PATCH 016/133] Fix audio upload when no audio in input dir (#3891) --- web/extensions/core/uploadAudio.js | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/web/extensions/core/uploadAudio.js b/web/extensions/core/uploadAudio.js index d3dfef4a7..12a2a196b 100644 --- a/web/extensions/core/uploadAudio.js +++ b/web/extensions/core/uploadAudio.js @@ -145,7 +145,9 @@ app.registerExtension({ ) } // Initially load default audio file to audioUIWidget. - onAudioWidgetUpdate() + if (audioWidget.value) { + onAudioWidgetUpdate() + } audioWidget.callback = onAudioWidgetUpdate const fileInput = document.createElement("input") From 8ceb5a02a3182e6551690d9e56934bdca1cebcca Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Thu, 27 Jun 2024 11:06:52 -0400 Subject: [PATCH 017/133] Support saving stable audio checkpoint that can be loaded back. --- comfy/model_base.py | 9 +++++++++ comfy/sd.py | 2 +- comfy/supported_models.py | 5 ++++- 3 files changed, 14 insertions(+), 2 deletions(-) diff --git a/comfy/model_base.py b/comfy/model_base.py index f45b375de..80f6667ec 100644 --- a/comfy/model_base.py +++ b/comfy/model_base.py @@ -627,3 +627,12 @@ class StableAudio1(BaseModel): cross_attn = torch.cat([cross_attn.to(device), seconds_start_embed.repeat((cross_attn.shape[0], 1, 1)), seconds_total_embed.repeat((cross_attn.shape[0], 1, 1))], dim=1) out['c_crossattn'] = comfy.conds.CONDRegular(cross_attn) return out + + def state_dict_for_saving(self, clip_state_dict=None, vae_state_dict=None, clip_vision_state_dict=None): + sd = super().state_dict_for_saving(clip_state_dict=clip_state_dict, vae_state_dict=vae_state_dict, clip_vision_state_dict=clip_vision_state_dict) + d = {"conditioner.conditioners.seconds_start.": self.seconds_start_embedder.state_dict(), "conditioner.conditioners.seconds_total.": self.seconds_total_embedder.state_dict()} + for k in d: + s = d[k] + for l in s: + sd["{}{}".format(k, l)] = s[l] + return sd diff --git a/comfy/sd.py b/comfy/sd.py index ea6e9b663..dda0887ba 100644 --- a/comfy/sd.py +++ b/comfy/sd.py @@ -236,7 +236,7 @@ class VAE: self.first_stage_model = AutoencodingEngine(regularizer_config={'target': "comfy.ldm.models.autoencoder.DiagonalGaussianRegularizer"}, encoder_config={'target': "comfy.ldm.modules.diffusionmodules.model.Encoder", 'params': ddconfig}, decoder_config={'target': "comfy.ldm.modules.diffusionmodules.model.Decoder", 'params': ddconfig}) - elif "decoder.layers.0.weight_v" in sd: + elif "decoder.layers.1.layers.0.beta" in sd: self.first_stage_model = AudioOobleckVAE() self.memory_used_encode = lambda shape, dtype: (1000 * shape[2]) * model_management.dtype_size(dtype) self.memory_used_decode = lambda shape, dtype: (1000 * shape[2] * 2048) * model_management.dtype_size(dtype) diff --git a/comfy/supported_models.py b/comfy/supported_models.py index 761498dbc..21fdb7ec7 100644 --- a/comfy/supported_models.py +++ b/comfy/supported_models.py @@ -543,13 +543,16 @@ class StableAudio(supported_models_base.BASE): seconds_total_sd = utils.state_dict_prefix_replace(state_dict, {"conditioner.conditioners.seconds_total.": ""}, filter_keys=True) return model_base.StableAudio1(self, seconds_start_embedder_weights=seconds_start_sd, seconds_total_embedder_weights=seconds_total_sd, device=device) - def process_unet_state_dict(self, state_dict): for k in list(state_dict.keys()): if k.endswith(".cross_attend_norm.beta") or k.endswith(".ff_norm.beta") or k.endswith(".pre_norm.beta"): #These weights are all zero state_dict.pop(k) return state_dict + def process_unet_state_dict_for_saving(self, state_dict): + replace_prefix = {"": "model.model."} + return utils.state_dict_prefix_replace(state_dict, replace_prefix) + def clip_target(self, state_dict={}): return supported_models_base.ClipTarget(sa_t5.SAT5Tokenizer, sa_t5.SAT5Model) From 449bf52923896236ed645da2ff05aadbf2b0d536 Mon Sep 17 00:00:00 2001 From: Robin Huang Date: Thu, 27 Jun 2024 13:08:26 -0700 Subject: [PATCH 018/133] Add integration test for Linux with Nvidia GPU. #3884 (#3895) * Add linux integration test. * Fix directory path. * Add paths ignore. * Fix conda env directory path. --- .../conda-environments/linux-environment.yml | 28 +++++++++++ .github/workflows/linux-integration-test.yml | 50 +++++++++++++++++++ 2 files changed, 78 insertions(+) create mode 100644 .github/conda-environments/linux-environment.yml create mode 100644 .github/workflows/linux-integration-test.yml diff --git a/.github/conda-environments/linux-environment.yml b/.github/conda-environments/linux-environment.yml new file mode 100644 index 000000000..c9ebd6406 --- /dev/null +++ b/.github/conda-environments/linux-environment.yml @@ -0,0 +1,28 @@ +name: comfyui +channels: + - pytorch + - nvidia + - defaults +dependencies: + - python>=3.9 + - pip + - pytorch + - torchvision + - torchaudio + - pytorch-cuda=12.1 + - pip: + # comfyui requirements + - einops + - transformers>=4.25.1 + - safetensors>=0.4.2 + - aiohttp + - pyyaml + - Pillow + - scipy + - tqdm + - psutil + # comfy-action requirements + - requests + - google-cloud-storage + - comfy-cli + - charset-normalizer \ No newline at end of file diff --git a/.github/workflows/linux-integration-test.yml b/.github/workflows/linux-integration-test.yml new file mode 100644 index 000000000..eed84a77c --- /dev/null +++ b/.github/workflows/linux-integration-test.yml @@ -0,0 +1,50 @@ +name: (Linux) ComfyUI Integration Tests +on: + push: + branches: + - master + paths-ignore: + - 'app/**' + - 'input/**' + - 'output/**' + - 'model/**' + - 'notebook/**' + - 'script_example/**' + - 'tests/**' + - 'tests-ui/**' + - '.github/**' + - '.ci/**' + - 'web/**' + workflow_dispatch: + pull_request: + branches: + - master + paths-ignore: + - 'app/**' + - 'input/**' + - 'output/**' + - 'model/**' + - 'notebook/**' + - 'script_example/**' + - 'tests/**' + - 'tests-ui/**' + - '.github/**' + - '.ci/**' + - 'web/**' + +jobs: + test-workflows: + runs-on: [self-hosted, Linux, t4] + steps: + - name: Test ComfyUI Workflows + uses: comfy-org/comfy-action@main + with: + os: linux + cuda_version: 12.1 + models-json: '{"v1-5-pruned-emaonly.ckpt": {"url": "https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.ckpt", "directory": "checkpoints"}}' + workflow_filenames: "default.json" + gcs_bucket_name: 'comfy-ci-results' + google_credentials: ${{ secrets.GCS_SERVICE_ACCOUNT_JSON }} + output_prefix: 'ComfyUI' + conda_env_file: '.github/conda-environments/linux-environment.yml' + timeout: 50 From 97b409cd486b1a3b1114ae204802c81f3727d1a2 Mon Sep 17 00:00:00 2001 From: Robin Huang Date: Thu, 27 Jun 2024 13:10:16 -0700 Subject: [PATCH 019/133] Add macOs integration test for default workflow. (#3898) --- .../conda-environments/mac-environment.yml | 26 ++++++++++ .github/workflows/mac-integration-test.yml | 50 +++++++++++++++++++ 2 files changed, 76 insertions(+) create mode 100644 .github/conda-environments/mac-environment.yml create mode 100644 .github/workflows/mac-integration-test.yml diff --git a/.github/conda-environments/mac-environment.yml b/.github/conda-environments/mac-environment.yml new file mode 100644 index 000000000..33832b854 --- /dev/null +++ b/.github/conda-environments/mac-environment.yml @@ -0,0 +1,26 @@ +name: comfyui +channels: + - pytorch-nightly + - defaults +dependencies: + - python>=3.9 + - pytorch-nightly::pytorch + - torchvision + - torchaudio + - pip: + - pip + # comfyui requirements + - einops + - transformers>=4.25.1 + - safetensors>=0.4.2 + - aiohttp + - pyyaml + - Pillow + - scipy + - tqdm + - psutil + # comfy-action requirements + - requests + - google-cloud-storage + - comfy-cli + - charset-normalizer diff --git a/.github/workflows/mac-integration-test.yml b/.github/workflows/mac-integration-test.yml new file mode 100644 index 000000000..6a0482b1b --- /dev/null +++ b/.github/workflows/mac-integration-test.yml @@ -0,0 +1,50 @@ +name: (macOS) ComfyUI Integration Tests +on: + push: + branches: + - master + paths-ignore: + - 'app/**' + - 'input/**' + - 'output/**' + - 'model/**' + - 'notebook/**' + - 'script_example/**' + - 'tests/**' + - 'tests-ui/**' + - '.github/**' + - '.ci/**' + - 'web/**' + workflow_dispatch: + pull_request: + branches: + - master + paths-ignore: + - 'app/**' + - 'input/**' + - 'output/**' + - 'model/**' + - 'notebook/**' + - 'script_example/**' + - 'tests/**' + - 'tests-ui/**' + - '.github/**' + - '.ci/**' + - 'web/**' + +jobs: + test-workflows: + runs-on: [self-hosted, m2] + steps: + - name: Test ComfyUI Workflows + uses: comfy-org/comfy-action@main + with: + os: mac + models-json: '{"v1-5-pruned-emaonly.ckpt": {"url": "https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.ckpt", "directory": "checkpoints"}}' + workflow_filenames: "default.json" + gcs_bucket_name: 'comfy-ci-results' + google_credentials: ${{ secrets.GCS_SERVICE_ACCOUNT_JSON }} + output_prefix: 'ComfyUI' + conda_env_file: '.github/conda-environments/mac-environment.yml' + timeout: 50 + From 66aaa14001be9f7cf2b52f84c0dff588e36aabbf Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Tue, 25 Jun 2024 17:02:05 -0400 Subject: [PATCH 020/133] Controlnet refactor. --- comfy/cldm/cldm.py | 9 +++++---- comfy/controlnet.py | 35 ++++++++++----------------------- comfy/ldm/cascade/controlnet.py | 2 +- comfy/t2i_adapter/adapter.py | 10 ++++++++-- 4 files changed, 24 insertions(+), 32 deletions(-) diff --git a/comfy/cldm/cldm.py b/comfy/cldm/cldm.py index 28076dd92..f8a161594 100644 --- a/comfy/cldm/cldm.py +++ b/comfy/cldm/cldm.py @@ -289,7 +289,8 @@ class ControlNet(nn.Module): guided_hint = self.input_hint_block(hint, emb, context) - outs = [] + out_output = [] + out_middle = [] hs = [] if self.num_classes is not None: @@ -304,10 +305,10 @@ class ControlNet(nn.Module): guided_hint = None else: h = module(h, emb, context) - outs.append(zero_conv(h, emb, context)) + out_output.append(zero_conv(h, emb, context)) h = self.middle_block(h, emb, context) - outs.append(self.middle_block_out(h, emb, context)) + out_middle.append(self.middle_block_out(h, emb, context)) - return outs + return {"middle": out_middle, "output": out_output} diff --git a/comfy/controlnet.py b/comfy/controlnet.py index 8cf4a61a6..f50df6835 100644 --- a/comfy/controlnet.py +++ b/comfy/controlnet.py @@ -89,27 +89,12 @@ class ControlBase: return self.previous_controlnet.inference_memory_requirements(dtype) return 0 - def control_merge(self, control_input, control_output, control_prev, output_dtype): + def control_merge(self, control, control_prev, output_dtype): out = {'input':[], 'middle':[], 'output': []} - if control_input is not None: - for i in range(len(control_input)): - key = 'input' - x = control_input[i] - if x is not None: - x *= self.strength - if x.dtype != output_dtype: - x = x.to(output_dtype) - out[key].insert(0, x) - - if control_output is not None: + for key in control: + control_output = control[key] for i in range(len(control_output)): - if i == (len(control_output) - 1): - key = 'middle' - index = 0 - else: - key = 'output' - index = i x = control_output[i] if x is not None: if self.global_average_pooling: @@ -120,6 +105,7 @@ class ControlBase: x = x.to(output_dtype) out[key].append(x) + if control_prev is not None: for x in ['input', 'middle', 'output']: o = out[x] @@ -182,7 +168,7 @@ class ControlNet(ControlBase): x_noisy = self.model_sampling_current.calculate_input(t, x_noisy) control = self.control_model(x=x_noisy.to(dtype), hint=self.cond_hint, timesteps=timestep.float(), context=context.to(dtype), y=y) - return self.control_merge(None, control, control_prev, output_dtype) + return self.control_merge(control, control_prev, output_dtype) def copy(self): c = ControlNet(None, global_average_pooling=self.global_average_pooling, load_device=self.load_device, manual_cast_dtype=self.manual_cast_dtype) @@ -490,12 +476,11 @@ class T2IAdapter(ControlBase): self.control_input = self.t2i_model(self.cond_hint.to(x_noisy.dtype)) self.t2i_model.cpu() - control_input = list(map(lambda a: None if a is None else a.clone(), self.control_input)) - mid = None - if self.t2i_model.xl == True: - mid = control_input[-1:] - control_input = control_input[:-1] - return self.control_merge(control_input, mid, control_prev, x_noisy.dtype) + control_input = {} + for k in self.control_input: + control_input[k] = list(map(lambda a: None if a is None else a.clone(), self.control_input[k])) + + return self.control_merge(control_input, control_prev, x_noisy.dtype) def copy(self): c = T2IAdapter(self.t2i_model, self.channels_in, self.compression_ratio, self.upscale_algorithm) diff --git a/comfy/ldm/cascade/controlnet.py b/comfy/ldm/cascade/controlnet.py index 5dac59394..7a52c3c26 100644 --- a/comfy/ldm/cascade/controlnet.py +++ b/comfy/ldm/cascade/controlnet.py @@ -90,4 +90,4 @@ class ControlNet(nn.Module): proj_outputs = [None for _ in range(max(self.proj_blocks) + 1)] for i, idx in enumerate(self.proj_blocks): proj_outputs[idx] = self.projections[i](x) - return proj_outputs + return {"input": proj_outputs[::-1]} diff --git a/comfy/t2i_adapter/adapter.py b/comfy/t2i_adapter/adapter.py index e9a606b1c..10ea18e32 100644 --- a/comfy/t2i_adapter/adapter.py +++ b/comfy/t2i_adapter/adapter.py @@ -153,7 +153,13 @@ class Adapter(nn.Module): features.append(None) features.append(x) - return features + features = features[::-1] + + if self.xl: + return {"input": features[1:], "middle": features[:1]} + else: + return {"input": features} + class LayerNorm(nn.LayerNorm): @@ -290,4 +296,4 @@ class Adapter_light(nn.Module): features.append(None) features.append(x) - return features + return {"input": features[::-1]} From f8f7568d031a61f5d21ca0ed56ff56d7d83c9115 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Tue, 25 Jun 2024 23:40:44 -0400 Subject: [PATCH 021/133] Basic SD3 controlnet implementation. Still missing the node to properly use it. --- comfy/cldm/mmdit.py | 91 +++++++++++++++++++++ comfy/controlnet.py | 45 +++++++++- comfy/ldm/modules/diffusionmodules/mmdit.py | 30 +++++-- comfy/model_detection.py | 11 ++- comfy/utils.py | 3 +- 5 files changed, 165 insertions(+), 15 deletions(-) create mode 100644 comfy/cldm/mmdit.py diff --git a/comfy/cldm/mmdit.py b/comfy/cldm/mmdit.py new file mode 100644 index 000000000..6e72474ce --- /dev/null +++ b/comfy/cldm/mmdit.py @@ -0,0 +1,91 @@ +import torch +from typing import Dict, Optional +import comfy.ldm.modules.diffusionmodules.mmdit +import comfy.latent_formats + +class ControlNet(comfy.ldm.modules.diffusionmodules.mmdit.MMDiT): + def __init__( + self, + num_blocks = None, + dtype = None, + device = None, + operations = None, + **kwargs, + ): + super().__init__(dtype=dtype, device=device, operations=operations, final_layer=False, num_blocks=num_blocks, **kwargs) + # controlnet_blocks + self.controlnet_blocks = torch.nn.ModuleList([]) + for _ in range(len(self.joint_blocks)): + self.controlnet_blocks.append(operations.Linear(self.hidden_size, self.hidden_size, device=device, dtype=dtype)) + + self.pos_embed_input = comfy.ldm.modules.diffusionmodules.mmdit.PatchEmbed( + None, + self.patch_size, + self.in_channels, + self.hidden_size, + bias=True, + strict_img_size=False, + dtype=dtype, + device=device, + operations=operations + ) + + self.latent_format = comfy.latent_formats.SD3() + + def forward( + self, + x: torch.Tensor, + timesteps: torch.Tensor, + y: Optional[torch.Tensor] = None, + context: Optional[torch.Tensor] = None, + hint = None, + ) -> torch.Tensor: + + #weird sd3 controlnet specific stuff + hint = hint * self.latent_format.scale_factor # self.latent_format.process_in(hint) + y = torch.zeros_like(y) + + + if self.context_processor is not None: + context = self.context_processor(context) + + hw = x.shape[-2:] + x = self.x_embedder(x) + self.cropped_pos_embed(hw, device=x.device).to(dtype=x.dtype, device=x.device) + x += self.pos_embed_input(hint) + + c = self.t_embedder(timesteps, dtype=x.dtype) + if y is not None and self.y_embedder is not None: + y = self.y_embedder(y) + c = c + y + + if context is not None: + context = self.context_embedder(context) + + if self.register_length > 0: + context = torch.cat( + ( + repeat(self.register, "1 ... -> b ...", b=x.shape[0]), + default(context, torch.Tensor([]).type_as(x)), + ), + 1, + ) + + output = [] + + blocks = len(self.joint_blocks) + for i in range(blocks): + context, x = self.joint_blocks[i]( + context, + x, + c=c, + use_checkpoint=self.use_checkpoint, + ) + + out = self.controlnet_blocks[i](x) + count = self.depth // blocks + if i == blocks - 1: + count -= 1 + for j in range(count): + output.append(out) + + return {"output": output} diff --git a/comfy/controlnet.py b/comfy/controlnet.py index f50df6835..9202c3194 100644 --- a/comfy/controlnet.py +++ b/comfy/controlnet.py @@ -11,6 +11,7 @@ import comfy.ops import comfy.cldm.cldm import comfy.t2i_adapter.adapter import comfy.ldm.cascade.controlnet +import comfy.cldm.mmdit def broadcast_image_to(tensor, target_batch_size, batched_number): @@ -94,13 +95,17 @@ class ControlBase: for key in control: control_output = control[key] + applied_to = set() for i in range(len(control_output)): x = control_output[i] if x is not None: if self.global_average_pooling: x = torch.mean(x, dim=(2, 3), keepdim=True).repeat(1, 1, x.shape[2], x.shape[3]) - x *= self.strength + if x not in applied_to: #memory saving strategy, allow shared tensors and only apply strength to shared tensors once + applied_to.add(x) + x *= self.strength + if x.dtype != output_dtype: x = x.to(output_dtype) @@ -120,17 +125,18 @@ class ControlBase: if o[i].shape[0] < prev_val.shape[0]: o[i] = prev_val + o[i] else: - o[i] += prev_val + o[i] = prev_val + o[i] #TODO: change back to inplace add if shared tensors stop being an issue return out class ControlNet(ControlBase): - def __init__(self, control_model=None, global_average_pooling=False, device=None, load_device=None, manual_cast_dtype=None): + def __init__(self, control_model=None, global_average_pooling=False, compression_ratio=8, device=None, load_device=None, manual_cast_dtype=None): super().__init__(device) self.control_model = control_model self.load_device = load_device if control_model is not None: self.control_model_wrapped = comfy.model_patcher.ModelPatcher(self.control_model, load_device=load_device, offload_device=comfy.model_management.unet_offload_device()) + self.compression_ratio = compression_ratio self.global_average_pooling = global_average_pooling self.model_sampling_current = None self.manual_cast_dtype = manual_cast_dtype @@ -308,6 +314,37 @@ class ControlLora(ControlNet): def inference_memory_requirements(self, dtype): return comfy.utils.calculate_parameters(self.control_weights) * comfy.model_management.dtype_size(dtype) + ControlBase.inference_memory_requirements(self, dtype) +def load_controlnet_mmdit(sd): + new_sd = comfy.model_detection.convert_diffusers_mmdit(sd, "") + model_config = comfy.model_detection.model_config_from_unet(new_sd, "", True) + num_blocks = comfy.model_detection.count_blocks(new_sd, 'joint_blocks.{}.') + for k in sd: + new_sd[k] = sd[k] + + supported_inference_dtypes = model_config.supported_inference_dtypes + + controlnet_config = model_config.unet_config + unet_dtype = comfy.model_management.unet_dtype(supported_dtypes=supported_inference_dtypes) + load_device = comfy.model_management.get_torch_device() + manual_cast_dtype = comfy.model_management.unet_manual_cast(unet_dtype, load_device) + if manual_cast_dtype is not None: + operations = comfy.ops.manual_cast + else: + operations = comfy.ops.disable_weight_init + + control_model = comfy.cldm.mmdit.ControlNet(num_blocks=num_blocks, operations=operations, device=load_device, dtype=unet_dtype, **controlnet_config) + missing, unexpected = control_model.load_state_dict(new_sd, strict=False) + + if len(missing) > 0: + logging.warning("missing controlnet keys: {}".format(missing)) + + if len(unexpected) > 0: + logging.debug("unexpected controlnet keys: {}".format(unexpected)) + + control = ControlNet(control_model, compression_ratio=1, load_device=load_device, manual_cast_dtype=manual_cast_dtype) + return control + + def load_controlnet(ckpt_path, model=None): controlnet_data = comfy.utils.load_torch_file(ckpt_path, safe_load=True) if "lora_controlnet" in controlnet_data: @@ -360,6 +397,8 @@ def load_controlnet(ckpt_path, model=None): if len(leftover_keys) > 0: logging.warning("leftover keys: {}".format(leftover_keys)) controlnet_data = new_sd + elif "controlnet_blocks.0.weight" in controlnet_data: #SD3 diffusers format + return load_controlnet_mmdit(controlnet_data) pth_key = 'control_model.zero_convs.0.0.weight' pth = False diff --git a/comfy/ldm/modules/diffusionmodules/mmdit.py b/comfy/ldm/modules/diffusionmodules/mmdit.py index 20d3a321a..927451534 100644 --- a/comfy/ldm/modules/diffusionmodules/mmdit.py +++ b/comfy/ldm/modules/diffusionmodules/mmdit.py @@ -745,6 +745,8 @@ class MMDiT(nn.Module): qkv_bias: bool = True, context_processor_layers = None, context_size = 4096, + num_blocks = None, + final_layer = True, dtype = None, #TODO device = None, operations = None, @@ -766,7 +768,10 @@ class MMDiT(nn.Module): # apply magic --> this defines a head_size of 64 self.hidden_size = 64 * depth num_heads = depth + if num_blocks is None: + num_blocks = depth + self.depth = depth self.num_heads = num_heads self.x_embedder = PatchEmbed( @@ -821,7 +826,7 @@ class MMDiT(nn.Module): mlp_ratio=mlp_ratio, qkv_bias=qkv_bias, attn_mode=attn_mode, - pre_only=i == depth - 1, + pre_only=(i == num_blocks - 1) and final_layer, rmsnorm=rmsnorm, scale_mod_only=scale_mod_only, swiglu=swiglu, @@ -830,11 +835,12 @@ class MMDiT(nn.Module): device=device, operations=operations ) - for i in range(depth) + for i in range(num_blocks) ] ) - self.final_layer = FinalLayer(self.hidden_size, patch_size, self.out_channels, dtype=dtype, device=device, operations=operations) + if final_layer: + self.final_layer = FinalLayer(self.hidden_size, patch_size, self.out_channels, dtype=dtype, device=device, operations=operations) if compile_core: assert False @@ -893,6 +899,7 @@ class MMDiT(nn.Module): x: torch.Tensor, c_mod: torch.Tensor, context: Optional[torch.Tensor] = None, + control = None, ) -> torch.Tensor: if self.register_length > 0: context = torch.cat( @@ -905,13 +912,20 @@ class MMDiT(nn.Module): # context is B, L', D # x is B, L, D - for block in self.joint_blocks: - context, x = block( + blocks = len(self.joint_blocks) + for i in range(blocks): + context, x = self.joint_blocks[i]( context, x, c=c_mod, use_checkpoint=self.use_checkpoint, ) + if control is not None: + control_o = control.get("output") + if i < len(control_o): + add = control_o[i] + if add is not None: + x += add x = self.final_layer(x, c_mod) # (N, T, patch_size ** 2 * out_channels) return x @@ -922,6 +936,7 @@ class MMDiT(nn.Module): t: torch.Tensor, y: Optional[torch.Tensor] = None, context: Optional[torch.Tensor] = None, + control = None, ) -> torch.Tensor: """ Forward pass of DiT. @@ -943,7 +958,7 @@ class MMDiT(nn.Module): if context is not None: context = self.context_embedder(context) - x = self.forward_core_with_concat(x, c, context) + x = self.forward_core_with_concat(x, c, context, control) x = self.unpatchify(x, hw=hw) # (N, out_channels, H, W) return x[:,:,:hw[-2],:hw[-1]] @@ -956,7 +971,8 @@ class OpenAISignatureMMDITWrapper(MMDiT): timesteps: torch.Tensor, context: Optional[torch.Tensor] = None, y: Optional[torch.Tensor] = None, + control = None, **kwargs, ) -> torch.Tensor: - return super().forward(x, timesteps, context=context, y=y) + return super().forward(x, timesteps, context=context, y=y, control=control) diff --git a/comfy/model_detection.py b/comfy/model_detection.py index e09dd381a..0b678480f 100644 --- a/comfy/model_detection.py +++ b/comfy/model_detection.py @@ -41,7 +41,9 @@ def detect_unet_config(state_dict, key_prefix): unet_config["in_channels"] = state_dict['{}x_embedder.proj.weight'.format(key_prefix)].shape[1] patch_size = state_dict['{}x_embedder.proj.weight'.format(key_prefix)].shape[2] unet_config["patch_size"] = patch_size - unet_config["out_channels"] = state_dict['{}final_layer.linear.weight'.format(key_prefix)].shape[0] // (patch_size * patch_size) + final_layer = '{}final_layer.linear.weight'.format(key_prefix) + if final_layer in state_dict: + unet_config["out_channels"] = state_dict[final_layer].shape[0] // (patch_size * patch_size) unet_config["depth"] = state_dict['{}x_embedder.proj.weight'.format(key_prefix)].shape[0] // 64 unet_config["input_size"] = None @@ -435,10 +437,11 @@ def model_config_from_diffusers_unet(state_dict): return None def convert_diffusers_mmdit(state_dict, output_prefix=""): - depth = count_blocks(state_dict, 'transformer_blocks.{}.') - if depth > 0: + num_blocks = count_blocks(state_dict, 'transformer_blocks.{}.') + if num_blocks > 0: + depth = state_dict["pos_embed.proj.weight"].shape[0] // 64 out_sd = {} - sd_map = comfy.utils.mmdit_to_diffusers({"depth": depth}, output_prefix=output_prefix) + sd_map = comfy.utils.mmdit_to_diffusers({"depth": depth, "num_blocks": num_blocks}, output_prefix=output_prefix) for k in sd_map: weight = state_dict.get(k, None) if weight is not None: diff --git a/comfy/utils.py b/comfy/utils.py index ed6c58a64..48618e076 100644 --- a/comfy/utils.py +++ b/comfy/utils.py @@ -298,7 +298,8 @@ def mmdit_to_diffusers(mmdit_config, output_prefix=""): key_map = {} depth = mmdit_config.get("depth", 0) - for i in range(depth): + num_blocks = mmdit_config.get("num_blocks", depth) + for i in range(num_blocks): block_from = "transformer_blocks.{}".format(i) block_to = "{}joint_blocks.{}".format(output_prefix, i) From 264caca20e1e051f3bcbec59d7209513ea99d4ed Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Wed, 26 Jun 2024 16:14:47 -0400 Subject: [PATCH 022/133] ControlNetApplySD3 node can now be used to use SD3 controlnets. --- comfy/cldm/mmdit.py | 5 ----- comfy/controlnet.py | 28 ++++++++++++++++++++++++---- comfy_extras/nodes_sd3.py | 15 +++++++++++++++ nodes.py | 4 ++-- 4 files changed, 41 insertions(+), 11 deletions(-) diff --git a/comfy/cldm/mmdit.py b/comfy/cldm/mmdit.py index 6e72474ce..ee0282bc7 100644 --- a/comfy/cldm/mmdit.py +++ b/comfy/cldm/mmdit.py @@ -1,7 +1,6 @@ import torch from typing import Dict, Optional import comfy.ldm.modules.diffusionmodules.mmdit -import comfy.latent_formats class ControlNet(comfy.ldm.modules.diffusionmodules.mmdit.MMDiT): def __init__( @@ -30,8 +29,6 @@ class ControlNet(comfy.ldm.modules.diffusionmodules.mmdit.MMDiT): operations=operations ) - self.latent_format = comfy.latent_formats.SD3() - def forward( self, x: torch.Tensor, @@ -42,10 +39,8 @@ class ControlNet(comfy.ldm.modules.diffusionmodules.mmdit.MMDiT): ) -> torch.Tensor: #weird sd3 controlnet specific stuff - hint = hint * self.latent_format.scale_factor # self.latent_format.process_in(hint) y = torch.zeros_like(y) - if self.context_processor is not None: context = self.context_processor(context) diff --git a/comfy/controlnet.py b/comfy/controlnet.py index 9202c3194..d00395139 100644 --- a/comfy/controlnet.py +++ b/comfy/controlnet.py @@ -7,6 +7,7 @@ import comfy.model_management import comfy.model_detection import comfy.model_patcher import comfy.ops +import comfy.latent_formats import comfy.cldm.cldm import comfy.t2i_adapter.adapter @@ -38,6 +39,8 @@ class ControlBase: self.cond_hint = None self.strength = 1.0 self.timestep_percent_range = (0.0, 1.0) + self.latent_format = None + self.vae = None self.global_average_pooling = False self.timestep_range = None self.compression_ratio = 8 @@ -48,10 +51,12 @@ class ControlBase: self.device = device self.previous_controlnet = None - def set_cond_hint(self, cond_hint, strength=1.0, timestep_percent_range=(0.0, 1.0)): + def set_cond_hint(self, cond_hint, strength=1.0, timestep_percent_range=(0.0, 1.0), vae=None): self.cond_hint_original = cond_hint self.strength = strength self.timestep_percent_range = timestep_percent_range + if self.latent_format is not None: + self.vae = vae return self def pre_run(self, model, percent_to_timestep_function): @@ -84,6 +89,8 @@ class ControlBase: c.global_average_pooling = self.global_average_pooling c.compression_ratio = self.compression_ratio c.upscale_algorithm = self.upscale_algorithm + c.latent_format = self.latent_format + c.vae = self.vae def inference_memory_requirements(self, dtype): if self.previous_controlnet is not None: @@ -129,7 +136,7 @@ class ControlBase: return out class ControlNet(ControlBase): - def __init__(self, control_model=None, global_average_pooling=False, compression_ratio=8, device=None, load_device=None, manual_cast_dtype=None): + def __init__(self, control_model=None, global_average_pooling=False, compression_ratio=8, latent_format=None, device=None, load_device=None, manual_cast_dtype=None): super().__init__(device) self.control_model = control_model self.load_device = load_device @@ -140,6 +147,7 @@ class ControlNet(ControlBase): self.global_average_pooling = global_average_pooling self.model_sampling_current = None self.manual_cast_dtype = manual_cast_dtype + self.latent_format = latent_format def get_control(self, x_noisy, t, cond, batched_number): control_prev = None @@ -162,7 +170,17 @@ class ControlNet(ControlBase): if self.cond_hint is not None: del self.cond_hint self.cond_hint = None - self.cond_hint = comfy.utils.common_upscale(self.cond_hint_original, x_noisy.shape[3] * self.compression_ratio, x_noisy.shape[2] * self.compression_ratio, self.upscale_algorithm, "center").to(dtype).to(self.device) + compression_ratio = self.compression_ratio + if self.vae is not None: + compression_ratio *= self.vae.downscale_ratio + self.cond_hint = comfy.utils.common_upscale(self.cond_hint_original, x_noisy.shape[3] * compression_ratio, x_noisy.shape[2] * compression_ratio, self.upscale_algorithm, "center") + if self.vae is not None: + loaded_models = comfy.model_management.loaded_models(only_currently_used=True) + self.cond_hint = self.vae.encode(self.cond_hint.movedim(1, -1)) + comfy.model_management.load_models_gpu(loaded_models) + if self.latent_format is not None: + self.cond_hint = self.latent_format.process_in(self.cond_hint) + self.cond_hint = self.cond_hint.to(device=self.device, dtype=dtype) if x_noisy.shape[0] != self.cond_hint.shape[0]: self.cond_hint = broadcast_image_to(self.cond_hint, x_noisy.shape[0], batched_number) @@ -341,7 +359,9 @@ def load_controlnet_mmdit(sd): if len(unexpected) > 0: logging.debug("unexpected controlnet keys: {}".format(unexpected)) - control = ControlNet(control_model, compression_ratio=1, load_device=load_device, manual_cast_dtype=manual_cast_dtype) + latent_format = comfy.latent_formats.SD3() + latent_format.shift_factor = 0 #SD3 controlnet weirdness + control = ControlNet(control_model, compression_ratio=1, latent_format=latent_format, load_device=load_device, manual_cast_dtype=manual_cast_dtype) return control diff --git a/comfy_extras/nodes_sd3.py b/comfy_extras/nodes_sd3.py index d0303aec5..548b1ad6a 100644 --- a/comfy_extras/nodes_sd3.py +++ b/comfy_extras/nodes_sd3.py @@ -80,8 +80,23 @@ class CLIPTextEncodeSD3: return ([[cond, {"pooled_output": pooled}]], ) +class ControlNetApplySD3(nodes.ControlNetApplyAdvanced): + @classmethod + def INPUT_TYPES(s): + return {"required": {"positive": ("CONDITIONING", ), + "negative": ("CONDITIONING", ), + "control_net": ("CONTROL_NET", ), + "vae": ("VAE", ), + "image": ("IMAGE", ), + "strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}), + "start_percent": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001}), + "end_percent": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.001}) + }} + CATEGORY = "_for_testing/sd3" + NODE_CLASS_MAPPINGS = { "TripleCLIPLoader": TripleCLIPLoader, "EmptySD3LatentImage": EmptySD3LatentImage, "CLIPTextEncodeSD3": CLIPTextEncodeSD3, + "ControlNetApplySD3": ControlNetApplySD3, } diff --git a/nodes.py b/nodes.py index 99645b81c..04775d290 100644 --- a/nodes.py +++ b/nodes.py @@ -783,7 +783,7 @@ class ControlNetApplyAdvanced: CATEGORY = "conditioning" - def apply_controlnet(self, positive, negative, control_net, image, strength, start_percent, end_percent): + def apply_controlnet(self, positive, negative, control_net, image, strength, start_percent, end_percent, vae=None): if strength == 0: return (positive, negative) @@ -800,7 +800,7 @@ class ControlNetApplyAdvanced: if prev_cnet in cnets: c_net = cnets[prev_cnet] else: - c_net = control_net.copy().set_cond_hint(control_hint, strength, (start_percent, end_percent)) + c_net = control_net.copy().set_cond_hint(control_hint, strength, (start_percent, end_percent), vae) c_net.set_previous_controlnet(prev_cnet) cnets[prev_cnet] = c_net From 0d9009c96ea5a1922a1c187deef27c7f133ee946 Mon Sep 17 00:00:00 2001 From: pythongosssss <125205205+pythongosssss@users.noreply.github.com> Date: Fri, 28 Jun 2024 06:07:19 +0100 Subject: [PATCH 023/133] New menu/workflows fixes (#3900) * Fix auto queue * Detect added nodes via search * Fix loading workflows * Add button click style --- web/scripts/changeTracker.js | 12 +++++++++++- web/scripts/ui/menu/menu.css | 4 ++++ web/scripts/ui/menu/queueButton.js | 4 ++-- web/scripts/workflows.js | 4 ++-- 4 files changed, 19 insertions(+), 5 deletions(-) diff --git a/web/scripts/changeTracker.js b/web/scripts/changeTracker.js index 59901d5fc..041c83122 100644 --- a/web/scripts/changeTracker.js +++ b/web/scripts/changeTracker.js @@ -3,7 +3,6 @@ import { api } from "./api.js"; import { clone } from "./utils.js"; - export class ChangeTracker { static MAX_HISTORY = 50; #app; @@ -170,6 +169,17 @@ export class ChangeTracker { return v; }; + // Detects nodes being added via the node search dialog + const onNodeAdded = LiteGraph.LGraph.prototype.onNodeAdded; + LiteGraph.LGraph.prototype.onNodeAdded = function () { + const v = onNodeAdded?.apply(this, arguments); + const ct = changeTracker(); + if (!ct.isOurLoad) { + ct.checkState(); + } + return v; + }; + // Store node outputs api.addEventListener("executed", ({ detail }) => { const prompt = app.workflowManager.queuedPrompts[detail.prompt_id]; diff --git a/web/scripts/ui/menu/menu.css b/web/scripts/ui/menu/menu.css index 20eeab2cf..afaed3fb0 100644 --- a/web/scripts/ui/menu/menu.css +++ b/web/scripts/ui/menu/menu.css @@ -19,8 +19,12 @@ padding: 4px 8px; box-sizing: border-box; margin: 0; + transition: box-shadow 0.1s; } +.comfyui-button:active { + box-shadow: inset 1px 1px 10px rgba(0, 0, 0, 0.5); +} .comfyui-button:disabled { opacity: 0.5; cursor: not-allowed; diff --git a/web/scripts/ui/menu/queueButton.js b/web/scripts/ui/menu/queueButton.js index 3c29ab090..608f4cc9b 100644 --- a/web/scripts/ui/menu/queueButton.js +++ b/web/scripts/ui/menu/queueButton.js @@ -13,8 +13,8 @@ export class ComfyQueueButton { queuePrompt = async (e) => { this.#internalQueueSize += this.queueOptions.batchCount; - // Hold shift to queue front - await this.app.queuePrompt(-e.shiftKey, this.queueOptions.batchCount); + // Hold shift to queue front, event is undefined when auto-queue is enabled + await this.app.queuePrompt(e?.shiftKey ? -1 : 0, this.queueOptions.batchCount); }; constructor(app) { diff --git a/web/scripts/workflows.js b/web/scripts/workflows.js index 16bbc9976..d38b6f5fc 100644 --- a/web/scripts/workflows.js +++ b/web/scripts/workflows.js @@ -301,11 +301,11 @@ export class ComfyWorkflow { load = async () => { if (this.isOpen) { - await this.manager.app.loadGraphData(this.changeTracker.activeState, true, this); + await this.manager.app.loadGraphData(this.changeTracker.activeState, true, true, this); } else { const data = await this.getWorkflowData(); if (!data) return; - await this.manager.app.loadGraphData(data, true, this); + await this.manager.app.loadGraphData(data, true, true, this); } }; From 7ecb2ec1699dc988f93188c04733eeb8a41e8196 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Fri, 28 Jun 2024 02:55:36 -0400 Subject: [PATCH 024/133] Audio second setting in EmptyLatentAudio. --- comfy_extras/nodes_audio.py | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/comfy_extras/nodes_audio.py b/comfy_extras/nodes_audio.py index 34bcfa96d..6481ed3ba 100644 --- a/comfy_extras/nodes_audio.py +++ b/comfy_extras/nodes_audio.py @@ -14,15 +14,16 @@ class EmptyLatentAudio: @classmethod def INPUT_TYPES(s): - return {"required": {}} + return {"required": {"seconds": ("FLOAT", {"default": 47.6, "min": 1.0, "max": 1000.0, "step": 0.1})}} RETURN_TYPES = ("LATENT",) FUNCTION = "generate" CATEGORY = "_for_testing/audio" - def generate(self): + def generate(self, seconds): batch_size = 1 - latent = torch.zeros([batch_size, 64, 1024], device=self.device) + length = round((seconds * 44100 / 2048) / 2) * 2 + latent = torch.zeros([batch_size, 64, length], device=self.device) return ({"samples":latent, "type": "audio"}, ) class VAEEncodeAudio: From 02cac1d48783725d5994d37ed03e9f3dc32ec504 Mon Sep 17 00:00:00 2001 From: Robin Huang Date: Fri, 28 Jun 2024 13:09:39 -0700 Subject: [PATCH 025/133] Revert "Add macOs integration test for default workflow. (#3898)" (#3904) This reverts commit 97b409cd486b1a3b1114ae204802c81f3727d1a2. --- .../conda-environments/mac-environment.yml | 26 ---------- .github/workflows/mac-integration-test.yml | 50 ------------------- 2 files changed, 76 deletions(-) delete mode 100644 .github/conda-environments/mac-environment.yml delete mode 100644 .github/workflows/mac-integration-test.yml diff --git a/.github/conda-environments/mac-environment.yml b/.github/conda-environments/mac-environment.yml deleted file mode 100644 index 33832b854..000000000 --- a/.github/conda-environments/mac-environment.yml +++ /dev/null @@ -1,26 +0,0 @@ -name: comfyui -channels: - - pytorch-nightly - - defaults -dependencies: - - python>=3.9 - - pytorch-nightly::pytorch - - torchvision - - torchaudio - - pip: - - pip - # comfyui requirements - - einops - - transformers>=4.25.1 - - safetensors>=0.4.2 - - aiohttp - - pyyaml - - Pillow - - scipy - - tqdm - - psutil - # comfy-action requirements - - requests - - google-cloud-storage - - comfy-cli - - charset-normalizer diff --git a/.github/workflows/mac-integration-test.yml b/.github/workflows/mac-integration-test.yml deleted file mode 100644 index 6a0482b1b..000000000 --- a/.github/workflows/mac-integration-test.yml +++ /dev/null @@ -1,50 +0,0 @@ -name: (macOS) ComfyUI Integration Tests -on: - push: - branches: - - master - paths-ignore: - - 'app/**' - - 'input/**' - - 'output/**' - - 'model/**' - - 'notebook/**' - - 'script_example/**' - - 'tests/**' - - 'tests-ui/**' - - '.github/**' - - '.ci/**' - - 'web/**' - workflow_dispatch: - pull_request: - branches: - - master - paths-ignore: - - 'app/**' - - 'input/**' - - 'output/**' - - 'model/**' - - 'notebook/**' - - 'script_example/**' - - 'tests/**' - - 'tests-ui/**' - - '.github/**' - - '.ci/**' - - 'web/**' - -jobs: - test-workflows: - runs-on: [self-hosted, m2] - steps: - - name: Test ComfyUI Workflows - uses: comfy-org/comfy-action@main - with: - os: mac - models-json: '{"v1-5-pruned-emaonly.ckpt": {"url": "https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.ckpt", "directory": "checkpoints"}}' - workflow_filenames: "default.json" - gcs_bucket_name: 'comfy-ci-results' - google_credentials: ${{ secrets.GCS_SERVICE_ACCOUNT_JSON }} - output_prefix: 'ComfyUI' - conda_env_file: '.github/conda-environments/mac-environment.yml' - timeout: 50 - From c39cf7fff09c728d573835a48106e2133c446e11 Mon Sep 17 00:00:00 2001 From: Robin Huang Date: Fri, 28 Jun 2024 13:09:55 -0700 Subject: [PATCH 026/133] Revert "Add integration test for Linux with Nvidia GPU. #3884 (#3895)" (#3905) This reverts commit 449bf52923896236ed645da2ff05aadbf2b0d536. --- .../conda-environments/linux-environment.yml | 28 ----------- .github/workflows/linux-integration-test.yml | 50 ------------------- 2 files changed, 78 deletions(-) delete mode 100644 .github/conda-environments/linux-environment.yml delete mode 100644 .github/workflows/linux-integration-test.yml diff --git a/.github/conda-environments/linux-environment.yml b/.github/conda-environments/linux-environment.yml deleted file mode 100644 index c9ebd6406..000000000 --- a/.github/conda-environments/linux-environment.yml +++ /dev/null @@ -1,28 +0,0 @@ -name: comfyui -channels: - - pytorch - - nvidia - - defaults -dependencies: - - python>=3.9 - - pip - - pytorch - - torchvision - - torchaudio - - pytorch-cuda=12.1 - - pip: - # comfyui requirements - - einops - - transformers>=4.25.1 - - safetensors>=0.4.2 - - aiohttp - - pyyaml - - Pillow - - scipy - - tqdm - - psutil - # comfy-action requirements - - requests - - google-cloud-storage - - comfy-cli - - charset-normalizer \ No newline at end of file diff --git a/.github/workflows/linux-integration-test.yml b/.github/workflows/linux-integration-test.yml deleted file mode 100644 index eed84a77c..000000000 --- a/.github/workflows/linux-integration-test.yml +++ /dev/null @@ -1,50 +0,0 @@ -name: (Linux) ComfyUI Integration Tests -on: - push: - branches: - - master - paths-ignore: - - 'app/**' - - 'input/**' - - 'output/**' - - 'model/**' - - 'notebook/**' - - 'script_example/**' - - 'tests/**' - - 'tests-ui/**' - - '.github/**' - - '.ci/**' - - 'web/**' - workflow_dispatch: - pull_request: - branches: - - master - paths-ignore: - - 'app/**' - - 'input/**' - - 'output/**' - - 'model/**' - - 'notebook/**' - - 'script_example/**' - - 'tests/**' - - 'tests-ui/**' - - '.github/**' - - '.ci/**' - - 'web/**' - -jobs: - test-workflows: - runs-on: [self-hosted, Linux, t4] - steps: - - name: Test ComfyUI Workflows - uses: comfy-org/comfy-action@main - with: - os: linux - cuda_version: 12.1 - models-json: '{"v1-5-pruned-emaonly.ckpt": {"url": "https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.ckpt", "directory": "checkpoints"}}' - workflow_filenames: "default.json" - gcs_bucket_name: 'comfy-ci-results' - google_credentials: ${{ secrets.GCS_SERVICE_ACCOUNT_JSON }} - output_prefix: 'ComfyUI' - conda_env_file: '.github/conda-environments/linux-environment.yml' - timeout: 50 From fbb7a1f1b663b170d49718590aa1cb4093586f20 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Sat, 29 Jun 2024 01:33:22 -0400 Subject: [PATCH 027/133] PreviewAudio node. --- comfy_extras/nodes_audio.py | 16 +++++++++++++++- web/extensions/core/uploadAudio.js | 6 +++--- 2 files changed, 18 insertions(+), 4 deletions(-) diff --git a/comfy_extras/nodes_audio.py b/comfy_extras/nodes_audio.py index 6481ed3ba..9950d58ed 100644 --- a/comfy_extras/nodes_audio.py +++ b/comfy_extras/nodes_audio.py @@ -6,6 +6,7 @@ import os import io import json import struct +import random from comfy.cli_args import args class EmptyLatentAudio: @@ -118,7 +119,6 @@ class SaveAudio: self.output_dir = folder_paths.get_output_directory() self.type = "output" self.prefix_append = "" - self.compress_level = 4 @classmethod def INPUT_TYPES(s): @@ -168,6 +168,19 @@ class SaveAudio: return { "ui": { "audio": results } } +class PreviewAudio(SaveAudio): + def __init__(self): + self.output_dir = folder_paths.get_temp_directory() + self.type = "temp" + self.prefix_append = "_temp_" + ''.join(random.choice("abcdefghijklmnopqrstupvxyz") for x in range(5)) + + @classmethod + def INPUT_TYPES(s): + return {"required": + {"audio": ("AUDIO", ), }, + "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"}, + } + class LoadAudio: SUPPORTED_FORMATS = ('.wav', '.mp3', '.ogg', '.flac', '.aiff', '.aif') @@ -214,4 +227,5 @@ NODE_CLASS_MAPPINGS = { "VAEDecodeAudio": VAEDecodeAudio, "SaveAudio": SaveAudio, "LoadAudio": LoadAudio, + "PreviewAudio": PreviewAudio, } diff --git a/web/extensions/core/uploadAudio.js b/web/extensions/core/uploadAudio.js index 12a2a196b..0ac9cb807 100644 --- a/web/extensions/core/uploadAudio.js +++ b/web/extensions/core/uploadAudio.js @@ -70,7 +70,7 @@ async function uploadFile( app.registerExtension({ name: "Comfy.AudioWidget", async beforeRegisterNodeDef(nodeType, nodeData) { - if (["LoadAudio", "SaveAudio"].includes(nodeType.comfyClass)) { + if (["LoadAudio", "SaveAudio", "PreviewAudio"].includes(nodeType.comfyClass)) { nodeData.input.required.audioUI = ["AUDIO_UI"] } }, @@ -103,7 +103,7 @@ app.registerExtension({ if (!audios) return const audio = audios[0] audioUIWidget.element.src = api.apiURL( - getResourceURL(audio.subfolder, audio.filename, "output") + getResourceURL(audio.subfolder, audio.filename, audio.type) ) audioUIWidget.element.classList.remove("empty-audio-widget") } @@ -118,7 +118,7 @@ app.registerExtension({ if ("audio" in output) { const audioUIWidget = node.widgets.find((w) => w.name === "audioUI"); const audio = output.audio[0]; - audioUIWidget.element.src = api.apiURL(getResourceURL(audio.subfolder, audio.filename, "output")); + audioUIWidget.element.src = api.apiURL(getResourceURL(audio.subfolder, audio.filename, audio.type)); audioUIWidget.element.classList.remove("empty-audio-widget"); } } From 05e831697a03984032863b2aa5d6443e422713e6 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Sat, 29 Jun 2024 11:59:48 -0400 Subject: [PATCH 028/133] Switch to the real cfg++ method in the samplers. The old _pp ones will be updated automatically to the regular ones with 2x the cfg. My fault for not checking what the "_pp" samplers actually did. --- comfy/k_diffusion/sampling.py | 12 ++++++------ comfy/samplers.py | 2 +- web/scripts/app.js | 8 ++++++++ 3 files changed, 15 insertions(+), 7 deletions(-) diff --git a/comfy/k_diffusion/sampling.py b/comfy/k_diffusion/sampling.py index f8091bb3f..763d8cc78 100644 --- a/comfy/k_diffusion/sampling.py +++ b/comfy/k_diffusion/sampling.py @@ -998,7 +998,7 @@ def sample_deis(model, x, sigmas, extra_args=None, callback=None, disable=None, return x_next @torch.no_grad() -def sample_euler_pp(model, x, sigmas, extra_args=None, callback=None, disable=None): +def sample_euler_cfg_pp(model, x, sigmas, extra_args=None, callback=None, disable=None): extra_args = {} if extra_args is None else extra_args temp = [0] @@ -1013,16 +1013,16 @@ def sample_euler_pp(model, x, sigmas, extra_args=None, callback=None, disable=No for i in trange(len(sigmas) - 1, disable=disable): sigma_hat = sigmas[i] denoised = model(x, sigma_hat * s_in, **extra_args) - d = to_d(x - denoised + temp[0], sigma_hat, denoised) + d = to_d(x, sigma_hat, temp[0]) if callback is not None: callback({'x': x, 'i': i, 'sigma': sigmas[i], 'sigma_hat': sigma_hat, 'denoised': denoised}) dt = sigmas[i + 1] - sigma_hat # Euler method - x = x + d * dt + x = denoised + d * sigmas[i + 1] return x @torch.no_grad() -def sample_euler_ancestral_pp(model, x, sigmas, extra_args=None, callback=None, disable=None, eta=1., s_noise=1., noise_sampler=None): +def sample_euler_ancestral_cfg_pp(model, x, sigmas, extra_args=None, callback=None, disable=None, eta=1., s_noise=1., noise_sampler=None): """Ancestral sampling with Euler method steps.""" extra_args = {} if extra_args is None else extra_args noise_sampler = default_noise_sampler(x) if noise_sampler is None else noise_sampler @@ -1041,10 +1041,10 @@ def sample_euler_ancestral_pp(model, x, sigmas, extra_args=None, callback=None, sigma_down, sigma_up = get_ancestral_step(sigmas[i], sigmas[i + 1], eta=eta) if callback is not None: callback({'x': x, 'i': i, 'sigma': sigmas[i], 'sigma_hat': sigmas[i], 'denoised': denoised}) - d = to_d(x - denoised + temp[0], sigmas[i], denoised) + d = to_d(x, sigmas[i], temp[0]) # Euler method dt = sigma_down - sigmas[i] - x = x + d * dt + x = denoised + d * sigma_down if sigmas[i + 1] > 0: x = x + noise_sampler(sigmas[i], sigmas[i + 1]) * s_noise * sigma_up return x diff --git a/comfy/samplers.py b/comfy/samplers.py index 7f7114dbb..c0aa12916 100644 --- a/comfy/samplers.py +++ b/comfy/samplers.py @@ -537,7 +537,7 @@ class Sampler: sigma = float(sigmas[0]) return math.isclose(max_sigma, sigma, rel_tol=1e-05) or sigma > max_sigma -KSAMPLER_NAMES = ["euler", "euler_pp", "euler_ancestral", "euler_ancestral_pp", "heun", "heunpp2","dpm_2", "dpm_2_ancestral", +KSAMPLER_NAMES = ["euler", "euler_cfg_pp", "euler_ancestral", "euler_ancestral_cfg_pp", "heun", "heunpp2","dpm_2", "dpm_2_ancestral", "lms", "dpm_fast", "dpm_adaptive", "dpmpp_2s_ancestral", "dpmpp_sde", "dpmpp_sde_gpu", "dpmpp_2m", "dpmpp_2m_sde", "dpmpp_2m_sde_gpu", "dpmpp_3m_sde", "dpmpp_3m_sde_gpu", "ddpm", "lcm", "ipndm", "ipndm_v", "deis"] diff --git a/web/scripts/app.js b/web/scripts/app.js index 43df61065..3a91aa239 100644 --- a/web/scripts/app.js +++ b/web/scripts/app.js @@ -1966,6 +1966,14 @@ export class ComfyApp { if (widget.value.startsWith("sample_")) { widget.value = widget.value.slice(7); } + if (widget.value === "euler_pp" || widget.value === "euler_ancestral_pp") { + widget.value = widget.value.slice(0, -3); + for (let w of node.widgets) { + if (w.name == "cfg") { + w.value *= 2.0; + } + } + } } } if (node.type == "KSampler" || node.type == "KSamplerAdvanced" || node.type == "PrimitiveNode") { From dbb7dd3b5eb6672e1141a5fc7006d3bee08b0d21 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Sun, 30 Jun 2024 00:15:49 -0400 Subject: [PATCH 029/133] Add to readme that Stable Audio is supported. --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index a40dd07dd..2ce7c3e6b 100644 --- a/README.md +++ b/README.md @@ -11,16 +11,16 @@ This ui will let you design and execute advanced stable diffusion pipelines usin ## Features - Nodes/graph/flowchart interface to experiment and create complex Stable Diffusion workflows without needing to code anything. -- Fully supports SD1.x, SD2.x, [SDXL](https://comfyanonymous.github.io/ComfyUI_examples/sdxl/), [Stable Video Diffusion](https://comfyanonymous.github.io/ComfyUI_examples/video/), [Stable Cascade](https://comfyanonymous.github.io/ComfyUI_examples/stable_cascade/) and [SD3](https://comfyanonymous.github.io/ComfyUI_examples/sd3/) +- Fully supports SD1.x, SD2.x, [SDXL](https://comfyanonymous.github.io/ComfyUI_examples/sdxl/), [Stable Video Diffusion](https://comfyanonymous.github.io/ComfyUI_examples/video/), [Stable Cascade](https://comfyanonymous.github.io/ComfyUI_examples/stable_cascade/), [SD3](https://comfyanonymous.github.io/ComfyUI_examples/sd3/) and [Stable Audio](https://comfyanonymous.github.io/ComfyUI_examples/audio/) - Asynchronous Queue system - Many optimizations: Only re-executes the parts of the workflow that changes between executions. -- Command line option: ```--lowvram``` to make it work on GPUs with less than 3GB vram (enabled automatically on GPUs with low vram) +- Smart memory management: can automatically run models on GPUs with as low as 1GB vram. - Works even if you don't have a GPU with: ```--cpu``` (slow) - Can load ckpt, safetensors and diffusers models/checkpoints. Standalone VAEs and CLIP models. - Embeddings/Textual inversion - [Loras (regular, locon and loha)](https://comfyanonymous.github.io/ComfyUI_examples/lora/) - [Hypernetworks](https://comfyanonymous.github.io/ComfyUI_examples/hypernetworks/) -- Loading full workflows (with seeds) from generated PNG files. +- Loading full workflows (with seeds) from generated PNG, WebP and FLAC files. - Saving/Loading workflows as Json files. - Nodes interface can be used to create complex workflows like one for [Hires fix](https://comfyanonymous.github.io/ComfyUI_examples/2_pass_txt2img/) or much more advanced ones. - [Area Composition](https://comfyanonymous.github.io/ComfyUI_examples/area_composition/) From 521421f53ee1ba74304dfaa138b0f851093e1595 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Sun, 30 Jun 2024 15:51:54 -0400 Subject: [PATCH 030/133] Fix workflow not importing from flac files on some systems. --- web/scripts/app.js | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/web/scripts/app.js b/web/scripts/app.js index 3a91aa239..776fc197a 100644 --- a/web/scripts/app.js +++ b/web/scripts/app.js @@ -2292,7 +2292,7 @@ export class ComfyApp { } else { this.showErrorOnFileLoad(file); } - } else if (file.type === "audio/flac") { + } else if (file.type === "audio/flac" || file.type === "audio/x-flac") { const pngInfo = await getFlacMetadata(file); // Support loading workflows from that webp custom node. const workflow = pngInfo?.workflow; From 7c5fa7f4a2046c1f4bb77ed5e480918ffb8a10aa Mon Sep 17 00:00:00 2001 From: Chenlei Hu Date: Mon, 1 Jul 2024 12:10:44 -0400 Subject: [PATCH 031/133] Fix loadGraphData func call (#3918) --- web/scripts/app.js | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/web/scripts/app.js b/web/scripts/app.js index 776fc197a..b8889a4cf 100644 --- a/web/scripts/app.js +++ b/web/scripts/app.js @@ -2314,14 +2314,14 @@ export class ComfyApp { } else if(this.isApiJson(jsonContent)) { this.loadApiJson(jsonContent, fileName); } else { - await this.loadGraphData(jsonContent, true, fileName); + await this.loadGraphData(jsonContent, true, true, fileName); } }; reader.readAsText(file); } else if (file.name?.endsWith(".latent") || file.name?.endsWith(".safetensors")) { const info = await getLatentMetadata(file); if (info.workflow) { - await this.loadGraphData(JSON.parse(info.workflow), true, fileName); + await this.loadGraphData(JSON.parse(info.workflow), true, true, fileName); } else if (info.prompt) { this.loadApiJson(JSON.parse(info.prompt)); } else { From e53b1592ba8426e2c01cd9278bc19c2e4264065b Mon Sep 17 00:00:00 2001 From: ruucm Date: Mon, 1 Jul 2024 10:45:34 -0700 Subject: [PATCH 032/133] enable cmd shortcuts for mac (mute & bypass) (#3792) --- web/scripts/app.js | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/web/scripts/app.js b/web/scripts/app.js index b8889a4cf..67e488bf9 100644 --- a/web/scripts/app.js +++ b/web/scripts/app.js @@ -1084,7 +1084,7 @@ export class ComfyApp { if (e.type == "keydown" && !e.repeat) { // Ctrl + M mute/unmute - if (e.key === 'm' && e.ctrlKey) { + if (e.key === 'm' && (e.metaKey || e.ctrlKey)) { if (this.selected_nodes) { for (var i in this.selected_nodes) { if (this.selected_nodes[i].mode === 2) { // never @@ -1098,7 +1098,7 @@ export class ComfyApp { } // Ctrl + B bypass - if (e.key === 'b' && e.ctrlKey) { + if (e.key === 'b' && (e.metaKey || e.ctrlKey)) { if (this.selected_nodes) { for (var i in this.selected_nodes) { if (this.selected_nodes[i].mode === 4) { // never From 601b4b63e1c0af2deef8630449497b9e84aa00f8 Mon Sep 17 00:00:00 2001 From: Robin Huang Date: Mon, 1 Jul 2024 10:51:00 -0700 Subject: [PATCH 033/133] Add CONTRIBUTING.md (#3910) * Create CONTRIBUTING.md * Add feature-request channel link. * Remove discord links for channels. --- CONTRIBUTING.md | 41 +++++++++++++++++++++++++++++++++++++++++ 1 file changed, 41 insertions(+) create mode 100644 CONTRIBUTING.md diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md new file mode 100644 index 000000000..048f127e7 --- /dev/null +++ b/CONTRIBUTING.md @@ -0,0 +1,41 @@ +# Contributing to ComfyUI + +Welcome, and thank you for your interest in contributing to ComfyUI! + +There are several ways in which you can contribute, beyond writing code. The goal of this document is to provide a high-level overview of how you can get involved. + +## Asking Questions + +Have a question? Instead of opening an issue, please ask on [Discord](https://comfy.org/discord) or [Matrix](https://app.element.io/#/room/%23comfyui_space%3Amatrix.org) channels. Our team and the community will help you. + +## Providing Feedback + +Your comments and feedback are welcome, and the development team is available via a handful of different channels. + +See the `#bug-report`, `#feature-request` and `#feedback` channels on Discord. + +## Reporting Issues + +Have you identified a reproducible problem in ComfyUI? Do you have a feature request? We want to hear about it! Here's how you can report your issue as effectively as possible. + + +### Look For an Existing Issue + +Before you create a new issue, please do a search in [open issues](https://github.com/comfyanonymous/ComfyUI/issues) to see if the issue or feature request has already been filed. + +If you find your issue already exists, make relevant comments and add your [reaction](https://github.com/blog/2119-add-reactions-to-pull-requests-issues-and-comments). Use a reaction in place of a "+1" comment: + +* 👍 - upvote +* 👎 - downvote + +If you cannot find an existing issue that describes your bug or feature, create a new issue. We have an issue template in place to organize new issues. + + +### Creating Pull Requests + +* Please refer to the article on [creating pull requests](https://github.com/comfyanonymous/ComfyUI/wiki/How-to-Contribute-Code) and contributing to this project. + + +## Thank You + +Your contributions to open source, large or small, make great projects like this possible. Thank you for taking the time to contribute. From 0cd4a6a5e5101172a1496c337e67f15ad266fb98 Mon Sep 17 00:00:00 2001 From: YAN Wenkun Date: Tue, 2 Jul 2024 05:15:49 +0800 Subject: [PATCH 034/133] Fine-tuning GitHub Actions (#3169) * Bumping GitHub Actions versions * Using LZMA2 for 7zip compression in Windows packaging --- .github/workflows/windows_release_dependencies.yml | 6 +++--- .github/workflows/windows_release_nightly_pytorch.yml | 4 ++-- .github/workflows/windows_release_package.yml | 6 +++--- 3 files changed, 8 insertions(+), 8 deletions(-) diff --git a/.github/workflows/windows_release_dependencies.yml b/.github/workflows/windows_release_dependencies.yml index ffd3e2216..5aa57e7d7 100644 --- a/.github/workflows/windows_release_dependencies.yml +++ b/.github/workflows/windows_release_dependencies.yml @@ -33,8 +33,8 @@ jobs: build_dependencies: runs-on: windows-latest steps: - - uses: actions/checkout@v3 - - uses: actions/setup-python@v4 + - uses: actions/checkout@v4 + - uses: actions/setup-python@v5 with: python-version: 3.${{ inputs.python_minor }}.${{ inputs.python_patch }} @@ -58,7 +58,7 @@ jobs: mv temp_wheel_dir cu${{ inputs.cu }}_python_deps tar cf cu${{ inputs.cu }}_python_deps.tar cu${{ inputs.cu }}_python_deps - - uses: actions/cache/save@v3 + - uses: actions/cache/save@v4 with: path: | cu${{ inputs.cu }}_python_deps.tar diff --git a/.github/workflows/windows_release_nightly_pytorch.yml b/.github/workflows/windows_release_nightly_pytorch.yml index fa24a985c..d27c56b30 100644 --- a/.github/workflows/windows_release_nightly_pytorch.yml +++ b/.github/workflows/windows_release_nightly_pytorch.yml @@ -32,11 +32,11 @@ jobs: pull-requests: "read" runs-on: windows-latest steps: - - uses: actions/checkout@v3 + - uses: actions/checkout@v4 with: fetch-depth: 0 persist-credentials: false - - uses: actions/setup-python@v4 + - uses: actions/setup-python@v5 with: python-version: 3.${{ inputs.python_minor }}.${{ inputs.python_patch }} - shell: bash diff --git a/.github/workflows/windows_release_package.yml b/.github/workflows/windows_release_package.yml index 4e3cdabd2..020741c41 100644 --- a/.github/workflows/windows_release_package.yml +++ b/.github/workflows/windows_release_package.yml @@ -32,7 +32,7 @@ jobs: pull-requests: "read" runs-on: windows-latest steps: - - uses: actions/cache/restore@v3 + - uses: actions/cache/restore@v4 id: cache with: path: | @@ -48,7 +48,7 @@ jobs: pwd ls - - uses: actions/checkout@v3 + - uses: actions/checkout@v4 with: fetch-depth: 0 persist-credentials: false @@ -82,7 +82,7 @@ jobs: cd .. - "C:\Program Files\7-Zip\7z.exe" a -t7z -m0=lzma -mx=8 -mfb=64 -md=32m -ms=on -mf=BCJ2 ComfyUI_windows_portable.7z ComfyUI_windows_portable + "C:\Program Files\7-Zip\7z.exe" a -t7z -m0=lzma2 -mx=8 -mfb=64 -md=32m -ms=on -mf=BCJ2 ComfyUI_windows_portable.7z ComfyUI_windows_portable mv ComfyUI_windows_portable.7z ComfyUI/new_ComfyUI_windows_portable_nvidia_cu${{ inputs.cu }}_or_cpu.7z cd ComfyUI_windows_portable From 5dccfefe8d4ca9b33dfe6dfabcc6c666853c73b9 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Mon, 1 Jul 2024 17:17:25 -0400 Subject: [PATCH 035/133] Switch nightly pytorch standalone package to lzma2. --- .github/workflows/windows_release_nightly_pytorch.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/windows_release_nightly_pytorch.yml b/.github/workflows/windows_release_nightly_pytorch.yml index d27c56b30..e68011b64 100644 --- a/.github/workflows/windows_release_nightly_pytorch.yml +++ b/.github/workflows/windows_release_nightly_pytorch.yml @@ -73,7 +73,7 @@ jobs: pause" > ./update/update_comfyui_and_python_dependencies.bat cd .. - "C:\Program Files\7-Zip\7z.exe" a -t7z -m0=lzma -mx=8 -mfb=64 -md=32m -ms=on -mf=BCJ2 ComfyUI_windows_portable_nightly_pytorch.7z ComfyUI_windows_portable_nightly_pytorch + "C:\Program Files\7-Zip\7z.exe" a -t7z -m0=lzma2 -mx=8 -mfb=64 -md=32m -ms=on -mf=BCJ2 ComfyUI_windows_portable_nightly_pytorch.7z ComfyUI_windows_portable_nightly_pytorch mv ComfyUI_windows_portable_nightly_pytorch.7z ComfyUI/ComfyUI_windows_portable_nvidia_or_cpu_nightly_pytorch.7z cd ComfyUI_windows_portable_nightly_pytorch From 755c48d78ea2381b3554de729e36acfb381ebc67 Mon Sep 17 00:00:00 2001 From: Hayden Reeve <39004735+HaydenReeve@users.noreply.github.com> Date: Tue, 2 Jul 2024 05:21:12 +0800 Subject: [PATCH 036/133] Fix several typos in example_node.py.example (#3204) This change includes corrections for several spelling errors in the documentation of example_node.py.example file. These were previously raised by #3157, but they missed a few. --- custom_nodes/example_node.py.example | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/custom_nodes/example_node.py.example b/custom_nodes/example_node.py.example index f06632593..57c9cbedf 100644 --- a/custom_nodes/example_node.py.example +++ b/custom_nodes/example_node.py.example @@ -12,9 +12,9 @@ class Example: Attributes ---------- RETURN_TYPES (`tuple`): - The type of each element in the output tulple. + The type of each element in the output tuple. RETURN_NAMES (`tuple`): - Optional: The name of each output in the output tulple. + Optional: The name of each output in the output tuple. FUNCTION (`str`): The name of the entry-point method. For example, if `FUNCTION = "execute"` then it will run Example().execute() OUTPUT_NODE ([`bool`]): @@ -44,7 +44,7 @@ class Example: * Key field_name (`string`): Name of a entry-point method's argument * Value field_config (`tuple`): + First value is a string indicate the type of field or a list for selection. - + Secound value is a config for type "INT", "STRING" or "FLOAT". + + Second value is a config for type "INT", "STRING" or "FLOAT". """ return { "required": { @@ -61,7 +61,7 @@ class Example: "min": 0.0, "max": 10.0, "step": 0.01, - "round": 0.001, #The value represeting the precision to round to, will be set to the step value by default. Can be set to False to disable rounding. + "round": 0.001, #The value representing the precision to round to, will be set to the step value by default. Can be set to False to disable rounding. "display": "number"}), "print_to_screen": (["enable", "disable"],), "string_field": ("STRING", { From b82d67d5bfa9a1f8c6d0167bf871cbd151c1005f Mon Sep 17 00:00:00 2001 From: Peter Crabtree Date: Mon, 1 Jul 2024 17:42:17 -0400 Subject: [PATCH 037/133] Add SamplerEulerAncestralCFG++ custom sampler node (#3901) (for eta and s_noise) --- comfy_extras/nodes_custom_sampler.py | 24 ++++++++++++++++++++++++ 1 file changed, 24 insertions(+) diff --git a/comfy_extras/nodes_custom_sampler.py b/comfy_extras/nodes_custom_sampler.py index 69f1b9418..64a8c0631 100644 --- a/comfy_extras/nodes_custom_sampler.py +++ b/comfy_extras/nodes_custom_sampler.py @@ -293,6 +293,25 @@ class SamplerEulerAncestral: sampler = comfy.samplers.ksampler("euler_ancestral", {"eta": eta, "s_noise": s_noise}) return (sampler, ) +class SamplerEulerAncestralCFGPP: + @classmethod + def INPUT_TYPES(s): + return { + "required": { + "eta": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step":0.01, "round": False}), + "s_noise": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step":0.01, "round": False}), + }} + RETURN_TYPES = ("SAMPLER",) + CATEGORY = "sampling/custom_sampling/samplers" + + FUNCTION = "get_sampler" + + def get_sampler(self, eta, s_noise): + sampler = comfy.samplers.ksampler( + "euler_ancestral_cfg_pp", + {"eta": eta, "s_noise": s_noise}) + return (sampler, ) + class SamplerLMS: @classmethod def INPUT_TYPES(s): @@ -622,6 +641,7 @@ NODE_CLASS_MAPPINGS = { "SDTurboScheduler": SDTurboScheduler, "KSamplerSelect": KSamplerSelect, "SamplerEulerAncestral": SamplerEulerAncestral, + "SamplerEulerAncestralCFGPP": SamplerEulerAncestralCFGPP, "SamplerLMS": SamplerLMS, "SamplerDPMPP_3M_SDE": SamplerDPMPP_3M_SDE, "SamplerDPMPP_2M_SDE": SamplerDPMPP_2M_SDE, @@ -639,3 +659,7 @@ NODE_CLASS_MAPPINGS = { "AddNoise": AddNoise, "SamplerCustomAdvanced": SamplerCustomAdvanced, } + +NODE_DISPLAY_NAME_MAPPINGS = { + "SamplerEulerAncestralCFGPP": "SamplerEulerAncestralCFG++", +} \ No newline at end of file From 9dd549e253f0e2c5e6360f9349b0872af18d8962 Mon Sep 17 00:00:00 2001 From: Chenlei Hu Date: Mon, 1 Jul 2024 17:54:03 -0400 Subject: [PATCH 038/133] Add `--no-custom-node` cmd flag (#3903) * Add --no-custom-node cmd flag * nit --- comfy/cli_args.py | 1 + folder_paths.py | 8 +++++--- main.py | 13 +++++++++++-- nodes.py | 24 ++++++++++++++++++++---- 4 files changed, 37 insertions(+), 9 deletions(-) diff --git a/comfy/cli_args.py b/comfy/cli_args.py index fb0d37ce7..b72bf3998 100644 --- a/comfy/cli_args.py +++ b/comfy/cli_args.py @@ -118,6 +118,7 @@ parser.add_argument("--quick-test-for-ci", action="store_true", help="Quick test parser.add_argument("--windows-standalone-build", action="store_true", help="Windows standalone build: Enable convenient things that most people using the standalone windows build will probably enjoy (like auto opening the page on startup).") parser.add_argument("--disable-metadata", action="store_true", help="Disable saving prompt metadata in files.") +parser.add_argument("--disable-all-custom-nodes", action="store_true", help="Disable loading all custom nodes.") parser.add_argument("--multi-user", action="store_true", help="Enables per-user storage.") diff --git a/folder_paths.py b/folder_paths.py index 234b73409..2cf45f12a 100644 --- a/folder_paths.py +++ b/folder_paths.py @@ -2,9 +2,11 @@ import os import time import logging -supported_pt_extensions = set(['.ckpt', '.pt', '.bin', '.pth', '.safetensors', '.pkl']) +supported_pt_extensions: set[str] = set(['.ckpt', '.pt', '.bin', '.pth', '.safetensors', '.pkl']) -folder_names_and_paths = {} +SupportedFileExtensionsType = set[str] +ScanPathType = list[str] +folder_names_and_paths: dict[str, tuple[ScanPathType, SupportedFileExtensionsType]] = {} base_path = os.path.dirname(os.path.realpath(__file__)) models_dir = os.path.join(base_path, "models") @@ -26,7 +28,7 @@ folder_names_and_paths["gligen"] = ([os.path.join(models_dir, "gligen")], suppor folder_names_and_paths["upscale_models"] = ([os.path.join(models_dir, "upscale_models")], supported_pt_extensions) -folder_names_and_paths["custom_nodes"] = ([os.path.join(base_path, "custom_nodes")], []) +folder_names_and_paths["custom_nodes"] = ([os.path.join(base_path, "custom_nodes")], set()) folder_names_and_paths["hypernetworks"] = ([os.path.join(models_dir, "hypernetworks")], supported_pt_extensions) diff --git a/main.py b/main.py index a374f2b12..2957dd2ff 100644 --- a/main.py +++ b/main.py @@ -5,6 +5,8 @@ import os import importlib.util import folder_paths import time +from comfy.cli_args import args + def execute_prestartup_script(): def execute_script(script_path): @@ -18,6 +20,9 @@ def execute_prestartup_script(): print(f"Failed to execute startup-script: {script_path} / {e}") return False + if args.disable_all_custom_nodes: + return + node_paths = folder_paths.get_folder_paths("custom_nodes") for custom_node_path in node_paths: possible_modules = os.listdir(custom_node_path) @@ -76,7 +81,7 @@ import yaml import execution import server from server import BinaryEventTypes -from nodes import init_custom_nodes +from nodes import init_builtin_extra_nodes, init_external_custom_nodes import comfy.model_management def cuda_malloc_warning(): @@ -214,7 +219,11 @@ if __name__ == "__main__": for config_path in itertools.chain(*args.extra_model_paths_config): load_extra_path_config(config_path) - init_custom_nodes() + init_builtin_extra_nodes() + if not args.disable_all_custom_nodes: + init_external_custom_nodes() + else: + logging.info("Skipping loading of custom nodes") cuda_malloc_warning() diff --git a/nodes.py b/nodes.py index 04775d290..a0d2178f4 100644 --- a/nodes.py +++ b/nodes.py @@ -1925,7 +1925,16 @@ def load_custom_node(module_path, ignore=set()): logging.warning(f"Cannot import {module_path} module for custom nodes: {e}") return False -def load_custom_nodes(): +def init_external_custom_nodes(): + """ + Initializes the external custom nodes. + + This function loads custom nodes from the specified folder paths and imports them into the application. + It measures the import times for each custom node and logs the results. + + Returns: + None + """ base_node_names = set(NODE_CLASS_MAPPINGS.keys()) node_paths = folder_paths.get_folder_paths("custom_nodes") node_import_times = [] @@ -1952,7 +1961,16 @@ def load_custom_nodes(): logging.info("{:6.1f} seconds{}: {}".format(n[0], import_message, n[1])) logging.info("") -def init_custom_nodes(): +def init_builtin_extra_nodes(): + """ + Initializes the built-in extra nodes in ComfyUI. + + This function loads the extra node files located in the "comfy_extras" directory and imports them into ComfyUI. + If any of the extra node files fail to import, a warning message is logged. + + Returns: + None + """ extras_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), "comfy_extras") extras_files = [ "nodes_latent.py", @@ -1999,8 +2017,6 @@ def init_custom_nodes(): if not load_custom_node(os.path.join(extras_dir, node_file)): import_failed.append(node_file) - load_custom_nodes() - if len(import_failed) > 0: logging.warning("WARNING: some comfy_extras/ nodes did not import correctly. This may be because they are missing some dependencies.\n") for node in import_failed: From 1ef66b095586981633cd11906e6d2e555deab9f6 Mon Sep 17 00:00:00 2001 From: Bob Du Date: Tue, 2 Jul 2024 06:02:42 +0800 Subject: [PATCH 039/133] Add example for how to add custom API routes (#3597) --- custom_nodes/example_node.py.example | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/custom_nodes/example_node.py.example b/custom_nodes/example_node.py.example index 57c9cbedf..72ca3688c 100644 --- a/custom_nodes/example_node.py.example +++ b/custom_nodes/example_node.py.example @@ -106,6 +106,16 @@ class Example: # Set the web directory, any .js file in that directory will be loaded by the frontend as a frontend extension # WEB_DIRECTORY = "./somejs" + +# Add custom API routes, using router +from aiohttp import web +from server import PromptServer + +@PromptServer.instance.routes.get("/hello") +async def get_hello(request): + return web.json_response("hello") + + # A dictionary that contains all nodes you want to export with their names # NOTE: names should be globally unique NODE_CLASS_MAPPINGS = { From 52aaee251fcd87b7c554f4e9c1386b184236f81f Mon Sep 17 00:00:00 2001 From: shawnington <88048838+shawnington@users.noreply.github.com> Date: Tue, 2 Jul 2024 01:30:33 -0400 Subject: [PATCH 040/133] Fix to #3465. Prevent, resaving of duplicate images if overwrite not specified (#3472) * Fix to #3465. Prevent the, resaving of duplicate images if overwrite not specified This is a fix to #3465 Adds function compare_image_hash to do a sha256 hash comparison between an uploaded image and existing images with matching file names. This changes the behavior so that only images having the same filename that are actually different are saved to input, existing images are instead now opened instead of resaved with increment. Currently, exact duplicates with the same filename are resave saved with an incremented filename in the format: (n).ext with the code: ``` while os.path.exists(filepath): filename = f"{split[0]} ({i}){split[1]}" filepath = os.path.join(full_output_folder, filename) i += 1 ``` This commit changes this to: ``` while os.path.exists(filepath): if compare_image_hash(filepath, image): image_is_duplicate = True break filename = f"{split[0]} ({i}){split[1]}" filepath = os.path.join(full_output_folder, filename) i += 1 ``` a check for if image_is_duplicate = False is done before saving the file. Currently, if you load the same image of a cat named cat.jpg into the LoadImage node 3 times, you will get 3 new files in your input folder with incremented file names. With this change, you will now only have the single copy of cat.jpg, that will be re-opened instead of re-saved. However if you load 3 different images of cats named cat.jpg, you will get the expected behavior of having: cat.jpg cat (1).jpg cat (2).jpg This saves space and clutter. After checking my own input folder, I have 800+ images that are duplicates that were resaved with incremented file names amounting to more than 5GB of duplicated data. * fixed typo in expression --- server.py | 31 +++++++++++++++++++++++++------ 1 file changed, 25 insertions(+), 6 deletions(-) diff --git a/server.py b/server.py index 30ea90c6c..5b98620ad 100644 --- a/server.py +++ b/server.py @@ -12,6 +12,7 @@ import json import glob import struct import ssl +import hashlib from PIL import Image, ImageOps from PIL.PngImagePlugin import PngInfo from io import BytesIO @@ -153,10 +154,24 @@ class PromptServer(): type_dir = folder_paths.get_output_directory() return type_dir, dir_type - + + def compare_image_hash(filepath, image): + # function to compare hashes of two images to see if it already exists, fix to #3465 + if os.path.exists(filepath): + a = hashlib.sha256() + b = hashlib.sha256() + with open(filepath, "rb") as f: + a.update(f.read()) + b.update(image.file.read()) + image.file.seek(0) + f.close() + return a.hexdigest() == b.hexdigest() + return False + def image_upload(post, image_save_function=None): image = post.get("image") overwrite = post.get("overwrite") + image_is_duplicate = False image_upload_type = post.get("type") upload_dir, image_upload_type = get_dir_by_type(image_upload_type) @@ -183,15 +198,19 @@ class PromptServer(): else: i = 1 while os.path.exists(filepath): + if compare_image_hash(filepath, image): #compare hash to prevent saving of duplicates with same name, fix for #3465 + image_is_duplicate = True + break filename = f"{split[0]} ({i}){split[1]}" filepath = os.path.join(full_output_folder, filename) i += 1 - if image_save_function is not None: - image_save_function(image, post, filepath) - else: - with open(filepath, "wb") as f: - f.write(image.file.read()) + if not image_is_duplicate: + if image_save_function is not None: + image_save_function(image, post, filepath) + else: + with open(filepath, "wb") as f: + f.write(image.file.read()) return web.json_response({"name" : filename, "subfolder": subfolder, "type": image_upload_type}) else: From 2f03201690e0fb8a3ec551a125b20d89c9019a02 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Tue, 2 Jul 2024 01:32:23 -0400 Subject: [PATCH 041/133] Remove some empty lines. --- server.py | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/server.py b/server.py index 5b98620ad..38b1bab80 100644 --- a/server.py +++ b/server.py @@ -111,7 +111,7 @@ class PromptServer(): # On reconnect if we are the currently executing client send the current node if self.client_id == sid and self.last_node_id is not None: await self.send("executing", { "node": self.last_node_id }, sid) - + async for msg in ws: if msg.type == aiohttp.WSMsgType.ERROR: logging.warning('ws connection closed with exception %s' % ws.exception()) @@ -132,9 +132,9 @@ class PromptServer(): async def get_extensions(request): files = glob.glob(os.path.join( glob.escape(self.web_root), 'extensions/**/*.js'), recursive=True) - + extensions = list(map(lambda f: "/" + os.path.relpath(f, self.web_root).replace("\\", "/"), files)) - + for name, dir in nodes.EXTENSION_WEB_DIRS.items(): files = glob.glob(os.path.join(glob.escape(dir), '**/*.js'), recursive=True) extensions.extend(list(map(lambda f: "/extensions/" + urllib.parse.quote( @@ -154,7 +154,7 @@ class PromptServer(): type_dir = folder_paths.get_output_directory() return type_dir, dir_type - + def compare_image_hash(filepath, image): # function to compare hashes of two images to see if it already exists, fix to #3465 if os.path.exists(filepath): @@ -167,7 +167,7 @@ class PromptServer(): f.close() return a.hexdigest() == b.hexdigest() return False - + def image_upload(post, image_save_function=None): image = post.get("image") overwrite = post.get("overwrite") @@ -205,7 +205,7 @@ class PromptServer(): filepath = os.path.join(full_output_folder, filename) i += 1 - if not image_is_duplicate: + if not image_is_duplicate: if image_save_function is not None: image_save_function(image, post, filepath) else: From 01991f72ce1bdce31ff4bd6fc2fa64454b1526ad Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Tue, 2 Jul 2024 12:21:08 -0400 Subject: [PATCH 042/133] Fix SamplerEulerCFGpp node. --- comfy_extras/nodes_advanced_samplers.py | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/comfy_extras/nodes_advanced_samplers.py b/comfy_extras/nodes_advanced_samplers.py index cee3a10c4..820c250ef 100644 --- a/comfy_extras/nodes_advanced_samplers.py +++ b/comfy_extras/nodes_advanced_samplers.py @@ -60,7 +60,7 @@ from comfy.k_diffusion.sampling import to_d import comfy.model_patcher @torch.no_grad() -def sample_euler_cfgpp(model, x, sigmas, extra_args=None, callback=None, disable=None): +def sample_euler_pp(model, x, sigmas, extra_args=None, callback=None, disable=None): extra_args = {} if extra_args is None else extra_args temp = [0] @@ -75,11 +75,11 @@ def sample_euler_cfgpp(model, x, sigmas, extra_args=None, callback=None, disable for i in trange(len(sigmas) - 1, disable=disable): sigma_hat = sigmas[i] denoised = model(x, sigma_hat * s_in, **extra_args) - d = to_d(x, sigma_hat, temp[0]) + d = to_d(x - denoised + temp[0], sigmas[i], denoised) if callback is not None: callback({'x': x, 'i': i, 'sigma': sigmas[i], 'sigma_hat': sigma_hat, 'denoised': denoised}) dt = sigmas[i + 1] - sigma_hat - x = denoised + sigmas[i + 1] * d + x = x + d * dt return x @@ -96,10 +96,10 @@ class SamplerEulerCFGpp: FUNCTION = "get_sampler" def get_sampler(self, version): - if version == "regular": - sampler = comfy.samplers.KSAMPLER(sample_euler_cfgpp) + if version == "alternative": + sampler = comfy.samplers.KSAMPLER(sample_euler_pp) else: - sampler = comfy.samplers.ksampler("euler_pp") + sampler = comfy.samplers.ksampler("euler_cfg_pp") return (sampler, ) NODE_CLASS_MAPPINGS = { From 3f46362d227fa0ca578a69aeb194951b9f87aea0 Mon Sep 17 00:00:00 2001 From: "Alex \"mcmonkey\" Goodwin" <4000772+mcmonkey4eva@users.noreply.github.com> Date: Tue, 2 Jul 2024 17:16:33 -0700 Subject: [PATCH 043/133] fix non-contiguous tensor saving (from channels-last) (#3932) --- comfy/sd.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/comfy/sd.py b/comfy/sd.py index dda0887ba..b28bfe358 100644 --- a/comfy/sd.py +++ b/comfy/sd.py @@ -627,5 +627,7 @@ def save_checkpoint(output_path, model, clip=None, vae=None, clip_vision=None, m sd = model.model.state_dict_for_saving(clip_sd, vae.get_sd(), clip_vision_sd) for k in extra_keys: sd[k] = extra_keys[k] + for k in sd: + sd[k] = sd[k].contiguous() comfy.utils.save_torch_file(sd, output_path, metadata=metadata) From 537f35c7bc76e611b53102d3b5a2926e46ec7362 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Tue, 2 Jul 2024 20:21:51 -0400 Subject: [PATCH 044/133] Don't update dict if contiguous. --- comfy/sd.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/comfy/sd.py b/comfy/sd.py index b28bfe358..4ba00a62c 100644 --- a/comfy/sd.py +++ b/comfy/sd.py @@ -627,7 +627,10 @@ def save_checkpoint(output_path, model, clip=None, vae=None, clip_vision=None, m sd = model.model.state_dict_for_saving(clip_sd, vae.get_sd(), clip_vision_sd) for k in extra_keys: sd[k] = extra_keys[k] + for k in sd: - sd[k] = sd[k].contiguous() + t = sd[k] + if not t.is_contiguous(): + sd[k] = t.contiguous() comfy.utils.save_torch_file(sd, output_path, metadata=metadata) From d7484ef30c97c077dde1c7ae07a16689bec86dd3 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Wed, 3 Jul 2024 11:34:32 -0400 Subject: [PATCH 045/133] Support loading checkpoints with the UNETLoader node. --- comfy/sd.py | 24 ++++++++++++++++-------- 1 file changed, 16 insertions(+), 8 deletions(-) diff --git a/comfy/sd.py b/comfy/sd.py index 4ba00a62c..e343e1fa8 100644 --- a/comfy/sd.py +++ b/comfy/sd.py @@ -563,24 +563,32 @@ def load_checkpoint_guess_config(ckpt_path, output_vae=True, output_clip=True, o return (model_patcher, clip, vae, clipvision) -def load_unet_state_dict(sd): #load unet in diffusers format +def load_unet_state_dict(sd): #load unet in diffusers or regular format + + #Allow loading unets from checkpoint files + checkpoint = False + diffusion_model_prefix = model_detection.unet_prefix_from_state_dict(sd) + temp_sd = comfy.utils.state_dict_prefix_replace(sd, {diffusion_model_prefix: ""}, filter_keys=True) + if len(temp_sd) > 0: + sd = temp_sd + checkpoint = True + parameters = comfy.utils.calculate_parameters(sd) unet_dtype = model_management.unet_dtype(model_params=parameters) load_device = model_management.get_torch_device() - if 'transformer_blocks.0.attn.add_q_proj.weight' in sd: #MMDIT SD3 + if checkpoint or "input_blocks.0.0.weight" in sd or 'clf.1.weight' in sd: #ldm or stable cascade + model_config = model_detection.model_config_from_unet(sd, "") + if model_config is None: + return None + new_sd = sd + elif 'transformer_blocks.0.attn.add_q_proj.weight' in sd: #MMDIT SD3 new_sd = model_detection.convert_diffusers_mmdit(sd, "") if new_sd is None: return None model_config = model_detection.model_config_from_unet(new_sd, "") if model_config is None: return None - elif "input_blocks.0.0.weight" in sd or 'clf.1.weight' in sd: #ldm or stable cascade - model_config = model_detection.model_config_from_unet(sd, "") - if model_config is None: - return None - new_sd = sd - else: #diffusers model_config = model_detection.model_config_from_diffusers_unet(sd) if model_config is None: From 086ac75228af3fea96be58ec45c2f6c17286e75d Mon Sep 17 00:00:00 2001 From: Chenlei Hu Date: Wed, 3 Jul 2024 19:31:46 -0400 Subject: [PATCH 046/133] 3.8 Compatible type annotation (#3938) --- folder_paths.py | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/folder_paths.py b/folder_paths.py index 2cf45f12a..2baf8ce1c 100644 --- a/folder_paths.py +++ b/folder_paths.py @@ -1,12 +1,13 @@ import os import time import logging +from typing import Set, List, Dict, Tuple -supported_pt_extensions: set[str] = set(['.ckpt', '.pt', '.bin', '.pth', '.safetensors', '.pkl']) +supported_pt_extensions: Set[str] = set(['.ckpt', '.pt', '.bin', '.pth', '.safetensors', '.pkl']) -SupportedFileExtensionsType = set[str] -ScanPathType = list[str] -folder_names_and_paths: dict[str, tuple[ScanPathType, SupportedFileExtensionsType]] = {} +SupportedFileExtensionsType = Set[str] +ScanPathType = List[str] +folder_names_and_paths: Dict[str, Tuple[ScanPathType, SupportedFileExtensionsType]] = {} base_path = os.path.dirname(os.path.realpath(__file__)) models_dir = os.path.join(base_path, "models") From 24b969d3dace581ed3fb547eedfbdf502ad0f7e9 Mon Sep 17 00:00:00 2001 From: bymyself Date: Wed, 3 Jul 2024 17:30:07 -0700 Subject: [PATCH 047/133] Skip state check hook on first load (#3915) --- web/scripts/changeTracker.js | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/web/scripts/changeTracker.js b/web/scripts/changeTracker.js index 041c83122..39bc4a810 100644 --- a/web/scripts/changeTracker.js +++ b/web/scripts/changeTracker.js @@ -173,9 +173,11 @@ export class ChangeTracker { const onNodeAdded = LiteGraph.LGraph.prototype.onNodeAdded; LiteGraph.LGraph.prototype.onNodeAdded = function () { const v = onNodeAdded?.apply(this, arguments); - const ct = changeTracker(); - if (!ct.isOurLoad) { - ct.checkState(); + if (!app?.configuringGraph) { + const ct = changeTracker(); + if (!ct.isOurLoad) { + ct.checkState(); + } } return v; }; From 739b76630e0298561c39d0d3341bc2856e55d995 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Thu, 4 Jul 2024 15:14:13 -0400 Subject: [PATCH 048/133] Remove useless code. --- comfy/cldm/mmdit.py | 9 --------- 1 file changed, 9 deletions(-) diff --git a/comfy/cldm/mmdit.py b/comfy/cldm/mmdit.py index ee0282bc7..025c2fb5d 100644 --- a/comfy/cldm/mmdit.py +++ b/comfy/cldm/mmdit.py @@ -56,15 +56,6 @@ class ControlNet(comfy.ldm.modules.diffusionmodules.mmdit.MMDiT): if context is not None: context = self.context_embedder(context) - if self.register_length > 0: - context = torch.cat( - ( - repeat(self.register, "1 ... -> b ...", b=x.shape[0]), - default(context, torch.Tensor([]).type_as(x)), - ), - 1, - ) - output = [] blocks = len(self.joint_blocks) From 0e3dfd9e343d4aee7826fbc188e2af8ceb1bdde9 Mon Sep 17 00:00:00 2001 From: Chenlei Hu Date: Thu, 4 Jul 2024 20:49:07 -0400 Subject: [PATCH 049/133] Use relative path for custom/extra node module name (#3944) * Fix module name for comfy extra nodes * Use module name relative to root dir --- nodes.py | 30 ++++++++++++++++++++++++++---- 1 file changed, 26 insertions(+), 4 deletions(-) diff --git a/nodes.py b/nodes.py index a0d2178f4..81efecf65 100644 --- a/nodes.py +++ b/nodes.py @@ -1887,11 +1887,33 @@ NODE_DISPLAY_NAME_MAPPINGS = { EXTENSION_WEB_DIRS = {} -def load_custom_node(module_path, ignore=set()): - module_name = os.path.basename(module_path) + +def get_module_name(module_path: str) -> str: + """ + Returns the module name based on the given module path. + Examples: + get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node.py") -> "custom_nodes.my_custom_node" + get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node") -> "custom_nodes.my_custom_node" + get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node/") -> "custom_nodes.my_custom_node" + get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node/__init__.py") -> "custom_nodes.my_custom_node" + get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node/__init__") -> "custom_nodes.my_custom_node" + get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node/__init__/") -> "custom_nodes.my_custom_node" + get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node.disabled") -> "custom_nodes.my + + Args: + module_path (str): The path of the module. + + Returns: + str: The module name. + """ + relative_path = os.path.relpath(module_path, folder_paths.base_path) if os.path.isfile(module_path): - sp = os.path.splitext(module_path) - module_name = sp[0] + relative_path = os.path.splitext(relative_path)[0] + return relative_path.replace(os.sep, '.') + + +def load_custom_node(module_path, ignore=set()): + module_name = get_module_name(module_path) try: logging.debug("Trying to load custom node {}".format(module_path)) if os.path.isfile(module_path): From 720b17442d39b5991e1d3c336f9d16a0f75c929c Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Thu, 4 Jul 2024 21:09:05 -0400 Subject: [PATCH 050/133] Temporary revert. --- nodes.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nodes.py b/nodes.py index 81efecf65..03544be02 100644 --- a/nodes.py +++ b/nodes.py @@ -1913,7 +1913,7 @@ def get_module_name(module_path: str) -> str: def load_custom_node(module_path, ignore=set()): - module_name = get_module_name(module_path) + module_name = os.path.basename(module_path) try: logging.debug("Trying to load custom node {}".format(module_path)) if os.path.isfile(module_path): From bd2d3e27d786b89e9ef89d6eb083e94172126306 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Thu, 4 Jul 2024 21:43:23 -0400 Subject: [PATCH 051/133] Show comfy_extras warning at the end. Remove code. --- main.py | 8 ++------ nodes.py | 35 +++++++++++------------------------ 2 files changed, 13 insertions(+), 30 deletions(-) diff --git a/main.py b/main.py index 2957dd2ff..9650703a8 100644 --- a/main.py +++ b/main.py @@ -81,7 +81,7 @@ import yaml import execution import server from server import BinaryEventTypes -from nodes import init_builtin_extra_nodes, init_external_custom_nodes +import nodes import comfy.model_management def cuda_malloc_warning(): @@ -219,11 +219,7 @@ if __name__ == "__main__": for config_path in itertools.chain(*args.extra_model_paths_config): load_extra_path_config(config_path) - init_builtin_extra_nodes() - if not args.disable_all_custom_nodes: - init_external_custom_nodes() - else: - logging.info("Skipping loading of custom nodes") + nodes.init_extra_nodes(init_custom_nodes=not args.disable_all_custom_nodes) cuda_malloc_warning() diff --git a/nodes.py b/nodes.py index 03544be02..8f8abb494 100644 --- a/nodes.py +++ b/nodes.py @@ -1888,30 +1888,6 @@ NODE_DISPLAY_NAME_MAPPINGS = { EXTENSION_WEB_DIRS = {} -def get_module_name(module_path: str) -> str: - """ - Returns the module name based on the given module path. - Examples: - get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node.py") -> "custom_nodes.my_custom_node" - get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node") -> "custom_nodes.my_custom_node" - get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node/") -> "custom_nodes.my_custom_node" - get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node/__init__.py") -> "custom_nodes.my_custom_node" - get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node/__init__") -> "custom_nodes.my_custom_node" - get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node/__init__/") -> "custom_nodes.my_custom_node" - get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node.disabled") -> "custom_nodes.my - - Args: - module_path (str): The path of the module. - - Returns: - str: The module name. - """ - relative_path = os.path.relpath(module_path, folder_paths.base_path) - if os.path.isfile(module_path): - relative_path = os.path.splitext(relative_path)[0] - return relative_path.replace(os.sep, '.') - - def load_custom_node(module_path, ignore=set()): module_name = os.path.basename(module_path) try: @@ -2039,6 +2015,17 @@ def init_builtin_extra_nodes(): if not load_custom_node(os.path.join(extras_dir, node_file)): import_failed.append(node_file) + return import_failed + + +def init_extra_nodes(init_custom_nodes=True): + import_failed = init_external_custom_nodes() + + if init_custom_nodes: + init_external_custom_nodes() + else: + logging.info("Skipping loading of custom nodes") + if len(import_failed) > 0: logging.warning("WARNING: some comfy_extras/ nodes did not import correctly. This may be because they are missing some dependencies.\n") for node in import_failed: From cedbc94cc0551cfdeae01c48b922d546c816f898 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Thu, 4 Jul 2024 21:49:50 -0400 Subject: [PATCH 052/133] Forgot this in last commit. --- nodes.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/nodes.py b/nodes.py index 8f8abb494..9c541eba8 100644 --- a/nodes.py +++ b/nodes.py @@ -1890,6 +1890,9 @@ EXTENSION_WEB_DIRS = {} def load_custom_node(module_path, ignore=set()): module_name = os.path.basename(module_path) + if os.path.isfile(module_path): + sp = os.path.splitext(module_path) + module_name = sp[0] try: logging.debug("Trying to load custom node {}".format(module_path)) if os.path.isfile(module_path): @@ -2019,7 +2022,7 @@ def init_builtin_extra_nodes(): def init_extra_nodes(init_custom_nodes=True): - import_failed = init_external_custom_nodes() + import_failed = init_builtin_extra_nodes() if init_custom_nodes: init_external_custom_nodes() From 1dc87df4c5f4925f8eb286236e71c9dd38941dd6 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Thu, 4 Jul 2024 22:03:37 -0400 Subject: [PATCH 053/133] Readme changes. --- README.md | 9 ++++----- 1 file changed, 4 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 2ce7c3e6b..35e3238a1 100644 --- a/README.md +++ b/README.md @@ -225,12 +225,11 @@ Use `--tls-keyfile key.pem --tls-certfile cert.pem` to enable TLS/SSL, the app w [Matrix space: #comfyui_space:matrix.org](https://app.element.io/#/room/%23comfyui_space%3Amatrix.org) (it's like discord but open source). +See also: [https://www.comfy.org/](https://www.comfy.org/) + # QA -### Why did you make this? +### Which GPU should I buy for this? -I wanted to learn how Stable Diffusion worked in detail. I also wanted something clean and powerful that would let me experiment with SD without restrictions. +[See this page for some recommendations](https://github.com/comfyanonymous/ComfyUI/wiki/Which-GPU-should-I-buy-for-ComfyUI) -### Who is this for? - -This is for anyone that wants to make complex workflows with SD or that wants to learn more how SD works. The interface follows closely how SD works and the code should be much more simple to understand than other SD UIs. From b4c2d03d476f97d9d91c0d7d0af7fde382084385 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Fri, 5 Jul 2024 12:10:22 -0400 Subject: [PATCH 054/133] Remove duplicate import. --- main.py | 1 - 1 file changed, 1 deletion(-) diff --git a/main.py b/main.py index 9650703a8..196351a3d 100644 --- a/main.py +++ b/main.py @@ -58,7 +58,6 @@ import shutil import threading import gc -from comfy.cli_args import args import logging if os.name == "nt": From ce649d61c05ab0e905155b4a010d4f0459a0db8d Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Fri, 5 Jul 2024 23:48:17 -0400 Subject: [PATCH 055/133] Allow zeroing out of embeds with unused attention mask. --- comfy/sd1_clip.py | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/comfy/sd1_clip.py b/comfy/sd1_clip.py index 78e556b56..3b812b44c 100644 --- a/comfy/sd1_clip.py +++ b/comfy/sd1_clip.py @@ -169,7 +169,7 @@ class SDClipModel(torch.nn.Module, ClipTokenWeightEncoder): tokens = torch.LongTensor(tokens).to(device) attention_mask = None - if self.enable_attention_masks: + if self.enable_attention_masks or self.zero_out_masked: attention_mask = torch.zeros_like(tokens) end_token = self.special_tokens.get("end", -1) for x in range(attention_mask.shape[0]): @@ -178,7 +178,11 @@ class SDClipModel(torch.nn.Module, ClipTokenWeightEncoder): if tokens[x, y] == end_token: break - outputs = self.transformer(tokens, attention_mask, intermediate_output=self.layer_idx, final_layer_norm_intermediate=self.layer_norm_hidden_state) + attention_mask_model = None + if self.enable_attention_masks: + attention_mask_model = attention_mask + + outputs = self.transformer(tokens, attention_mask_model, intermediate_output=self.layer_idx, final_layer_norm_intermediate=self.layer_norm_hidden_state) self.transformer.set_input_embeddings(backup_embeds) if self.layer == "last": @@ -186,7 +190,7 @@ class SDClipModel(torch.nn.Module, ClipTokenWeightEncoder): else: z = outputs[1].float() - if self.zero_out_masked and attention_mask is not None: + if self.zero_out_masked: z *= attention_mask.unsqueeze(-1).float() pooled_output = None From 80c45909985aa37e6803ed59b6753fc289ee365f Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Sat, 6 Jul 2024 00:06:49 -0400 Subject: [PATCH 056/133] Allow specifying the padding token for the tokenizer. --- comfy/sd1_clip.py | 20 ++++++++++++-------- 1 file changed, 12 insertions(+), 8 deletions(-) diff --git a/comfy/sd1_clip.py b/comfy/sd1_clip.py index 3b812b44c..ed3dc2298 100644 --- a/comfy/sd1_clip.py +++ b/comfy/sd1_clip.py @@ -364,7 +364,7 @@ def load_embed(embedding_name, embedding_directory, embedding_size, embed_key=No return embed_out class SDTokenizer: - def __init__(self, tokenizer_path=None, max_length=77, pad_with_end=True, embedding_directory=None, embedding_size=768, embedding_key='clip_l', tokenizer_class=CLIPTokenizer, has_start_token=True, pad_to_max_length=True, min_length=None): + def __init__(self, tokenizer_path=None, max_length=77, pad_with_end=True, embedding_directory=None, embedding_size=768, embedding_key='clip_l', tokenizer_class=CLIPTokenizer, has_start_token=True, pad_to_max_length=True, min_length=None, pad_token=None): if tokenizer_path is None: tokenizer_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "sd1_tokenizer") self.tokenizer = tokenizer_class.from_pretrained(tokenizer_path) @@ -380,6 +380,14 @@ class SDTokenizer: self.tokens_start = 0 self.start_token = None self.end_token = empty[0] + + if pad_token is not None: + self.pad_token = pad_token + elif pad_with_end: + self.pad_token = self.end_token + else: + self.pad_token = 0 + self.pad_with_end = pad_with_end self.pad_to_max_length = pad_to_max_length @@ -412,10 +420,6 @@ class SDTokenizer: Word id values are unique per word and embedding, where the id 0 is reserved for non word tokens. Returned list has the dimensions NxM where M is the input size of CLIP ''' - if self.pad_with_end: - pad_token = self.end_token - else: - pad_token = 0 text = escape_important(text) parsed_weights = token_weights(text, 1.0) @@ -467,7 +471,7 @@ class SDTokenizer: else: batch.append((self.end_token, 1.0, 0)) if self.pad_to_max_length: - batch.extend([(pad_token, 1.0, 0)] * (remaining_length)) + batch.extend([(self.pad_token, 1.0, 0)] * (remaining_length)) #start new batch batch = [] if self.start_token is not None: @@ -480,9 +484,9 @@ class SDTokenizer: #fill last batch batch.append((self.end_token, 1.0, 0)) if self.pad_to_max_length: - batch.extend([(pad_token, 1.0, 0)] * (self.max_length - len(batch))) + batch.extend([(self.pad_token, 1.0, 0)] * (self.max_length - len(batch))) if self.min_length is not None and len(batch) < self.min_length: - batch.extend([(pad_token, 1.0, 0)] * (self.min_length - len(batch))) + batch.extend([(self.pad_token, 1.0, 0)] * (self.min_length - len(batch))) if not return_word_ids: batched_tokens = [[(t, w) for t, w,_ in x] for x in batched_tokens] From b8e58a939463be85877c1244ee00763368723c07 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Sat, 6 Jul 2024 00:33:25 -0400 Subject: [PATCH 057/133] Cleanup T5 code a bit. --- comfy/t5.py | 35 +++++++++++++++++++++-------------- comfy/t5_config_base.json | 1 + comfy/t5_config_xxl.json | 1 + 3 files changed, 23 insertions(+), 14 deletions(-) diff --git a/comfy/t5.py b/comfy/t5.py index 06dfe4766..d00b560a3 100644 --- a/comfy/t5.py +++ b/comfy/t5.py @@ -13,29 +13,36 @@ class T5LayerNorm(torch.nn.Module): x = x * torch.rsqrt(variance + self.variance_epsilon) return self.weight.to(device=x.device, dtype=x.dtype) * x +activations = { + "gelu_pytorch_tanh": lambda a: torch.nn.functional.gelu(a, approximate="tanh"), + "relu": torch.nn.functional.relu, +} + class T5DenseActDense(torch.nn.Module): - def __init__(self, model_dim, ff_dim, dtype, device, operations): + def __init__(self, model_dim, ff_dim, ff_activation, dtype, device, operations): super().__init__() self.wi = operations.Linear(model_dim, ff_dim, bias=False, dtype=dtype, device=device) self.wo = operations.Linear(ff_dim, model_dim, bias=False, dtype=dtype, device=device) # self.dropout = nn.Dropout(config.dropout_rate) + self.act = activations[ff_activation] def forward(self, x): - x = torch.nn.functional.relu(self.wi(x)) + x = self.act(self.wi(x)) # x = self.dropout(x) x = self.wo(x) return x class T5DenseGatedActDense(torch.nn.Module): - def __init__(self, model_dim, ff_dim, dtype, device, operations): + def __init__(self, model_dim, ff_dim, ff_activation, dtype, device, operations): super().__init__() self.wi_0 = operations.Linear(model_dim, ff_dim, bias=False, dtype=dtype, device=device) self.wi_1 = operations.Linear(model_dim, ff_dim, bias=False, dtype=dtype, device=device) self.wo = operations.Linear(ff_dim, model_dim, bias=False, dtype=dtype, device=device) # self.dropout = nn.Dropout(config.dropout_rate) + self.act = activations[ff_activation] def forward(self, x): - hidden_gelu = torch.nn.functional.gelu(self.wi_0(x), approximate="tanh") + hidden_gelu = self.act(self.wi_0(x)) hidden_linear = self.wi_1(x) x = hidden_gelu * hidden_linear # x = self.dropout(x) @@ -43,12 +50,12 @@ class T5DenseGatedActDense(torch.nn.Module): return x class T5LayerFF(torch.nn.Module): - def __init__(self, model_dim, ff_dim, ff_activation, dtype, device, operations): + def __init__(self, model_dim, ff_dim, ff_activation, gated_act, dtype, device, operations): super().__init__() - if ff_activation == "gelu_pytorch_tanh": - self.DenseReluDense = T5DenseGatedActDense(model_dim, ff_dim, dtype, device, operations) - elif ff_activation == "relu": - self.DenseReluDense = T5DenseActDense(model_dim, ff_dim, dtype, device, operations) + if gated_act: + self.DenseReluDense = T5DenseGatedActDense(model_dim, ff_dim, ff_activation, dtype, device, operations) + else: + self.DenseReluDense = T5DenseActDense(model_dim, ff_dim, ff_activation, dtype, device, operations) self.layer_norm = T5LayerNorm(model_dim, dtype=dtype, device=device, operations=operations) # self.dropout = nn.Dropout(config.dropout_rate) @@ -171,11 +178,11 @@ class T5LayerSelfAttention(torch.nn.Module): return x, past_bias class T5Block(torch.nn.Module): - def __init__(self, model_dim, inner_dim, ff_dim, ff_activation, num_heads, relative_attention_bias, dtype, device, operations): + def __init__(self, model_dim, inner_dim, ff_dim, ff_activation, gated_act, num_heads, relative_attention_bias, dtype, device, operations): super().__init__() self.layer = torch.nn.ModuleList() self.layer.append(T5LayerSelfAttention(model_dim, inner_dim, ff_dim, num_heads, relative_attention_bias, dtype, device, operations)) - self.layer.append(T5LayerFF(model_dim, ff_dim, ff_activation, dtype, device, operations)) + self.layer.append(T5LayerFF(model_dim, ff_dim, ff_activation, gated_act, dtype, device, operations)) def forward(self, x, mask=None, past_bias=None, optimized_attention=None): x, past_bias = self.layer[0](x, mask, past_bias, optimized_attention) @@ -183,11 +190,11 @@ class T5Block(torch.nn.Module): return x, past_bias class T5Stack(torch.nn.Module): - def __init__(self, num_layers, model_dim, inner_dim, ff_dim, ff_activation, num_heads, dtype, device, operations): + def __init__(self, num_layers, model_dim, inner_dim, ff_dim, ff_activation, gated_act, num_heads, dtype, device, operations): super().__init__() self.block = torch.nn.ModuleList( - [T5Block(model_dim, inner_dim, ff_dim, ff_activation, num_heads, relative_attention_bias=(i == 0), dtype=dtype, device=device, operations=operations) for i in range(num_layers)] + [T5Block(model_dim, inner_dim, ff_dim, ff_activation, gated_act, num_heads, relative_attention_bias=(i == 0), dtype=dtype, device=device, operations=operations) for i in range(num_layers)] ) self.final_layer_norm = T5LayerNorm(model_dim, dtype=dtype, device=device, operations=operations) # self.dropout = nn.Dropout(config.dropout_rate) @@ -216,7 +223,7 @@ class T5(torch.nn.Module): self.num_layers = config_dict["num_layers"] model_dim = config_dict["d_model"] - self.encoder = T5Stack(self.num_layers, model_dim, model_dim, config_dict["d_ff"], config_dict["dense_act_fn"], config_dict["num_heads"], dtype, device, operations) + self.encoder = T5Stack(self.num_layers, model_dim, model_dim, config_dict["d_ff"], config_dict["dense_act_fn"], config_dict["is_gated_act"], config_dict["num_heads"], dtype, device, operations) self.dtype = dtype self.shared = torch.nn.Embedding(config_dict["vocab_size"], model_dim, device=device) diff --git a/comfy/t5_config_base.json b/comfy/t5_config_base.json index facd85ef3..71f68327c 100644 --- a/comfy/t5_config_base.json +++ b/comfy/t5_config_base.json @@ -8,6 +8,7 @@ "dense_act_fn": "relu", "initializer_factor": 1.0, "is_encoder_decoder": true, + "is_gated_act": false, "layer_norm_epsilon": 1e-06, "model_type": "t5", "num_decoder_layers": 12, diff --git a/comfy/t5_config_xxl.json b/comfy/t5_config_xxl.json index bf4feadcf..28283b51a 100644 --- a/comfy/t5_config_xxl.json +++ b/comfy/t5_config_xxl.json @@ -8,6 +8,7 @@ "dense_act_fn": "gelu_pytorch_tanh", "initializer_factor": 1.0, "is_encoder_decoder": true, + "is_gated_act": true, "layer_norm_epsilon": 1e-06, "model_type": "t5", "num_decoder_layers": 24, From 404049114913f1a134656769a538779d7c927249 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Sat, 6 Jul 2024 00:53:33 -0400 Subject: [PATCH 058/133] Better T5xxl detection. --- comfy/sd.py | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/comfy/sd.py b/comfy/sd.py index e343e1fa8..b39230bd7 100644 --- a/comfy/sd.py +++ b/comfy/sd.py @@ -432,9 +432,11 @@ def load_clip(ckpt_paths, embedding_directory=None, clip_type=CLIPType.STABLE_DI clip_target.clip = sd2_clip.SD2ClipModel clip_target.tokenizer = sd2_clip.SD2Tokenizer elif "encoder.block.23.layer.1.DenseReluDense.wi_1.weight" in clip_data[0]: - dtype_t5 = clip_data[0]["encoder.block.23.layer.1.DenseReluDense.wi_1.weight"].dtype - clip_target.clip = sd3_clip.sd3_clip(clip_l=False, clip_g=False, t5=True, dtype_t5=dtype_t5) - clip_target.tokenizer = sd3_clip.SD3Tokenizer + weight = clip_data[0]["encoder.block.23.layer.1.DenseReluDense.wi_1.weight"] + dtype_t5 = weight.dtype + if weight.shape[-1] == 4096: + clip_target.clip = sd3_clip.sd3_clip(clip_l=False, clip_g=False, t5=True, dtype_t5=dtype_t5) + clip_target.tokenizer = sd3_clip.SD3Tokenizer elif "encoder.block.0.layer.0.SelfAttention.k.weight" in clip_data[0]: clip_target.clip = sa_t5.SAT5Model clip_target.tokenizer = sa_t5.SAT5Tokenizer From ff63893d103d9c3168eaf9101fb3cebbc2abd8fa Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Sat, 6 Jul 2024 02:42:53 -0400 Subject: [PATCH 059/133] Support other types of T5 models. --- comfy/t5.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/comfy/t5.py b/comfy/t5.py index d00b560a3..448c5aad3 100644 --- a/comfy/t5.py +++ b/comfy/t5.py @@ -190,11 +190,11 @@ class T5Block(torch.nn.Module): return x, past_bias class T5Stack(torch.nn.Module): - def __init__(self, num_layers, model_dim, inner_dim, ff_dim, ff_activation, gated_act, num_heads, dtype, device, operations): + def __init__(self, num_layers, model_dim, inner_dim, ff_dim, ff_activation, gated_act, num_heads, relative_attention, dtype, device, operations): super().__init__() self.block = torch.nn.ModuleList( - [T5Block(model_dim, inner_dim, ff_dim, ff_activation, gated_act, num_heads, relative_attention_bias=(i == 0), dtype=dtype, device=device, operations=operations) for i in range(num_layers)] + [T5Block(model_dim, inner_dim, ff_dim, ff_activation, gated_act, num_heads, relative_attention_bias=((not relative_attention) or (i == 0)), dtype=dtype, device=device, operations=operations) for i in range(num_layers)] ) self.final_layer_norm = T5LayerNorm(model_dim, dtype=dtype, device=device, operations=operations) # self.dropout = nn.Dropout(config.dropout_rate) @@ -223,7 +223,7 @@ class T5(torch.nn.Module): self.num_layers = config_dict["num_layers"] model_dim = config_dict["d_model"] - self.encoder = T5Stack(self.num_layers, model_dim, model_dim, config_dict["d_ff"], config_dict["dense_act_fn"], config_dict["is_gated_act"], config_dict["num_heads"], dtype, device, operations) + self.encoder = T5Stack(self.num_layers, model_dim, model_dim, config_dict["d_ff"], config_dict["dense_act_fn"], config_dict["is_gated_act"], config_dict["num_heads"], config_dict["model_type"] == "t5", dtype, device, operations) self.dtype = dtype self.shared = torch.nn.Embedding(config_dict["vocab_size"], model_dim, device=device) From 2dc84d14447782683862616eaf8c19c0c1feacf3 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Sat, 6 Jul 2024 04:06:03 -0400 Subject: [PATCH 060/133] Add a way to set the timestep multiplier in the flow sampling. --- comfy/model_sampling.py | 11 ++++++----- 1 file changed, 6 insertions(+), 5 deletions(-) diff --git a/comfy/model_sampling.py b/comfy/model_sampling.py index 6bd3a5d79..2d95a83dc 100644 --- a/comfy/model_sampling.py +++ b/comfy/model_sampling.py @@ -190,11 +190,12 @@ class ModelSamplingDiscreteFlow(torch.nn.Module): else: sampling_settings = {} - self.set_parameters(shift=sampling_settings.get("shift", 1.0)) + self.set_parameters(shift=sampling_settings.get("shift", 1.0), multiplier=sampling_settings.get("multiplier", 1000)) - def set_parameters(self, shift=1.0, timesteps=1000): + def set_parameters(self, shift=1.0, timesteps=1000, multiplier=1000): self.shift = shift - ts = self.sigma(torch.arange(1, timesteps + 1, 1)) + self.multiplier = multiplier + ts = self.sigma((torch.arange(1, timesteps + 1, 1) / timesteps) * multiplier) self.register_buffer('sigmas', ts) @property @@ -206,10 +207,10 @@ class ModelSamplingDiscreteFlow(torch.nn.Module): return self.sigmas[-1] def timestep(self, sigma): - return sigma * 1000 + return sigma * self.multiplier def sigma(self, timestep): - return time_snr_shift(self.shift, timestep / 1000) + return time_snr_shift(self.shift, timestep / self.multiplier) def percent_to_sigma(self, percent): if percent <= 0.0: From 628f0b8ebc2c9a51205e5e5a9973f8db348a310f Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Sun, 7 Jul 2024 09:22:32 -0400 Subject: [PATCH 061/133] Move audio nodes out of _for_testing. --- comfy_extras/nodes_audio.py | 11 +++++------ 1 file changed, 5 insertions(+), 6 deletions(-) diff --git a/comfy_extras/nodes_audio.py b/comfy_extras/nodes_audio.py index 9950d58ed..64d241e98 100644 --- a/comfy_extras/nodes_audio.py +++ b/comfy_extras/nodes_audio.py @@ -19,7 +19,7 @@ class EmptyLatentAudio: RETURN_TYPES = ("LATENT",) FUNCTION = "generate" - CATEGORY = "_for_testing/audio" + CATEGORY = "latent/audio" def generate(self, seconds): batch_size = 1 @@ -34,7 +34,7 @@ class VAEEncodeAudio: RETURN_TYPES = ("LATENT",) FUNCTION = "encode" - CATEGORY = "_for_testing/audio" + CATEGORY = "latent/audio" def encode(self, vae, audio): sample_rate = audio["sample_rate"] @@ -53,7 +53,7 @@ class VAEDecodeAudio: RETURN_TYPES = ("AUDIO",) FUNCTION = "decode" - CATEGORY = "_for_testing/audio" + CATEGORY = "latent/audio" def decode(self, vae, samples): audio = vae.decode(samples["samples"]).movedim(-1, 1) @@ -132,7 +132,7 @@ class SaveAudio: OUTPUT_NODE = True - CATEGORY = "_for_testing/audio" + CATEGORY = "audio" def save_audio(self, audio, filename_prefix="ComfyUI", prompt=None, extra_pnginfo=None): filename_prefix += self.prefix_append @@ -195,7 +195,7 @@ class LoadAudio: ] return {"required": {"audio": (sorted(files), {"audio_upload": True})}} - CATEGORY = "_for_testing/audio" + CATEGORY = "audio" RETURN_TYPES = ("AUDIO", ) FUNCTION = "load" @@ -203,7 +203,6 @@ class LoadAudio: def load(self, audio): audio_path = folder_paths.get_annotated_filepath(audio) waveform, sample_rate = torchaudio.load(audio_path) - multiplier = 1.0 audio = {"waveform": waveform.unsqueeze(0), "sample_rate": sample_rate} return (audio, ) From bb663bcd6c81a4395100c5f8527a221037d366f8 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Mon, 8 Jul 2024 08:48:38 -0400 Subject: [PATCH 062/133] Rename clip_t5base to t5base for stable audio text encoder. --- comfy/sa_t5.py | 2 +- comfy/sd1_clip.py | 12 +++++++++--- 2 files changed, 10 insertions(+), 4 deletions(-) diff --git a/comfy/sa_t5.py b/comfy/sa_t5.py index 37be5287e..acc302f67 100644 --- a/comfy/sa_t5.py +++ b/comfy/sa_t5.py @@ -19,4 +19,4 @@ class SAT5Tokenizer(sd1_clip.SD1Tokenizer): class SAT5Model(sd1_clip.SD1ClipModel): def __init__(self, device="cpu", dtype=None, **kwargs): - super().__init__(device=device, dtype=dtype, clip_name="t5base", clip_model=T5BaseModel, **kwargs) + super().__init__(device=device, dtype=dtype, name="t5base", clip_model=T5BaseModel, **kwargs) diff --git a/comfy/sd1_clip.py b/comfy/sd1_clip.py index ed3dc2298..0fe1f1d13 100644 --- a/comfy/sd1_clip.py +++ b/comfy/sd1_clip.py @@ -514,10 +514,16 @@ class SD1Tokenizer: class SD1ClipModel(torch.nn.Module): - def __init__(self, device="cpu", dtype=None, clip_name="l", clip_model=SDClipModel, **kwargs): + def __init__(self, device="cpu", dtype=None, clip_name="l", clip_model=SDClipModel, name=None, **kwargs): super().__init__() - self.clip_name = clip_name - self.clip = "clip_{}".format(self.clip_name) + + if name is not None: + self.clip_name = name + self.clip = "{}".format(self.clip_name) + else: + self.clip_name = clip_name + self.clip = "clip_{}".format(self.clip_name) + setattr(self, self.clip, clip_model(device=device, dtype=dtype, **kwargs)) self.dtypes = set() From faa57430b0ff882275b1afcf6610e8e9f8a5929b Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Mon, 8 Jul 2024 23:26:34 -0400 Subject: [PATCH 063/133] Controlnet union model basic implementation. This is only the model code itself, it currently defaults to an empty embedding [0] * 6 which seems to work better than treating it like a regular controlnet. TODO: Add nodes to select the image type. --- comfy/cldm/cldm.py | 113 +++++++++++++++++++++++++++++++++++++++++++- comfy/controlnet.py | 6 +++ 2 files changed, 118 insertions(+), 1 deletion(-) diff --git a/comfy/cldm/cldm.py b/comfy/cldm/cldm.py index f8a161594..3feb9bab0 100644 --- a/comfy/cldm/cldm.py +++ b/comfy/cldm/cldm.py @@ -13,7 +13,47 @@ from ..ldm.modules.diffusionmodules.util import ( from ..ldm.modules.attention import SpatialTransformer from ..ldm.modules.diffusionmodules.openaimodel import UNetModel, TimestepEmbedSequential, ResBlock, Downsample from ..ldm.util import exists +from ..ldm.cascade.common import OptimizedAttention +from collections import OrderedDict import comfy.ops +from comfy.ldm.modules.attention import optimized_attention + +class OptimizedAttention(nn.Module): + def __init__(self, c, nhead, dropout=0.0, dtype=None, device=None, operations=None): + super().__init__() + self.heads = nhead + self.c = c + + self.in_proj = operations.Linear(c, c * 3, bias=True, dtype=dtype, device=device) + self.out_proj = operations.Linear(c, c, bias=True, dtype=dtype, device=device) + + def forward(self, x): + x = self.in_proj(x) + q, k, v = x.split(self.c, dim=2) + out = optimized_attention(q, k, v, self.heads) + return self.out_proj(out) + +class QuickGELU(nn.Module): + def forward(self, x: torch.Tensor): + return x * torch.sigmoid(1.702 * x) + +class ResBlockUnionControlnet(nn.Module): + def __init__(self, dim, nhead, dtype=None, device=None, operations=None): + super().__init__() + self.attn = OptimizedAttention(dim, nhead, dtype=dtype, device=device, operations=operations) + self.ln_1 = operations.LayerNorm(dim, dtype=dtype, device=device) + self.mlp = nn.Sequential( + OrderedDict([("c_fc", operations.Linear(dim, dim * 4, dtype=dtype, device=device)), ("gelu", QuickGELU()), + ("c_proj", operations.Linear(dim * 4, dim, dtype=dtype, device=device))])) + self.ln_2 = operations.LayerNorm(dim, dtype=dtype, device=device) + + def attention(self, x: torch.Tensor): + return self.attn(x) + + def forward(self, x: torch.Tensor): + x = x + self.attention(self.ln_1(x)) + x = x + self.mlp(self.ln_2(x)) + return x class ControlledUnetModel(UNetModel): #implemented in the ldm unet @@ -53,6 +93,7 @@ class ControlNet(nn.Module): transformer_depth_middle=None, transformer_depth_output=None, attn_precision=None, + union_controlnet=False, device=None, operations=comfy.ops.disable_weight_init, **kwargs, @@ -280,6 +321,65 @@ class ControlNet(nn.Module): self.middle_block_out = self.make_zero_conv(ch, operations=operations, dtype=self.dtype, device=device) self._feature_size += ch + if union_controlnet: + self.num_control_type = 6 + num_trans_channel = 320 + num_trans_head = 8 + num_trans_layer = 1 + num_proj_channel = 320 + # task_scale_factor = num_trans_channel ** 0.5 + self.task_embedding = nn.Parameter(torch.empty(self.num_control_type, num_trans_channel, dtype=self.dtype, device=device)) + + self.transformer_layes = nn.Sequential(*[ResBlockUnionControlnet(num_trans_channel, num_trans_head, dtype=self.dtype, device=device, operations=operations) for _ in range(num_trans_layer)]) + self.spatial_ch_projs = operations.Linear(num_trans_channel, num_proj_channel, dtype=self.dtype, device=device) + #----------------------------------------------------------------------------------------------------- + + control_add_embed_dim = 256 + class ControlAddEmbedding(nn.Module): + def __init__(self, in_dim, out_dim, num_control_type, dtype=None, device=None, operations=None): + super().__init__() + self.num_control_type = num_control_type + self.in_dim = in_dim + self.linear_1 = operations.Linear(in_dim * num_control_type, out_dim, dtype=dtype, device=device) + self.linear_2 = operations.Linear(out_dim, out_dim, dtype=dtype, device=device) + def forward(self, control_type, dtype, device): + c_type = torch.zeros((self.num_control_type,), device=device) + c_type[control_type] = 1.0 + c_type = timestep_embedding(c_type.flatten(), self.in_dim, repeat_only=False).to(dtype).reshape((-1, self.num_control_type * self.in_dim)) + return self.linear_2(torch.nn.functional.silu(self.linear_1(c_type))) + + self.control_add_embedding = ControlAddEmbedding(control_add_embed_dim, time_embed_dim, self.num_control_type, dtype=self.dtype, device=device, operations=operations) + else: + self.task_embedding = None + self.control_add_embedding = None + + def union_controlnet_merge(self, hint, control_type, emb, context): + # Equivalent to: https://github.com/xinsir6/ControlNetPlus/tree/main + inputs = [] + condition_list = [] + + for idx in range(min(1, len(control_type))): + controlnet_cond = self.input_hint_block(hint[idx], emb, context) + feat_seq = torch.mean(controlnet_cond, dim=(2, 3)) + if idx < len(control_type): + feat_seq += self.task_embedding[control_type[idx]] + + inputs.append(feat_seq.unsqueeze(1)) + condition_list.append(controlnet_cond) + + x = torch.cat(inputs, dim=1) + x = self.transformer_layes(x) + controlnet_cond_fuser = None + for idx in range(len(control_type)): + alpha = self.spatial_ch_projs(x[:, idx]) + alpha = alpha.unsqueeze(-1).unsqueeze(-1) + o = condition_list[idx] + alpha + if controlnet_cond_fuser is None: + controlnet_cond_fuser = o + else: + controlnet_cond_fuser += o + return controlnet_cond_fuser + def make_zero_conv(self, channels, operations=None, dtype=None, device=None): return TimestepEmbedSequential(operations.conv_nd(self.dims, channels, channels, 1, padding=0, dtype=dtype, device=device)) @@ -287,7 +387,18 @@ class ControlNet(nn.Module): t_emb = timestep_embedding(timesteps, self.model_channels, repeat_only=False).to(x.dtype) emb = self.time_embed(t_emb) - guided_hint = self.input_hint_block(hint, emb, context) + guided_hint = None + if self.control_add_embedding is not None: + control_type = kwargs.get("control_type", []) + + emb += self.control_add_embedding(control_type, emb.dtype, emb.device) + if len(control_type) > 0: + if len(hint.shape) < 5: + hint = hint.unsqueeze(dim=0) + guided_hint = self.union_controlnet_merge(hint, control_type, emb, context) + + if guided_hint is None: + guided_hint = self.input_hint_block(hint, emb, context) out_output = [] out_middle = [] diff --git a/comfy/controlnet.py b/comfy/controlnet.py index d00395139..84286f1fa 100644 --- a/comfy/controlnet.py +++ b/comfy/controlnet.py @@ -413,6 +413,12 @@ def load_controlnet(ckpt_path, model=None): if k in controlnet_data: new_sd[diffusers_keys[k]] = controlnet_data.pop(k) + if "control_add_embedding.linear_1.bias" in controlnet_data: #Union Controlnet + controlnet_config["union_controlnet"] = True + for k in list(controlnet_data.keys()): + new_k = k.replace('.attn.in_proj_', '.attn.in_proj.') + new_sd[new_k] = controlnet_data.pop(k) + leftover_keys = controlnet_data.keys() if len(leftover_keys) > 0: logging.warning("leftover keys: {}".format(leftover_keys)) From ade7aa1b0ce7944f50f66af5d8742299ac49d07f Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Tue, 9 Jul 2024 11:05:05 -0400 Subject: [PATCH 064/133] Remove useless import. --- comfy/cldm/cldm.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/comfy/cldm/cldm.py b/comfy/cldm/cldm.py index 3feb9bab0..d4d32b87e 100644 --- a/comfy/cldm/cldm.py +++ b/comfy/cldm/cldm.py @@ -13,7 +13,6 @@ from ..ldm.modules.diffusionmodules.util import ( from ..ldm.modules.attention import SpatialTransformer from ..ldm.modules.diffusionmodules.openaimodel import UNetModel, TimestepEmbedSequential, ResBlock, Downsample from ..ldm.util import exists -from ..ldm.cascade.common import OptimizedAttention from collections import OrderedDict import comfy.ops from comfy.ldm.modules.attention import optimized_attention @@ -388,7 +387,7 @@ class ControlNet(nn.Module): emb = self.time_embed(t_emb) guided_hint = None - if self.control_add_embedding is not None: + if self.control_add_embedding is not None: #Union Controlnet control_type = kwargs.get("control_type", []) emb += self.control_add_embedding(control_type, emb.dtype, emb.device) From d160073829b836fce97046ebb5f145fa1c677ae3 Mon Sep 17 00:00:00 2001 From: bymyself Date: Tue, 9 Jul 2024 08:23:26 -0700 Subject: [PATCH 065/133] Fix loadGraphData call during restore (#3976) --- web/scripts/app.js | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/web/scripts/app.js b/web/scripts/app.js index 67e488bf9..8b4478a32 100644 --- a/web/scripts/app.js +++ b/web/scripts/app.js @@ -1599,7 +1599,7 @@ export class ComfyApp { if (json) { const workflow = JSON.parse(json); const workflowName = getStorageValue("Comfy.PreviousWorkflow"); - await this.loadGraphData(workflow, true, workflowName); + await this.loadGraphData(workflow, true, true, workflowName); return true; } }; From c3db344746163f9ab942591020043d47ca34e4f0 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Tue, 9 Jul 2024 11:52:31 -0400 Subject: [PATCH 066/133] Fix ConditioningZeroOut when there is no pooled output. --- nodes.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/nodes.py b/nodes.py index 9c541eba8..a230f725b 100644 --- a/nodes.py +++ b/nodes.py @@ -232,8 +232,9 @@ class ConditioningZeroOut: c = [] for t in conditioning: d = t[1].copy() - if "pooled_output" in d: - d["pooled_output"] = torch.zeros_like(d["pooled_output"]) + pooled_output = d.get("pooled_output", None) + if pooled_output is not None: + d["pooled_output"] = torch.zeros_like(pooled_output) n = [torch.zeros_like(t[0]), d] c.append(n) return (c, ) From f1a01c2c7e2678f34c72212d2a8640237f31fa43 Mon Sep 17 00:00:00 2001 From: Extraltodeus Date: Tue, 9 Jul 2024 22:20:49 +0200 Subject: [PATCH 067/133] Add sampler_pre_cfg_function (#3979) * Update samplers.py * Update model_patcher.py --- comfy/model_patcher.py | 9 +++++++++ comfy/samplers.py | 6 ++++++ 2 files changed, 15 insertions(+) diff --git a/comfy/model_patcher.py b/comfy/model_patcher.py index b949031e9..efac251ca 100644 --- a/comfy/model_patcher.py +++ b/comfy/model_patcher.py @@ -57,6 +57,12 @@ def set_model_options_post_cfg_function(model_options, post_cfg_function, disabl model_options["disable_cfg1_optimization"] = True return model_options +def set_model_options_pre_cfg_function(model_options, pre_cfg_function, disable_cfg1_optimization=False): + model_options["sampler_pre_cfg_function"] = model_options.get("sampler_pre_cfg_function", []) + [pre_cfg_function] + if disable_cfg1_optimization: + model_options["disable_cfg1_optimization"] = True + return model_options + class ModelPatcher: def __init__(self, model, load_device, offload_device, size=0, current_device=None, weight_inplace_update=False): self.size = size @@ -130,6 +136,9 @@ class ModelPatcher: def set_model_sampler_post_cfg_function(self, post_cfg_function, disable_cfg1_optimization=False): self.model_options = set_model_options_post_cfg_function(self.model_options, post_cfg_function, disable_cfg1_optimization) + def set_model_sampler_pre_cfg_function(self, pre_cfg_function, disable_cfg1_optimization=False): + self.model_options = set_model_options_pre_cfg_function(self.model_options, pre_cfg_function, disable_cfg1_optimization) + def set_model_unet_function_wrapper(self, unet_wrapper_function: UnetWrapperFunction): self.model_options["model_function_wrapper"] = unet_wrapper_function diff --git a/comfy/samplers.py b/comfy/samplers.py index c0aa12916..bbf9219f7 100644 --- a/comfy/samplers.py +++ b/comfy/samplers.py @@ -275,6 +275,12 @@ def sampling_function(model, x, timestep, uncond, cond, cond_scale, model_option conds = [cond, uncond_] out = calc_cond_batch(model, conds, x, timestep, model_options) + + for fn in model_options.get("sampler_pre_cfg_function", []): + args = {"conds":conds, "conds_out": out, "cond_scale": cond_scale, "timestep": timestep, + "input": x, "sigma": timestep, "model": model, "model_options": model_options} + out = fn(args) + return cfg_function(model, out[0], out[1], cond_scale, x, timestep, model_options=model_options, cond=cond, uncond=uncond_) From 83f70a88fbc4866050dae90d78ec66aebe8e341a Mon Sep 17 00:00:00 2001 From: Chenlei Hu Date: Tue, 9 Jul 2024 17:07:15 -0400 Subject: [PATCH 068/133] Add __module__ to node info (#3936) Use more explicit name 'python_module' Parse abs ath Move parse to nodes.py --- nodes.py | 29 ++++++++++++++++++++++++++--- server.py | 1 + 2 files changed, 27 insertions(+), 3 deletions(-) diff --git a/nodes.py b/nodes.py index a230f725b..8d8b153f8 100644 --- a/nodes.py +++ b/nodes.py @@ -1889,7 +1889,29 @@ NODE_DISPLAY_NAME_MAPPINGS = { EXTENSION_WEB_DIRS = {} -def load_custom_node(module_path, ignore=set()): +def get_relative_module_name(module_path: str) -> str: + """ + Returns the module name based on the given module path. + Examples: + get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node.py") -> "custom_nodes.my_custom_node" + get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node") -> "custom_nodes.my_custom_node" + get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node/") -> "custom_nodes.my_custom_node" + get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node/__init__.py") -> "custom_nodes.my_custom_node" + get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node/__init__") -> "custom_nodes.my_custom_node" + get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node/__init__/") -> "custom_nodes.my_custom_node" + get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node.disabled") -> "custom_nodes.my + Args: + module_path (str): The path of the module. + Returns: + str: The module name. + """ + relative_path = os.path.relpath(module_path, folder_paths.base_path) + if os.path.isfile(module_path): + relative_path = os.path.splitext(relative_path)[0] + return relative_path.replace(os.sep, '.') + + +def load_custom_node(module_path: str, ignore=set()) -> bool: module_name = os.path.basename(module_path) if os.path.isfile(module_path): sp = os.path.splitext(module_path) @@ -1913,9 +1935,10 @@ def load_custom_node(module_path, ignore=set()): EXTENSION_WEB_DIRS[module_name] = web_dir if hasattr(module, "NODE_CLASS_MAPPINGS") and getattr(module, "NODE_CLASS_MAPPINGS") is not None: - for name in module.NODE_CLASS_MAPPINGS: + for name, node_cls in module.NODE_CLASS_MAPPINGS.items(): if name not in ignore: - NODE_CLASS_MAPPINGS[name] = module.NODE_CLASS_MAPPINGS[name] + NODE_CLASS_MAPPINGS[name] = node_cls + node_cls.RELATIVE_PYTHON_MODULE = get_relative_module_name(module_path) if hasattr(module, "NODE_DISPLAY_NAME_MAPPINGS") and getattr(module, "NODE_DISPLAY_NAME_MAPPINGS") is not None: NODE_DISPLAY_NAME_MAPPINGS.update(module.NODE_DISPLAY_NAME_MAPPINGS) return True diff --git a/server.py b/server.py index 38b1bab80..ce7c7532d 100644 --- a/server.py +++ b/server.py @@ -416,6 +416,7 @@ class PromptServer(): info['name'] = node_class info['display_name'] = nodes.NODE_DISPLAY_NAME_MAPPINGS[node_class] if node_class in nodes.NODE_DISPLAY_NAME_MAPPINGS.keys() else node_class info['description'] = obj_class.DESCRIPTION if hasattr(obj_class,'DESCRIPTION') else '' + info['python_module'] = getattr(obj_class, "RELATIVE_PYTHON_MODULE", "nodes") info['category'] = 'sd' if hasattr(obj_class, 'OUTPUT_NODE') and obj_class.OUTPUT_NODE == True: info['output_node'] = True From 8d3f979b633dab9824c59bf8a06c748a533eec0b Mon Sep 17 00:00:00 2001 From: Chenlei Hu Date: Tue, 9 Jul 2024 17:12:57 -0400 Subject: [PATCH 069/133] Check unhandled exception in test log in test action (#3987) * Upload console logs * Check unhandled exception --- .github/workflows/test-browser.yml | 15 ++++++++++++++- 1 file changed, 14 insertions(+), 1 deletion(-) diff --git a/.github/workflows/test-browser.yml b/.github/workflows/test-browser.yml index 65483b00f..7beb0c696 100644 --- a/.github/workflows/test-browser.yml +++ b/.github/workflows/test-browser.yml @@ -42,7 +42,7 @@ jobs: working-directory: ComfyUI - name: Start ComfyUI server run: | - python main.py --cpu & + python main.py --cpu 2>&1 | tee console_output.log & wait-for-it --service 127.0.0.1:8188 -t 600 working-directory: ComfyUI - name: Install ComfyUI_frontend dependencies @@ -55,9 +55,22 @@ jobs: - name: Run Playwright tests run: npx playwright test working-directory: ComfyUI_frontend + - name: Check for unhandled exceptions in server log + run: | + if grep -qE "Exception|Error" console_output.log; then + echo "Unhandled exception/error found in server log." + exit 1 + fi + working-directory: ComfyUI - uses: actions/upload-artifact@v4 if: always() with: name: playwright-report path: ComfyUI_frontend/playwright-report/ retention-days: 30 + - uses: actions/upload-artifact@v4 + if: always() + with: + name: console-output + path: ComfyUI/console_output.log + retention-days: 30 From 90389b3b8a69c08c3ed0bcc9d87a92246578a8e3 Mon Sep 17 00:00:00 2001 From: Chenlei Hu Date: Wed, 10 Jul 2024 11:28:15 -0400 Subject: [PATCH 070/133] Update bug issue template (#3996) * Update issue template * nit --- .github/ISSUE_TEMPLATE/bug-report.yml | 83 ++++++++++++++------------- 1 file changed, 43 insertions(+), 40 deletions(-) diff --git a/.github/ISSUE_TEMPLATE/bug-report.yml b/.github/ISSUE_TEMPLATE/bug-report.yml index 87bef3681..39d1992d7 100644 --- a/.github/ISSUE_TEMPLATE/bug-report.yml +++ b/.github/ISSUE_TEMPLATE/bug-report.yml @@ -1,45 +1,48 @@ name: Bug Report description: "Something is broken inside of ComfyUI. (Do not use this if you're just having issues and need help, or if the issue relates to a custom node)" -labels: [ "Potential Bug" ] +labels: ["Potential Bug"] body: - - type: markdown - attributes: - value: | - Before submitting a **Bug Report**, please ensure the following: + - type: markdown + attributes: + value: | + Before submitting a **Bug Report**, please ensure the following: - **1:** You are running the latest version of ComfyUI. - **2:** You have looked at the existing bug reports and made sure this isn't already reported. - **3:** This is an actual bug in ComfyUI, not just a support question and not caused by an custom node. A bug is when you can specify exact steps to replicate what went wrong and others will be able to repeat your steps and see the same issue happen. + - **1:** You are running the latest version of ComfyUI. + - **2:** You have looked at the existing bug reports and made sure this isn't already reported. + - **3:** You confirmed that the bug is not caused by a custom node. You can disable all custom nodes by passing + `--disable-all-custom-nodes` command line argument. + - **4:** This is an actual bug in ComfyUI, not just a support question. A bug is when you can specify exact + steps to replicate what went wrong and others will be able to repeat your steps and see the same issue happen. - If unsure, ask on the [ComfyUI Matrix Space](https://app.element.io/#/room/%23comfyui_space%3Amatrix.org) or the [Comfy Org Discord](https://discord.gg/comfyorg) first. - - type: textarea - attributes: - label: Expected Behavior - description: "What you expected to happen." - validations: - required: true - - type: textarea - attributes: - label: Actual Behavior - description: "What actually happened. Please include a screenshot of the issue if possible." - validations: - required: true - - type: textarea - attributes: - label: Steps to Reproduce - description: "Describe how to reproduce the issue. Please be sure to attach a workflow JSON or PNG, ideally one that doesn't require custom nodes to test. If the bug open happens when certain custom nodes are used, most likely that custom node is what has the bug rather than ComfyUI, in which case it should be reported to the node's author." - validations: - required: true - - type: textarea - attributes: - label: Debug Logs - description: "Please copy the output from your terminal logs here." - render: powershell - validations: - required: true - - type: textarea - attributes: - label: Other - description: "Any other additional information you think might be helpful." - validations: - required: false + If unsure, ask on the [ComfyUI Matrix Space](https://app.element.io/#/room/%23comfyui_space%3Amatrix.org) or the [Comfy Org Discord](https://discord.gg/comfyorg) first. + - type: textarea + attributes: + label: Expected Behavior + description: "What you expected to happen." + validations: + required: true + - type: textarea + attributes: + label: Actual Behavior + description: "What actually happened. Please include a screenshot of the issue if possible." + validations: + required: true + - type: textarea + attributes: + label: Steps to Reproduce + description: "Describe how to reproduce the issue. Please be sure to attach a workflow JSON or PNG, ideally one that doesn't require custom nodes to test. If the bug open happens when certain custom nodes are used, most likely that custom node is what has the bug rather than ComfyUI, in which case it should be reported to the node's author." + validations: + required: true + - type: textarea + attributes: + label: Debug Logs + description: "Please copy the output from your terminal logs here." + render: powershell + validations: + required: true + - type: textarea + attributes: + label: Other + description: "Any other additional information you think might be helpful." + validations: + required: false From e44fa5667fd0a5469b1b5efa08187282779f4d44 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Wed, 10 Jul 2024 19:31:22 -0400 Subject: [PATCH 071/133] Support returning text encoder attention masks. --- comfy/sd1_clip.py | 19 ++++++++++++++----- 1 file changed, 14 insertions(+), 5 deletions(-) diff --git a/comfy/sd1_clip.py b/comfy/sd1_clip.py index 0fe1f1d13..4da2b46fd 100644 --- a/comfy/sd1_clip.py +++ b/comfy/sd1_clip.py @@ -38,7 +38,9 @@ class ClipTokenWeightEncoder: if has_weights or sections == 0: to_encode.append(gen_empty_tokens(self.special_tokens, max_token_len)) - out, pooled = self.encode(to_encode) + o = self.encode(to_encode) + out, pooled = o[:2] + if pooled is not None: first_pooled = pooled[0:1].to(model_management.intermediate_device()) else: @@ -57,8 +59,11 @@ class ClipTokenWeightEncoder: output.append(z) if (len(output) == 0): - return out[-1:].to(model_management.intermediate_device()), first_pooled - return torch.cat(output, dim=-2).to(model_management.intermediate_device()), first_pooled + r = (out[-1:].to(model_management.intermediate_device()), first_pooled) + else: + r = (torch.cat(output, dim=-2).to(model_management.intermediate_device()), first_pooled) + r = r + tuple(map(lambda a: a[:sections].flatten().unsqueeze(dim=0).to(model_management.intermediate_device()), o[2:])) + return r class SDClipModel(torch.nn.Module, ClipTokenWeightEncoder): """Uses the CLIP transformer encoder for text (from huggingface)""" @@ -70,7 +75,7 @@ class SDClipModel(torch.nn.Module, ClipTokenWeightEncoder): def __init__(self, version="openai/clip-vit-large-patch14", device="cpu", max_length=77, freeze=True, layer="last", layer_idx=None, textmodel_json_config=None, dtype=None, model_class=comfy.clip_model.CLIPTextModel, special_tokens={"start": 49406, "end": 49407, "pad": 49407}, layer_norm_hidden_state=True, enable_attention_masks=False, zero_out_masked=False, - return_projected_pooled=True): # clip-vit-base-patch32 + return_projected_pooled=True, return_attention_masks=False): # clip-vit-base-patch32 super().__init__() assert layer in self.LAYERS @@ -96,6 +101,7 @@ class SDClipModel(torch.nn.Module, ClipTokenWeightEncoder): self.layer_norm_hidden_state = layer_norm_hidden_state self.return_projected_pooled = return_projected_pooled + self.return_attention_masks = return_attention_masks if layer == "hidden": assert layer_idx is not None @@ -169,7 +175,7 @@ class SDClipModel(torch.nn.Module, ClipTokenWeightEncoder): tokens = torch.LongTensor(tokens).to(device) attention_mask = None - if self.enable_attention_masks or self.zero_out_masked: + if self.enable_attention_masks or self.zero_out_masked or self.return_attention_masks: attention_mask = torch.zeros_like(tokens) end_token = self.special_tokens.get("end", -1) for x in range(attention_mask.shape[0]): @@ -200,6 +206,9 @@ class SDClipModel(torch.nn.Module, ClipTokenWeightEncoder): elif outputs[2] is not None: pooled_output = outputs[2].float() + if self.return_attention_masks: + return z, pooled_output, attention_mask + return z, pooled_output def encode(self, tokens): From 391c1046cff8a3877a2ba343057579ab4278c5b1 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Wed, 10 Jul 2024 20:06:50 -0400 Subject: [PATCH 072/133] More flexibility with text encoder return values. Text encoders can now return other values to the CONDITIONING than the cond and pooled output. --- comfy/sd.py | 12 ++++++++++-- comfy/sd1_clip.py | 21 +++++++++++++++++---- nodes.py | 5 +++-- 3 files changed, 30 insertions(+), 8 deletions(-) diff --git a/comfy/sd.py b/comfy/sd.py index b39230bd7..25454f836 100644 --- a/comfy/sd.py +++ b/comfy/sd.py @@ -130,7 +130,7 @@ class CLIP: def tokenize(self, text, return_word_ids=False): return self.tokenizer.tokenize_with_weights(text, return_word_ids) - def encode_from_tokens(self, tokens, return_pooled=False): + def encode_from_tokens(self, tokens, return_pooled=False, return_dict=False): self.cond_stage_model.reset_clip_options() if self.layer_idx is not None: @@ -140,7 +140,15 @@ class CLIP: self.cond_stage_model.set_clip_options({"projected_pooled": False}) self.load_model() - cond, pooled = self.cond_stage_model.encode_token_weights(tokens) + o = self.cond_stage_model.encode_token_weights(tokens) + cond, pooled = o[:2] + if return_dict: + out = {"cond": cond, "pooled_output": pooled} + if len(o) > 2: + for k in o[2]: + out[k] = o[2][k] + return out + if return_pooled: return cond, pooled return cond diff --git a/comfy/sd1_clip.py b/comfy/sd1_clip.py index 4da2b46fd..565ad69da 100644 --- a/comfy/sd1_clip.py +++ b/comfy/sd1_clip.py @@ -62,7 +62,16 @@ class ClipTokenWeightEncoder: r = (out[-1:].to(model_management.intermediate_device()), first_pooled) else: r = (torch.cat(output, dim=-2).to(model_management.intermediate_device()), first_pooled) - r = r + tuple(map(lambda a: a[:sections].flatten().unsqueeze(dim=0).to(model_management.intermediate_device()), o[2:])) + + if len(o) > 2: + extra = {} + for k in o[2]: + v = o[2][k] + if k == "attention_mask": + v = v[:sections].flatten().unsqueeze(dim=0).to(model_management.intermediate_device()) + extra[k] = v + + r = r + (extra,) return r class SDClipModel(torch.nn.Module, ClipTokenWeightEncoder): @@ -206,8 +215,12 @@ class SDClipModel(torch.nn.Module, ClipTokenWeightEncoder): elif outputs[2] is not None: pooled_output = outputs[2].float() + extra = {} if self.return_attention_masks: - return z, pooled_output, attention_mask + extra["attention_mask"] = attention_mask + + if len(extra) > 0: + return z, pooled_output, extra return z, pooled_output @@ -547,8 +560,8 @@ class SD1ClipModel(torch.nn.Module): def encode_token_weights(self, token_weight_pairs): token_weight_pairs = token_weight_pairs[self.clip_name] - out, pooled = getattr(self, self.clip).encode_token_weights(token_weight_pairs) - return out, pooled + out = getattr(self, self.clip).encode_token_weights(token_weight_pairs) + return out def load_sd(self, sd): return getattr(self, self.clip).load_sd(sd) diff --git a/nodes.py b/nodes.py index 8d8b153f8..5778f0609 100644 --- a/nodes.py +++ b/nodes.py @@ -55,8 +55,9 @@ class CLIPTextEncode: def encode(self, clip, text): tokens = clip.tokenize(text) - cond, pooled = clip.encode_from_tokens(tokens, return_pooled=True) - return ([[cond, {"pooled_output": pooled}]], ) + output = clip.encode_from_tokens(tokens, return_pooled=True, return_dict=True) + cond = output.pop("cond") + return ([[cond, output]], ) class ConditioningCombine: @classmethod From ffe0bb0a33a8a8d9a999dafb540558646127d443 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Wed, 10 Jul 2024 20:33:12 -0400 Subject: [PATCH 073/133] Remove useless code. --- comfy/sd.py | 30 ------------------------------ 1 file changed, 30 deletions(-) diff --git a/comfy/sd.py b/comfy/sd.py index 25454f836..d0832ad3a 100644 --- a/comfy/sd.py +++ b/comfy/sd.py @@ -28,36 +28,6 @@ import comfy.t2i_adapter.adapter import comfy.supported_models_base import comfy.taesd.taesd -def load_model_weights(model, sd): - m, u = model.load_state_dict(sd, strict=False) - m = set(m) - unexpected_keys = set(u) - - k = list(sd.keys()) - for x in k: - if x not in unexpected_keys: - w = sd.pop(x) - del w - if len(m) > 0: - logging.warning("missing {}".format(m)) - return model - -def load_clip_weights(model, sd): - k = list(sd.keys()) - for x in k: - if x.startswith("cond_stage_model.transformer.") and not x.startswith("cond_stage_model.transformer.text_model."): - y = x.replace("cond_stage_model.transformer.", "cond_stage_model.transformer.text_model.") - sd[y] = sd.pop(x) - - if 'cond_stage_model.transformer.text_model.embeddings.position_ids' in sd: - ids = sd['cond_stage_model.transformer.text_model.embeddings.position_ids'] - if ids.dtype == torch.float32: - sd['cond_stage_model.transformer.text_model.embeddings.position_ids'] = ids.round() - - sd = comfy.utils.clip_text_transformers_convert(sd, "cond_stage_model.model.", "cond_stage_model.transformer.") - return load_model_weights(model, sd) - - def load_lora_for_models(model, clip, lora, strength_model, strength_clip): key_map = {} if model is not None: From 5e1fced6392ca4fef404e01094fbcbec77bdd31f Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Thu, 11 Jul 2024 11:37:31 -0400 Subject: [PATCH 074/133] Cleaner support for loading different diffusion model types. --- comfy/model_detection.py | 5 +++++ comfy/sd.py | 8 ++------ 2 files changed, 7 insertions(+), 6 deletions(-) diff --git a/comfy/model_detection.py b/comfy/model_detection.py index 0b678480f..783a03eb7 100644 --- a/comfy/model_detection.py +++ b/comfy/model_detection.py @@ -105,6 +105,9 @@ def detect_unet_config(state_dict, key_prefix): unet_config["audio_model"] = "dit1.0" return unet_config + if '{}input_blocks.0.0.weight'.format(key_prefix) not in state_dict_keys: + return None + unet_config = { "use_checkpoint": False, "image_size": 32, @@ -239,6 +242,8 @@ def model_config_from_unet_config(unet_config, state_dict=None): def model_config_from_unet(state_dict, unet_key_prefix, use_base_if_no_match=False): unet_config = detect_unet_config(state_dict, unet_key_prefix) + if unet_config is None: + return None model_config = model_config_from_unet_config(unet_config, state_dict) if model_config is None and use_base_if_no_match: return comfy.supported_models_base.BASE(unet_config) diff --git a/comfy/sd.py b/comfy/sd.py index d0832ad3a..66033b63e 100644 --- a/comfy/sd.py +++ b/comfy/sd.py @@ -546,21 +546,17 @@ def load_checkpoint_guess_config(ckpt_path, output_vae=True, output_clip=True, o def load_unet_state_dict(sd): #load unet in diffusers or regular format #Allow loading unets from checkpoint files - checkpoint = False diffusion_model_prefix = model_detection.unet_prefix_from_state_dict(sd) temp_sd = comfy.utils.state_dict_prefix_replace(sd, {diffusion_model_prefix: ""}, filter_keys=True) if len(temp_sd) > 0: sd = temp_sd - checkpoint = True parameters = comfy.utils.calculate_parameters(sd) unet_dtype = model_management.unet_dtype(model_params=parameters) load_device = model_management.get_torch_device() + model_config = model_detection.model_config_from_unet(sd, "") - if checkpoint or "input_blocks.0.0.weight" in sd or 'clf.1.weight' in sd: #ldm or stable cascade - model_config = model_detection.model_config_from_unet(sd, "") - if model_config is None: - return None + if model_config is not None: new_sd = sd elif 'transformer_blocks.0.attn.add_q_proj.weight' in sd: #MMDIT SD3 new_sd = model_detection.convert_diffusers_mmdit(sd, "") From f45157e3acbef1c0edf7d31fc73ee83e7913a994 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Thu, 11 Jul 2024 11:46:51 -0400 Subject: [PATCH 075/133] Fix error message never being shown. --- comfy/sd.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/comfy/sd.py b/comfy/sd.py index 66033b63e..eeffa423a 100644 --- a/comfy/sd.py +++ b/comfy/sd.py @@ -489,13 +489,13 @@ def load_checkpoint_guess_config(ckpt_path, output_vae=True, output_clip=True, o load_device = model_management.get_torch_device() model_config = model_detection.model_config_from_unet(sd, diffusion_model_prefix) + if model_config is None: + raise RuntimeError("ERROR: Could not detect model type of: {}".format(ckpt_path)) + unet_dtype = model_management.unet_dtype(model_params=parameters, supported_dtypes=model_config.supported_inference_dtypes) manual_cast_dtype = model_management.unet_manual_cast(unet_dtype, load_device, model_config.supported_inference_dtypes) model_config.set_inference_dtype(unet_dtype, manual_cast_dtype) - if model_config is None: - raise RuntimeError("ERROR: Could not detect model type of: {}".format(ckpt_path)) - if model_config.clip_vision_prefix is not None: if output_clipvision: clipvision = clip_vision.load_clipvision_from_sd(sd, model_config.clip_vision_prefix, True) From 9f291d75b344d7f7e83b7bd18447f430c99fcb28 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Thu, 11 Jul 2024 16:51:06 -0400 Subject: [PATCH 076/133] AuraFlow model implementation. --- comfy/ldm/aura/mmdit.py | 479 +++++++++ comfy/model_base.py | 12 + comfy/model_detection.py | 8 + comfy/sd.py | 4 + comfy/supported_models.py | 24 +- comfy/text_encoders/aura_t5.py | 22 + comfy/text_encoders/t5_pile_config_xl.json | 22 + .../t5_pile_tokenizer/added_tokens.json | 102 ++ .../t5_pile_tokenizer/special_tokens_map.json | 125 +++ .../t5_pile_tokenizer/tokenizer.model | Bin 0 -> 499723 bytes .../t5_pile_tokenizer/tokenizer_config.json | 945 ++++++++++++++++++ requirements.txt | 3 +- 12 files changed, 1744 insertions(+), 2 deletions(-) create mode 100644 comfy/ldm/aura/mmdit.py create mode 100644 comfy/text_encoders/aura_t5.py create mode 100644 comfy/text_encoders/t5_pile_config_xl.json create mode 100644 comfy/text_encoders/t5_pile_tokenizer/added_tokens.json create mode 100644 comfy/text_encoders/t5_pile_tokenizer/special_tokens_map.json create mode 100644 comfy/text_encoders/t5_pile_tokenizer/tokenizer.model create mode 100644 comfy/text_encoders/t5_pile_tokenizer/tokenizer_config.json diff --git a/comfy/ldm/aura/mmdit.py b/comfy/ldm/aura/mmdit.py new file mode 100644 index 000000000..c465619bd --- /dev/null +++ b/comfy/ldm/aura/mmdit.py @@ -0,0 +1,479 @@ +#AuraFlow MMDiT +#Originally written by the AuraFlow Authors + +import math + +import torch +import torch.nn as nn +import torch.nn.functional as F + +from comfy.ldm.modules.attention import optimized_attention + +def modulate(x, shift, scale): + return x * (1 + scale.unsqueeze(1)) + shift.unsqueeze(1) + + +def find_multiple(n: int, k: int) -> int: + if n % k == 0: + return n + return n + k - (n % k) + + +class MLP(nn.Module): + def __init__(self, dim, hidden_dim=None, dtype=None, device=None, operations=None) -> None: + super().__init__() + if hidden_dim is None: + hidden_dim = 4 * dim + + n_hidden = int(2 * hidden_dim / 3) + n_hidden = find_multiple(n_hidden, 256) + + self.c_fc1 = operations.Linear(dim, n_hidden, bias=False, dtype=dtype, device=device) + self.c_fc2 = operations.Linear(dim, n_hidden, bias=False, dtype=dtype, device=device) + self.c_proj = operations.Linear(n_hidden, dim, bias=False, dtype=dtype, device=device) + + def forward(self, x: torch.Tensor) -> torch.Tensor: + x = F.silu(self.c_fc1(x)) * self.c_fc2(x) + x = self.c_proj(x) + return x + + +class MultiHeadLayerNorm(nn.Module): + def __init__(self, hidden_size=None, eps=1e-5, dtype=None, device=None): + # Copy pasta from https://github.com/huggingface/transformers/blob/e5f71ecaae50ea476d1e12351003790273c4b2ed/src/transformers/models/cohere/modeling_cohere.py#L78 + + super().__init__() + self.weight = nn.Parameter(torch.empty(hidden_size, dtype=dtype, device=device)) + self.variance_epsilon = eps + + def forward(self, hidden_states): + input_dtype = hidden_states.dtype + hidden_states = hidden_states.to(torch.float32) + mean = hidden_states.mean(-1, keepdim=True) + variance = (hidden_states - mean).pow(2).mean(-1, keepdim=True) + hidden_states = (hidden_states - mean) * torch.rsqrt( + variance + self.variance_epsilon + ) + hidden_states = self.weight.to(torch.float32) * hidden_states + return hidden_states.to(input_dtype) + +class SingleAttention(nn.Module): + def __init__(self, dim, n_heads, mh_qknorm=False, dtype=None, device=None, operations=None): + super().__init__() + + self.n_heads = n_heads + self.head_dim = dim // n_heads + + # this is for cond + self.w1q = operations.Linear(dim, dim, bias=False, dtype=dtype, device=device) + self.w1k = operations.Linear(dim, dim, bias=False, dtype=dtype, device=device) + self.w1v = operations.Linear(dim, dim, bias=False, dtype=dtype, device=device) + self.w1o = operations.Linear(dim, dim, bias=False, dtype=dtype, device=device) + + self.q_norm1 = ( + MultiHeadLayerNorm((self.n_heads, self.head_dim), dtype=dtype, device=device) + if mh_qknorm + else operations.LayerNorm(self.head_dim, elementwise_affine=False, dtype=dtype, device=device) + ) + self.k_norm1 = ( + MultiHeadLayerNorm((self.n_heads, self.head_dim), dtype=dtype, device=device) + if mh_qknorm + else operations.LayerNorm(self.head_dim, elementwise_affine=False, dtype=dtype, device=device) + ) + + #@torch.compile() + def forward(self, c): + + bsz, seqlen1, _ = c.shape + + q, k, v = self.w1q(c), self.w1k(c), self.w1v(c) + q = q.view(bsz, seqlen1, self.n_heads, self.head_dim) + k = k.view(bsz, seqlen1, self.n_heads, self.head_dim) + v = v.view(bsz, seqlen1, self.n_heads, self.head_dim) + q, k = self.q_norm1(q), self.k_norm1(k) + + output = optimized_attention(q.permute(0, 2, 1, 3), k.permute(0, 2, 1, 3), v.permute(0, 2, 1, 3), self.n_heads, skip_reshape=True) + c = self.w1o(output) + return c + + + +class DoubleAttention(nn.Module): + def __init__(self, dim, n_heads, mh_qknorm=False, dtype=None, device=None, operations=None): + super().__init__() + + self.n_heads = n_heads + self.head_dim = dim // n_heads + + # this is for cond + self.w1q = operations.Linear(dim, dim, bias=False, dtype=dtype, device=device) + self.w1k = operations.Linear(dim, dim, bias=False, dtype=dtype, device=device) + self.w1v = operations.Linear(dim, dim, bias=False, dtype=dtype, device=device) + self.w1o = operations.Linear(dim, dim, bias=False, dtype=dtype, device=device) + + # this is for x + self.w2q = operations.Linear(dim, dim, bias=False, dtype=dtype, device=device) + self.w2k = operations.Linear(dim, dim, bias=False, dtype=dtype, device=device) + self.w2v = operations.Linear(dim, dim, bias=False, dtype=dtype, device=device) + self.w2o = operations.Linear(dim, dim, bias=False, dtype=dtype, device=device) + + self.q_norm1 = ( + MultiHeadLayerNorm((self.n_heads, self.head_dim), dtype=dtype, device=device) + if mh_qknorm + else operations.LayerNorm(self.head_dim, elementwise_affine=False, dtype=dtype, device=device) + ) + self.k_norm1 = ( + MultiHeadLayerNorm((self.n_heads, self.head_dim), dtype=dtype, device=device) + if mh_qknorm + else operations.LayerNorm(self.head_dim, elementwise_affine=False, dtype=dtype, device=device) + ) + + self.q_norm2 = ( + MultiHeadLayerNorm((self.n_heads, self.head_dim), dtype=dtype, device=device) + if mh_qknorm + else operations.LayerNorm(self.head_dim, elementwise_affine=False, dtype=dtype, device=device) + ) + self.k_norm2 = ( + MultiHeadLayerNorm((self.n_heads, self.head_dim), dtype=dtype, device=device) + if mh_qknorm + else operations.LayerNorm(self.head_dim, elementwise_affine=False, dtype=dtype, device=device) + ) + + + #@torch.compile() + def forward(self, c, x): + + bsz, seqlen1, _ = c.shape + bsz, seqlen2, _ = x.shape + seqlen = seqlen1 + seqlen2 + + cq, ck, cv = self.w1q(c), self.w1k(c), self.w1v(c) + cq = cq.view(bsz, seqlen1, self.n_heads, self.head_dim) + ck = ck.view(bsz, seqlen1, self.n_heads, self.head_dim) + cv = cv.view(bsz, seqlen1, self.n_heads, self.head_dim) + cq, ck = self.q_norm1(cq), self.k_norm1(ck) + + xq, xk, xv = self.w2q(x), self.w2k(x), self.w2v(x) + xq = xq.view(bsz, seqlen2, self.n_heads, self.head_dim) + xk = xk.view(bsz, seqlen2, self.n_heads, self.head_dim) + xv = xv.view(bsz, seqlen2, self.n_heads, self.head_dim) + xq, xk = self.q_norm2(xq), self.k_norm2(xk) + + # concat all + q, k, v = ( + torch.cat([cq, xq], dim=1), + torch.cat([ck, xk], dim=1), + torch.cat([cv, xv], dim=1), + ) + + output = optimized_attention(q.permute(0, 2, 1, 3), k.permute(0, 2, 1, 3), v.permute(0, 2, 1, 3), self.n_heads, skip_reshape=True) + + c, x = output.split([seqlen1, seqlen2], dim=1) + c = self.w1o(c) + x = self.w2o(x) + + return c, x + + +class MMDiTBlock(nn.Module): + def __init__(self, dim, heads=8, global_conddim=1024, is_last=False, dtype=None, device=None, operations=None): + super().__init__() + + self.normC1 = operations.LayerNorm(dim, elementwise_affine=False, dtype=dtype, device=device) + self.normC2 = operations.LayerNorm(dim, elementwise_affine=False, dtype=dtype, device=device) + if not is_last: + self.mlpC = MLP(dim, hidden_dim=dim * 4, dtype=dtype, device=device, operations=operations) + self.modC = nn.Sequential( + nn.SiLU(), + operations.Linear(global_conddim, 6 * dim, bias=False, dtype=dtype, device=device), + ) + else: + self.modC = nn.Sequential( + nn.SiLU(), + operations.Linear(global_conddim, 2 * dim, bias=False, dtype=dtype, device=device), + ) + + self.normX1 = operations.LayerNorm(dim, elementwise_affine=False, dtype=dtype, device=device) + self.normX2 = operations.LayerNorm(dim, elementwise_affine=False, dtype=dtype, device=device) + self.mlpX = MLP(dim, hidden_dim=dim * 4, dtype=dtype, device=device, operations=operations) + self.modX = nn.Sequential( + nn.SiLU(), + operations.Linear(global_conddim, 6 * dim, bias=False, dtype=dtype, device=device), + ) + + self.attn = DoubleAttention(dim, heads, dtype=dtype, device=device, operations=operations) + self.is_last = is_last + + #@torch.compile() + def forward(self, c, x, global_cond, **kwargs): + + cres, xres = c, x + + cshift_msa, cscale_msa, cgate_msa, cshift_mlp, cscale_mlp, cgate_mlp = ( + self.modC(global_cond).chunk(6, dim=1) + ) + + c = modulate(self.normC1(c), cshift_msa, cscale_msa) + + # xpath + xshift_msa, xscale_msa, xgate_msa, xshift_mlp, xscale_mlp, xgate_mlp = ( + self.modX(global_cond).chunk(6, dim=1) + ) + + x = modulate(self.normX1(x), xshift_msa, xscale_msa) + + # attention + c, x = self.attn(c, x) + + + c = self.normC2(cres + cgate_msa.unsqueeze(1) * c) + c = cgate_mlp.unsqueeze(1) * self.mlpC(modulate(c, cshift_mlp, cscale_mlp)) + c = cres + c + + x = self.normX2(xres + xgate_msa.unsqueeze(1) * x) + x = xgate_mlp.unsqueeze(1) * self.mlpX(modulate(x, xshift_mlp, xscale_mlp)) + x = xres + x + + return c, x + +class DiTBlock(nn.Module): + # like MMDiTBlock, but it only has X + def __init__(self, dim, heads=8, global_conddim=1024, dtype=None, device=None, operations=None): + super().__init__() + + self.norm1 = operations.LayerNorm(dim, elementwise_affine=False, dtype=dtype, device=device) + self.norm2 = operations.LayerNorm(dim, elementwise_affine=False, dtype=dtype, device=device) + + self.modCX = nn.Sequential( + nn.SiLU(), + operations.Linear(global_conddim, 6 * dim, bias=False, dtype=dtype, device=device), + ) + + self.attn = SingleAttention(dim, heads, dtype=dtype, device=device, operations=operations) + self.mlp = MLP(dim, hidden_dim=dim * 4, dtype=dtype, device=device, operations=operations) + + #@torch.compile() + def forward(self, cx, global_cond, **kwargs): + cxres = cx + shift_msa, scale_msa, gate_msa, shift_mlp, scale_mlp, gate_mlp = self.modCX( + global_cond + ).chunk(6, dim=1) + cx = modulate(self.norm1(cx), shift_msa, scale_msa) + cx = self.attn(cx) + cx = self.norm2(cxres + gate_msa.unsqueeze(1) * cx) + mlpout = self.mlp(modulate(cx, shift_mlp, scale_mlp)) + cx = gate_mlp.unsqueeze(1) * mlpout + + cx = cxres + cx + + return cx + + + +class TimestepEmbedder(nn.Module): + def __init__(self, hidden_size, frequency_embedding_size=256, dtype=None, device=None, operations=None): + super().__init__() + self.mlp = nn.Sequential( + operations.Linear(frequency_embedding_size, hidden_size, dtype=dtype, device=device), + nn.SiLU(), + operations.Linear(hidden_size, hidden_size, dtype=dtype, device=device), + ) + self.frequency_embedding_size = frequency_embedding_size + + @staticmethod + def timestep_embedding(t, dim, max_period=10000): + half = dim // 2 + freqs = 1000 * torch.exp( + -math.log(max_period) * torch.arange(start=0, end=half) / half + ).to(t.device) + args = t[:, None] * freqs[None] + embedding = torch.cat([torch.cos(args), torch.sin(args)], dim=-1) + if dim % 2: + embedding = torch.cat( + [embedding, torch.zeros_like(embedding[:, :1])], dim=-1 + ) + return embedding + + #@torch.compile() + def forward(self, t, dtype): + t_freq = self.timestep_embedding(t, self.frequency_embedding_size).to(dtype) + t_emb = self.mlp(t_freq) + return t_emb + + +class MMDiT(nn.Module): + def __init__( + self, + in_channels=4, + out_channels=4, + patch_size=2, + dim=3072, + n_layers=36, + n_double_layers=4, + n_heads=12, + global_conddim=3072, + cond_seq_dim=2048, + max_seq=32 * 32, + device=None, + dtype=None, + operations=None, + ): + super().__init__() + self.dtype = dtype + + self.t_embedder = TimestepEmbedder(global_conddim, dtype=dtype, device=device, operations=operations) + + self.cond_seq_linear = operations.Linear( + cond_seq_dim, dim, bias=False, dtype=dtype, device=device + ) # linear for something like text sequence. + self.init_x_linear = operations.Linear( + patch_size * patch_size * in_channels, dim, dtype=dtype, device=device + ) # init linear for patchified image. + + self.positional_encoding = nn.Parameter(torch.empty(1, max_seq, dim, dtype=dtype, device=device)) + self.register_tokens = nn.Parameter(torch.empty(1, 8, dim, dtype=dtype, device=device)) + + self.double_layers = nn.ModuleList([]) + self.single_layers = nn.ModuleList([]) + + + for idx in range(n_double_layers): + self.double_layers.append( + MMDiTBlock(dim, n_heads, global_conddim, is_last=(idx == n_layers - 1), dtype=dtype, device=device, operations=operations) + ) + + for idx in range(n_double_layers, n_layers): + self.single_layers.append( + DiTBlock(dim, n_heads, global_conddim, dtype=dtype, device=device, operations=operations) + ) + + + self.final_linear = operations.Linear( + dim, patch_size * patch_size * out_channels, bias=False, dtype=dtype, device=device + ) + + self.modF = nn.Sequential( + nn.SiLU(), + operations.Linear(global_conddim, 2 * dim, bias=False, dtype=dtype, device=device), + ) + + self.out_channels = out_channels + self.patch_size = patch_size + self.n_double_layers = n_double_layers + self.n_layers = n_layers + + self.h_max = round(max_seq**0.5) + self.w_max = round(max_seq**0.5) + + @torch.no_grad() + def extend_pe(self, init_dim=(16, 16), target_dim=(64, 64)): + # extend pe + pe_data = self.positional_encoding.data.squeeze(0)[: init_dim[0] * init_dim[1]] + + pe_as_2d = pe_data.view(init_dim[0], init_dim[1], -1).permute(2, 0, 1) + + # now we need to extend this to target_dim. for this we will use interpolation. + # we will use torch.nn.functional.interpolate + pe_as_2d = F.interpolate( + pe_as_2d.unsqueeze(0), size=target_dim, mode="bilinear" + ) + pe_new = pe_as_2d.squeeze(0).permute(1, 2, 0).flatten(0, 1) + self.positional_encoding.data = pe_new.unsqueeze(0).contiguous() + self.h_max, self.w_max = target_dim + print("PE extended to", target_dim) + + def pe_selection_index_based_on_dim(self, h, w): + h_p, w_p = h // self.patch_size, w // self.patch_size + original_pe_indexes = torch.arange(self.positional_encoding.shape[1]) + original_pe_indexes = original_pe_indexes.view(self.h_max, self.w_max) + starth = self.h_max // 2 - h_p // 2 + endh =starth + h_p + startw = self.w_max // 2 - w_p // 2 + endw = startw + w_p + original_pe_indexes = original_pe_indexes[ + starth:endh, startw:endw + ] + return original_pe_indexes.flatten() + + def unpatchify(self, x, h, w): + c = self.out_channels + p = self.patch_size + + x = x.reshape(shape=(x.shape[0], h, w, p, p, c)) + x = torch.einsum("nhwpqc->nchpwq", x) + imgs = x.reshape(shape=(x.shape[0], c, h * p, w * p)) + return imgs + + def patchify(self, x): + B, C, H, W = x.size() + pad_h = (self.patch_size - H % self.patch_size) % self.patch_size + pad_w = (self.patch_size - W % self.patch_size) % self.patch_size + + x = torch.nn.functional.pad(x, (0, pad_w, 0, pad_h), mode='reflect') + x = x.view( + B, + C, + (H + 1) // self.patch_size, + self.patch_size, + (W + 1) // self.patch_size, + self.patch_size, + ) + x = x.permute(0, 2, 4, 1, 3, 5).flatten(-3).flatten(1, 2) + return x + + def apply_pos_embeds(self, x, h, w): + h = (h + 1) // self.patch_size + w = (w + 1) // self.patch_size + max_dim = max(h, w) + + cur_dim = self.h_max + pos_encoding = self.positional_encoding.reshape(1, cur_dim, cur_dim, -1).to(device=x.device, dtype=x.dtype) + + if max_dim > cur_dim: + pos_encoding = F.interpolate(pos_encoding.movedim(-1, 1), (max_dim, max_dim), mode="bilinear").movedim(1, -1) + cur_dim = max_dim + + from_h = (cur_dim - h) // 2 + from_w = (cur_dim - w) // 2 + pos_encoding = pos_encoding[:,from_h:from_h+h,from_w:from_w+w] + return x + pos_encoding.reshape(1, -1, self.positional_encoding.shape[-1]) + + def forward(self, x, timestep, context, **kwargs): + # patchify x, add PE + b, c, h, w = x.shape + + # pe_indexes = self.pe_selection_index_based_on_dim(h, w) + # print(pe_indexes, pe_indexes.shape) + + x = self.init_x_linear(self.patchify(x)) # B, T_x, D + x = self.apply_pos_embeds(x, h, w) + # x = x + self.positional_encoding[:, : x.size(1)].to(device=x.device, dtype=x.dtype) + # x = x + self.positional_encoding[:, pe_indexes].to(device=x.device, dtype=x.dtype) + + # process conditions for MMDiT Blocks + c_seq = context # B, T_c, D_c + t = timestep + + c = self.cond_seq_linear(c_seq) # B, T_c, D + c = torch.cat([self.register_tokens.to(device=c.device, dtype=c.dtype).repeat(c.size(0), 1, 1), c], dim=1) + + global_cond = self.t_embedder(t, x.dtype) # B, D + + if len(self.double_layers) > 0: + for layer in self.double_layers: + c, x = layer(c, x, global_cond, **kwargs) + + if len(self.single_layers) > 0: + c_len = c.size(1) + cx = torch.cat([c, x], dim=1) + for layer in self.single_layers: + cx = layer(cx, global_cond, **kwargs) + + x = cx[:, c_len:] + + fshift, fscale = self.modF(global_cond).chunk(2, dim=1) + + x = modulate(x, fshift, fscale) + x = self.final_linear(x) + x = self.unpatchify(x, (h + 1) // self.patch_size, (w + 1) // self.patch_size)[:,:,:h,:w] + return x diff --git a/comfy/model_base.py b/comfy/model_base.py index 80f6667ec..0e0e69d3b 100644 --- a/comfy/model_base.py +++ b/comfy/model_base.py @@ -6,6 +6,7 @@ from comfy.ldm.cascade.stage_b import StageB from comfy.ldm.modules.encoders.noise_aug_modules import CLIPEmbeddingNoiseAugmentation from comfy.ldm.modules.diffusionmodules.upscaling import ImageConcatWithNoiseAugmentation from comfy.ldm.modules.diffusionmodules.mmdit import OpenAISignatureMMDITWrapper +import comfy.ldm.aura.mmdit import comfy.ldm.audio.dit import comfy.ldm.audio.embedders import comfy.model_management @@ -598,6 +599,17 @@ class SD3(BaseModel): area = input_shape[0] * input_shape[2] * input_shape[3] return (area * 0.3) * (1024 * 1024) +class AuraFlow(BaseModel): + def __init__(self, model_config, model_type=ModelType.FLOW, device=None): + super().__init__(model_config, model_type, device=device, unet_model=comfy.ldm.aura.mmdit.MMDiT) + + def extra_conds(self, **kwargs): + out = super().extra_conds(**kwargs) + cross_attn = kwargs.get("cross_attn", None) + if cross_attn is not None: + out['c_crossattn'] = comfy.conds.CONDRegular(cross_attn) + return out + class StableAudio1(BaseModel): def __init__(self, model_config, seconds_start_embedder_weights, seconds_total_embedder_weights, model_type=ModelType.V_PREDICTION_CONTINUOUS, device=None): diff --git a/comfy/model_detection.py b/comfy/model_detection.py index 783a03eb7..dd5bff82a 100644 --- a/comfy/model_detection.py +++ b/comfy/model_detection.py @@ -105,6 +105,12 @@ def detect_unet_config(state_dict, key_prefix): unet_config["audio_model"] = "dit1.0" return unet_config + if '{}double_layers.0.attn.w1q.weight'.format(key_prefix) in state_dict_keys: #aura flow dit + unet_config = {} + unet_config["max_seq"] = state_dict['{}positional_encoding'.format(key_prefix)].shape[1] + unet_config["cond_seq_dim"] = state_dict['{}cond_seq_linear.weight'.format(key_prefix)].shape[1] + return unet_config + if '{}input_blocks.0.0.weight'.format(key_prefix) not in state_dict_keys: return None @@ -253,6 +259,8 @@ def model_config_from_unet(state_dict, unet_key_prefix, use_base_if_no_match=Fal def unet_prefix_from_state_dict(state_dict): if "model.model.postprocess_conv.weight" in state_dict: #audio models unet_key_prefix = "model.model." + elif "model.double_layers.0.attn.w1q.weight" in state_dict: #aura flow + unet_key_prefix = "model." else: unet_key_prefix = "model.diffusion_model." return unet_key_prefix diff --git a/comfy/sd.py b/comfy/sd.py index eeffa423a..6028029d6 100644 --- a/comfy/sd.py +++ b/comfy/sd.py @@ -21,6 +21,7 @@ from . import sd2_clip from . import sdxl_clip from . import sd3_clip from . import sa_t5 +import comfy.text_encoders.aura_t5 import comfy.model_patcher import comfy.lora @@ -415,6 +416,9 @@ def load_clip(ckpt_paths, embedding_directory=None, clip_type=CLIPType.STABLE_DI if weight.shape[-1] == 4096: clip_target.clip = sd3_clip.sd3_clip(clip_l=False, clip_g=False, t5=True, dtype_t5=dtype_t5) clip_target.tokenizer = sd3_clip.SD3Tokenizer + elif weight.shape[-1] == 2048: + clip_target.clip = comfy.text_encoders.aura_t5.AuraT5Model + clip_target.tokenizer = comfy.text_encoders.aura_t5.AuraT5Tokenizer elif "encoder.block.0.layer.0.SelfAttention.k.weight" in clip_data[0]: clip_target.clip = sa_t5.SAT5Model clip_target.tokenizer = sa_t5.SAT5Tokenizer diff --git a/comfy/supported_models.py b/comfy/supported_models.py index 21fdb7ec7..ccf8c333e 100644 --- a/comfy/supported_models.py +++ b/comfy/supported_models.py @@ -7,6 +7,7 @@ from . import sd2_clip from . import sdxl_clip from . import sd3_clip from . import sa_t5 +import comfy.text_encoders.aura_t5 from . import supported_models_base from . import latent_formats @@ -556,7 +557,28 @@ class StableAudio(supported_models_base.BASE): def clip_target(self, state_dict={}): return supported_models_base.ClipTarget(sa_t5.SAT5Tokenizer, sa_t5.SAT5Model) +class AuraFlow(supported_models_base.BASE): + unet_config = { + "cond_seq_dim": 2048, + } -models = [Stable_Zero123, SD15_instructpix2pix, SD15, SD20, SD21UnclipL, SD21UnclipH, SDXL_instructpix2pix, SDXLRefiner, SDXL, SSD1B, KOALA_700M, KOALA_1B, Segmind_Vega, SD_X4Upscaler, Stable_Cascade_C, Stable_Cascade_B, SV3D_u, SV3D_p, SD3, StableAudio] + sampling_settings = { + "multiplier": 1.0, + } + + unet_extra_config = {} + latent_format = latent_formats.SDXL + + vae_key_prefix = ["vae."] + text_encoder_key_prefix = ["text_encoders."] + + def get_model(self, state_dict, prefix="", device=None): + out = model_base.AuraFlow(self, device=device) + return out + + def clip_target(self, state_dict={}): + return supported_models_base.ClipTarget(comfy.text_encoders.aura_t5.AuraT5Tokenizer, comfy.text_encoders.aura_t5.AuraT5Model) + +models = [Stable_Zero123, SD15_instructpix2pix, SD15, SD20, SD21UnclipL, SD21UnclipH, SDXL_instructpix2pix, SDXLRefiner, SDXL, SSD1B, KOALA_700M, KOALA_1B, Segmind_Vega, SD_X4Upscaler, Stable_Cascade_C, Stable_Cascade_B, SV3D_u, SV3D_p, SD3, StableAudio, AuraFlow] models += [SVD_img2vid] diff --git a/comfy/text_encoders/aura_t5.py b/comfy/text_encoders/aura_t5.py new file mode 100644 index 000000000..0e84189aa --- /dev/null +++ b/comfy/text_encoders/aura_t5.py @@ -0,0 +1,22 @@ +from comfy import sd1_clip +from transformers import LlamaTokenizerFast +import comfy.t5 +import os + +class PT5XlModel(sd1_clip.SDClipModel): + def __init__(self, device="cpu", layer="last", layer_idx=None, dtype=None): + textmodel_json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "t5_pile_config_xl.json") + super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, dtype=dtype, special_tokens={"end": 2, "pad": 1}, model_class=comfy.t5.T5, enable_attention_masks=True, zero_out_masked=True) + +class PT5XlTokenizer(sd1_clip.SDTokenizer): + def __init__(self, embedding_directory=None): + tokenizer_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "t5_pile_tokenizer") + super().__init__(tokenizer_path, pad_with_end=False, embedding_size=2048, embedding_key='pile_t5xl', tokenizer_class=LlamaTokenizerFast, has_start_token=False, pad_to_max_length=False, max_length=99999999, min_length=256, pad_token=1) + +class AuraT5Tokenizer(sd1_clip.SD1Tokenizer): + def __init__(self, embedding_directory=None): + super().__init__(embedding_directory=embedding_directory, clip_name="pile_t5xl", tokenizer=PT5XlTokenizer) + +class AuraT5Model(sd1_clip.SD1ClipModel): + def __init__(self, device="cpu", dtype=None, **kwargs): + super().__init__(device=device, dtype=dtype, name="pile_t5xl", clip_model=PT5XlModel, **kwargs) diff --git a/comfy/text_encoders/t5_pile_config_xl.json b/comfy/text_encoders/t5_pile_config_xl.json new file mode 100644 index 000000000..ee4e03f97 --- /dev/null +++ b/comfy/text_encoders/t5_pile_config_xl.json @@ -0,0 +1,22 @@ +{ + "d_ff": 5120, + "d_kv": 64, + "d_model": 2048, + "decoder_start_token_id": 0, + "dropout_rate": 0.1, + "eos_token_id": 2, + "dense_act_fn": "gelu_pytorch_tanh", + "initializer_factor": 1.0, + "is_encoder_decoder": true, + "is_gated_act": true, + "layer_norm_epsilon": 1e-06, + "model_type": "umt5", + "num_decoder_layers": 24, + "num_heads": 32, + "num_layers": 24, + "output_past": true, + "pad_token_id": 1, + "relative_attention_num_buckets": 32, + "tie_word_embeddings": false, + "vocab_size": 32128 +} diff --git a/comfy/text_encoders/t5_pile_tokenizer/added_tokens.json b/comfy/text_encoders/t5_pile_tokenizer/added_tokens.json new file mode 100644 index 000000000..3f5132007 --- /dev/null +++ b/comfy/text_encoders/t5_pile_tokenizer/added_tokens.json @@ -0,0 +1,102 @@ +{ + "": 32099, + "": 32089, + "": 32088, + "": 32087, + "": 32086, + "": 32085, + "": 32084, + "": 32083, + "": 32082, + "": 32081, + "": 32080, + "": 32098, + "": 32079, + "": 32078, + "": 32077, + "": 32076, + "": 32075, + "": 32074, + "": 32073, + "": 32072, + "": 32071, + "": 32070, + "": 32097, + "": 32069, + "": 32068, + "": 32067, + "": 32066, + "": 32065, + "": 32064, + "": 32063, + "": 32062, + "": 32061, + "": 32060, + "": 32096, + "": 32059, + "": 32058, + "": 32057, + "": 32056, + "": 32055, + "": 32054, + "": 32053, + "": 32052, + "": 32051, + "": 32050, + "": 32095, + "": 32049, + "": 32048, + "": 32047, + "": 32046, + "": 32045, + "": 32044, + "": 32043, + "": 32042, + "": 32041, + "": 32040, + "": 32094, + "": 32039, + "": 32038, + "": 32037, + "": 32036, + "": 32035, + "": 32034, + "": 32033, + "": 32032, + "": 32031, + "": 32030, + "": 32093, + "": 32029, + "": 32028, + "": 32027, + "": 32026, + "": 32025, + "": 32024, + "": 32023, + "": 32022, + "": 32021, + "": 32020, + "": 32092, + "": 32019, + "": 32018, + "": 32017, + "": 32016, + "": 32015, + "": 32014, + "": 32013, + "": 32012, + "": 32011, + "": 32010, + "": 32091, + "": 32009, + "": 32008, + "": 32007, + "": 32006, + "": 32005, + "": 32004, + "": 32003, + "": 32002, + "": 32001, + "": 32000, + "": 32090 +} diff --git a/comfy/text_encoders/t5_pile_tokenizer/special_tokens_map.json b/comfy/text_encoders/t5_pile_tokenizer/special_tokens_map.json new file mode 100644 index 000000000..19fb1d5f4 --- /dev/null +++ b/comfy/text_encoders/t5_pile_tokenizer/special_tokens_map.json @@ -0,0 +1,125 @@ +{ + "additional_special_tokens": [ + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", 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false, + "special": true + }, + "32087": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "32088": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "32089": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "32090": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "32091": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "32092": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "32093": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "32094": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "32095": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "32096": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "32097": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "32098": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "32099": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + } + }, + "additional_special_tokens": [ + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "", + "" + ], + "bos_token": "", + "clean_up_tokenization_spaces": false, + "eos_token": "", + "legacy": false, + "model_max_length": 512, + "pad_token": null, + "padding_side": "right", + "sp_model_kwargs": {}, + "spaces_between_special_tokens": false, + "tokenizer_class": "LlamaTokenizer", + "unk_token": "", + "use_default_system_prompt": false +} diff --git a/requirements.txt b/requirements.txt index 108958d2f..6febc3d68 100644 --- a/requirements.txt +++ b/requirements.txt @@ -3,7 +3,8 @@ torchsde torchvision torchaudio einops -transformers>=4.25.1 +transformers>=4.28.1 +tokenizers>=0.13.3 safetensors>=0.4.2 aiohttp pyyaml From 8e012043a9d0af3979bbe2cea8dc1ec7768f9d88 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Thu, 11 Jul 2024 17:51:56 -0400 Subject: [PATCH 077/133] Add a ModelSamplingAuraFlow node to change the shift value. Set the default AuraFlow shift value to 1.73 (sqrt(3)). --- comfy/supported_models.py | 1 + comfy_extras/nodes_model_advanced.py | 17 +++++++++++++++-- 2 files changed, 16 insertions(+), 2 deletions(-) diff --git a/comfy/supported_models.py b/comfy/supported_models.py index ccf8c333e..a030f6229 100644 --- a/comfy/supported_models.py +++ b/comfy/supported_models.py @@ -564,6 +564,7 @@ class AuraFlow(supported_models_base.BASE): sampling_settings = { "multiplier": 1.0, + "shift": 1.73, } unet_extra_config = {} diff --git a/comfy_extras/nodes_model_advanced.py b/comfy_extras/nodes_model_advanced.py index 97559cf56..22ba9547b 100644 --- a/comfy_extras/nodes_model_advanced.py +++ b/comfy_extras/nodes_model_advanced.py @@ -144,7 +144,7 @@ class ModelSamplingSD3: CATEGORY = "advanced/model" - def patch(self, model, shift): + def patch(self, model, shift, multiplier=1000): m = model.clone() sampling_base = comfy.model_sampling.ModelSamplingDiscreteFlow @@ -154,10 +154,22 @@ class ModelSamplingSD3: pass model_sampling = ModelSamplingAdvanced(model.model.model_config) - model_sampling.set_parameters(shift=shift) + model_sampling.set_parameters(shift=shift, multiplier=multiplier) m.add_object_patch("model_sampling", model_sampling) return (m, ) +class ModelSamplingAuraFlow(ModelSamplingSD3): + @classmethod + def INPUT_TYPES(s): + return {"required": { "model": ("MODEL",), + "shift": ("FLOAT", {"default": 1.73, "min": 0.0, "max": 100.0, "step":0.01}), + }} + + FUNCTION = "patch_aura" + + def patch_aura(self, model, shift): + return self.patch(model, shift, multiplier=1.0) + class ModelSamplingContinuousEDM: @classmethod def INPUT_TYPES(s): @@ -271,5 +283,6 @@ NODE_CLASS_MAPPINGS = { "ModelSamplingContinuousV": ModelSamplingContinuousV, "ModelSamplingStableCascade": ModelSamplingStableCascade, "ModelSamplingSD3": ModelSamplingSD3, + "ModelSamplingAuraFlow": ModelSamplingAuraFlow, "RescaleCFG": RescaleCFG, } From b6f09cf649a8e06783f148a0f5824405ed460003 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Thu, 11 Jul 2024 22:58:03 -0400 Subject: [PATCH 078/133] Add sentencepiece dependency. --- requirements.txt | 1 + 1 file changed, 1 insertion(+) diff --git a/requirements.txt b/requirements.txt index 6febc3d68..4c2c0b2b2 100644 --- a/requirements.txt +++ b/requirements.txt @@ -5,6 +5,7 @@ torchaudio einops transformers>=4.28.1 tokenizers>=0.13.3 +sentencepiece safetensors>=0.4.2 aiohttp pyyaml From 29c2e26724d4982a3e33114eb9064f1a11f4f4ed Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Fri, 12 Jul 2024 01:08:45 -0400 Subject: [PATCH 079/133] Better tokenizing code for AuraFlow. --- comfy/text_encoders/aura_t5.py | 6 +- comfy/text_encoders/llama_tokenizer.py | 22 + .../t5_pile_tokenizer/added_tokens.json | 102 -- .../t5_pile_tokenizer/special_tokens_map.json | 125 --- .../t5_pile_tokenizer/tokenizer_config.json | 945 ------------------ 5 files changed, 25 insertions(+), 1175 deletions(-) create mode 100644 comfy/text_encoders/llama_tokenizer.py delete mode 100644 comfy/text_encoders/t5_pile_tokenizer/added_tokens.json delete mode 100644 comfy/text_encoders/t5_pile_tokenizer/special_tokens_map.json delete mode 100644 comfy/text_encoders/t5_pile_tokenizer/tokenizer_config.json diff --git a/comfy/text_encoders/aura_t5.py b/comfy/text_encoders/aura_t5.py index 0e84189aa..95f942ef5 100644 --- a/comfy/text_encoders/aura_t5.py +++ b/comfy/text_encoders/aura_t5.py @@ -1,5 +1,5 @@ from comfy import sd1_clip -from transformers import LlamaTokenizerFast +from .llama_tokenizer import LLAMATokenizer import comfy.t5 import os @@ -10,8 +10,8 @@ class PT5XlModel(sd1_clip.SDClipModel): class PT5XlTokenizer(sd1_clip.SDTokenizer): def __init__(self, embedding_directory=None): - tokenizer_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "t5_pile_tokenizer") - super().__init__(tokenizer_path, pad_with_end=False, embedding_size=2048, embedding_key='pile_t5xl', tokenizer_class=LlamaTokenizerFast, has_start_token=False, pad_to_max_length=False, max_length=99999999, min_length=256, pad_token=1) + tokenizer_path = os.path.join(os.path.join(os.path.dirname(os.path.realpath(__file__)), "t5_pile_tokenizer"), "tokenizer.model") + super().__init__(tokenizer_path, pad_with_end=False, embedding_size=2048, embedding_key='pile_t5xl', tokenizer_class=LLAMATokenizer, has_start_token=False, pad_to_max_length=False, max_length=99999999, min_length=256, pad_token=1) class AuraT5Tokenizer(sd1_clip.SD1Tokenizer): def __init__(self, embedding_directory=None): diff --git a/comfy/text_encoders/llama_tokenizer.py b/comfy/text_encoders/llama_tokenizer.py new file mode 100644 index 000000000..a6db1da62 --- /dev/null +++ b/comfy/text_encoders/llama_tokenizer.py @@ -0,0 +1,22 @@ +import os + +class LLAMATokenizer: + @staticmethod + def from_pretrained(path): + return LLAMATokenizer(path) + + def __init__(self, tokenizer_path): + import sentencepiece + self.tokenizer = sentencepiece.SentencePieceProcessor(model_file=tokenizer_path) + self.end = self.tokenizer.eos_id() + + def get_vocab(self): + out = {} + for i in range(self.tokenizer.get_piece_size()): + out[self.tokenizer.id_to_piece(i)] = i + return out + + def __call__(self, string): + out = self.tokenizer.encode(string) + out += [self.end] + return {"input_ids": out} diff --git a/comfy/text_encoders/t5_pile_tokenizer/added_tokens.json b/comfy/text_encoders/t5_pile_tokenizer/added_tokens.json deleted file mode 100644 index 3f5132007..000000000 --- a/comfy/text_encoders/t5_pile_tokenizer/added_tokens.json +++ /dev/null @@ -1,102 +0,0 @@ -{ - 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"unk_token": "", - "use_default_system_prompt": false -} From 4ca9b9cc29fefaa899cba67d61a8252ae9f16c0d Mon Sep 17 00:00:00 2001 From: Robin Huang Date: Fri, 12 Jul 2024 10:33:57 -0700 Subject: [PATCH 080/133] Add Github Workflow for releasing stable versions and standalone bundle. (#3949) * Add stable release. * Only build CUDA 12.1 + 3.11 Python. * Upgrade checkout and setup-python to latest version. * lzma2 * Update artifact name to be ComfyUI_windows_portable_nvidia.7z --- .github/workflows/stable-release.yml | 109 +++++++++++++++++++++++++++ 1 file changed, 109 insertions(+) create mode 100644 .github/workflows/stable-release.yml diff --git a/.github/workflows/stable-release.yml b/.github/workflows/stable-release.yml new file mode 100644 index 000000000..1fd76b530 --- /dev/null +++ b/.github/workflows/stable-release.yml @@ -0,0 +1,109 @@ + +name: "Release Stable Version" + +on: + push: + tags: + - 'v*' + +jobs: + package_comfy_windows: + permissions: + contents: "write" + packages: "write" + pull-requests: "read" + runs-on: windows-latest + strategy: + matrix: + python_version: [3.11.8] + cuda_version: [121] + steps: + - name: Calculate Minor Version + shell: bash + run: | + # Extract the minor version from the Python version + MINOR_VERSION=$(echo "${{ matrix.python_version }}" | cut -d'.' -f2) + echo "MINOR_VERSION=$MINOR_VERSION" >> $GITHUB_ENV + - name: Setup Python + uses: actions/setup-python@v5 + with: + python-version: ${{ matrix.python_version }} + + - uses: actions/checkout@v4 + with: + fetch-depth: 0 + persist-credentials: false + - shell: bash + run: | + echo "@echo off + call update_comfyui.bat nopause + echo - + echo This will try to update pytorch and all python dependencies. + echo - + echo If you just want to update normally, close this and run update_comfyui.bat instead. + echo - + pause + ..\python_embeded\python.exe -s -m pip install --upgrade torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu${{ matrix.cuda_version }} -r ../ComfyUI/requirements.txt pygit2 + pause" > update_comfyui_and_python_dependencies.bat + + python -m pip wheel --no-cache-dir torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu${{ matrix.cuda_version }} -r requirements.txt pygit2 -w ./temp_wheel_dir + python -m pip install --no-cache-dir ./temp_wheel_dir/* + echo installed basic + ls -lah temp_wheel_dir + mv temp_wheel_dir cu${{ matrix.cuda_version }}_python_deps + mv cu${{ matrix.cuda_version }}_python_deps ../ + mv update_comfyui_and_python_dependencies.bat ../ + cd .. + pwd + ls + + cp -r ComfyUI ComfyUI_copy + curl https://www.python.org/ftp/python/${{ matrix.python_version }}/python-${{ matrix.python_version }}-embed-amd64.zip -o python_embeded.zip + unzip python_embeded.zip -d python_embeded + cd python_embeded + echo ${{ env.MINOR_VERSION }} + echo 'import site' >> ./python3${{ env.MINOR_VERSION }}._pth + curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py + ./python.exe get-pip.py + ./python.exe --version + echo "Pip version:" + ./python.exe -m pip --version + + set PATH=$PWD/Scripts:$PATH + echo $PATH + ./python.exe -s -m pip install ../cu${{ matrix.cuda_version }}_python_deps/* + sed -i '1i../ComfyUI' ./python3${{ env.MINOR_VERSION }}._pth + cd .. + + git clone https://github.com/comfyanonymous/taesd + cp taesd/*.pth ./ComfyUI_copy/models/vae_approx/ + + mkdir ComfyUI_windows_portable + mv python_embeded ComfyUI_windows_portable + mv ComfyUI_copy ComfyUI_windows_portable/ComfyUI + + cd ComfyUI_windows_portable + + mkdir update + cp -r ComfyUI/.ci/update_windows/* ./update/ + cp -r ComfyUI/.ci/windows_base_files/* ./ + cp ../update_comfyui_and_python_dependencies.bat ./update/ + + cd .. + + "C:\Program Files\7-Zip\7z.exe" a -t7z -m0=lzma2 -mx=8 -mfb=64 -md=32m -ms=on -mf=BCJ2 ComfyUI_windows_portable.7z ComfyUI_windows_portable + mv ComfyUI_windows_portable.7z ComfyUI/ComfyUI_windows_portable_nvidia.7z + + cd ComfyUI_windows_portable + python_embeded/python.exe -s ComfyUI/main.py --quick-test-for-ci --cpu + + ls + + - name: Upload binaries to release + uses: svenstaro/upload-release-action@v2 + with: + repo_token: ${{ secrets.GITHUB_TOKEN }} + file: ComfyUI_windows_portable_nvidia.7z + tag: ${{ github.ref }} + overwrite: true + From ce2473bb016748a4d98e9bce02d675b4fc22f4ac Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Fri, 12 Jul 2024 15:25:07 -0400 Subject: [PATCH 081/133] Add link to AuraFlow example in Readme. --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index 35e3238a1..5f747321f 100644 --- a/README.md +++ b/README.md @@ -32,6 +32,7 @@ This ui will let you design and execute advanced stable diffusion pipelines usin - [Model Merging](https://comfyanonymous.github.io/ComfyUI_examples/model_merging/) - [LCM models and Loras](https://comfyanonymous.github.io/ComfyUI_examples/lcm/) - [SDXL Turbo](https://comfyanonymous.github.io/ComfyUI_examples/sdturbo/) +- [AuraFlow](https://comfyanonymous.github.io/ComfyUI_examples/aura_flow/) - Latent previews with [TAESD](#how-to-show-high-quality-previews) - Starts up very fast. - Works fully offline: will never download anything. From a3dffc447a7b9f4948037a988fd143eeffd87bd1 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Sat, 13 Jul 2024 13:51:40 -0400 Subject: [PATCH 082/133] Support AuraFlow Lora and loading model weights in diffusers format. You can load model weights in diffusers format using the UNETLoader node. --- comfy/lora.py | 8 +++++ comfy/model_detection.py | 66 +++++++++++++++++++++---------------- comfy/sd.py | 33 +++++++++---------- comfy/utils.py | 70 ++++++++++++++++++++++++++++++++++++++++ 4 files changed, 133 insertions(+), 44 deletions(-) diff --git a/comfy/lora.py b/comfy/lora.py index 037431775..e36b354f0 100644 --- a/comfy/lora.py +++ b/comfy/lora.py @@ -274,4 +274,12 @@ def model_lora_keys_unet(model, key_map={}): key_lora = "lora_transformer_{}".format(k[:-len(".weight")].replace(".", "_")) #OneTrainer lora key_map[key_lora] = to + if isinstance(model, comfy.model_base.AuraFlow): #Diffusers lora AuraFlow + diffusers_keys = comfy.utils.auraflow_to_diffusers(model.model_config.unet_config, output_prefix="diffusion_model.") + for k in diffusers_keys: + if k.endswith(".weight"): + to = diffusers_keys[k] + key_lora = "transformer.{}".format(k[:-len(".weight")]) #simpletrainer and probably regular diffusers lora format + key_map[key_lora] = to + return key_map diff --git a/comfy/model_detection.py b/comfy/model_detection.py index dd5bff82a..c62e2b822 100644 --- a/comfy/model_detection.py +++ b/comfy/model_detection.py @@ -109,6 +109,10 @@ def detect_unet_config(state_dict, key_prefix): unet_config = {} unet_config["max_seq"] = state_dict['{}positional_encoding'.format(key_prefix)].shape[1] unet_config["cond_seq_dim"] = state_dict['{}cond_seq_linear.weight'.format(key_prefix)].shape[1] + double_layers = count_blocks(state_dict_keys, '{}double_layers.'.format(key_prefix) + '{}.') + single_layers = count_blocks(state_dict_keys, '{}single_layers.'.format(key_prefix) + '{}.') + unet_config["n_double_layers"] = double_layers + unet_config["n_layers"] = double_layers + single_layers return unet_config if '{}input_blocks.0.0.weight'.format(key_prefix) not in state_dict_keys: @@ -450,37 +454,45 @@ def model_config_from_diffusers_unet(state_dict): return None def convert_diffusers_mmdit(state_dict, output_prefix=""): - num_blocks = count_blocks(state_dict, 'transformer_blocks.{}.') - if num_blocks > 0: + out_sd = {} + + if 'transformer_blocks.0.attn.add_q_proj.weight' in state_dict: #SD3 + num_blocks = count_blocks(state_dict, 'transformer_blocks.{}.') depth = state_dict["pos_embed.proj.weight"].shape[0] // 64 - out_sd = {} sd_map = comfy.utils.mmdit_to_diffusers({"depth": depth, "num_blocks": num_blocks}, output_prefix=output_prefix) - for k in sd_map: - weight = state_dict.get(k, None) - if weight is not None: - t = sd_map[k] + elif 'joint_transformer_blocks.0.attn.add_k_proj.weight' in state_dict: #AuraFlow + num_joint = count_blocks(state_dict, 'joint_transformer_blocks.{}.') + num_single = count_blocks(state_dict, 'single_transformer_blocks.{}.') + sd_map = comfy.utils.auraflow_to_diffusers({"n_double_layers": num_joint, "n_layers": num_joint + num_single}, output_prefix=output_prefix) + else: + return None - if not isinstance(t, str): - if len(t) > 2: - fun = t[2] - else: - fun = lambda a: a - offset = t[1] - if offset is not None: - old_weight = out_sd.get(t[0], None) - if old_weight is None: - old_weight = torch.empty_like(weight) - old_weight = old_weight.repeat([3] + [1] * (len(old_weight.shape) - 1)) + for k in sd_map: + weight = state_dict.get(k, None) + if weight is not None: + t = sd_map[k] - w = old_weight.narrow(offset[0], offset[1], offset[2]) - else: - old_weight = weight - w = weight - w[:] = fun(weight) - t = t[0] - out_sd[t] = old_weight + if not isinstance(t, str): + if len(t) > 2: + fun = t[2] else: - out_sd[t] = weight - state_dict.pop(k) + fun = lambda a: a + offset = t[1] + if offset is not None: + old_weight = out_sd.get(t[0], None) + if old_weight is None: + old_weight = torch.empty_like(weight) + old_weight = old_weight.repeat([3] + [1] * (len(old_weight.shape) - 1)) + + w = old_weight.narrow(offset[0], offset[1], offset[2]) + else: + old_weight = weight + w = weight + w[:] = fun(weight) + t = t[0] + out_sd[t] = old_weight + else: + out_sd[t] = weight + state_dict.pop(k) return out_sd diff --git a/comfy/sd.py b/comfy/sd.py index 6028029d6..b5bbcef61 100644 --- a/comfy/sd.py +++ b/comfy/sd.py @@ -562,26 +562,25 @@ def load_unet_state_dict(sd): #load unet in diffusers or regular format if model_config is not None: new_sd = sd - elif 'transformer_blocks.0.attn.add_q_proj.weight' in sd: #MMDIT SD3 + else: new_sd = model_detection.convert_diffusers_mmdit(sd, "") - if new_sd is None: - return None - model_config = model_detection.model_config_from_unet(new_sd, "") - if model_config is None: - return None - else: #diffusers - model_config = model_detection.model_config_from_diffusers_unet(sd) - if model_config is None: - return None + if new_sd is not None: #diffusers mmdit + model_config = model_detection.model_config_from_unet(new_sd, "") + if model_config is None: + return None + else: #diffusers unet + model_config = model_detection.model_config_from_diffusers_unet(sd) + if model_config is None: + return None - diffusers_keys = comfy.utils.unet_to_diffusers(model_config.unet_config) + diffusers_keys = comfy.utils.unet_to_diffusers(model_config.unet_config) - new_sd = {} - for k in diffusers_keys: - if k in sd: - new_sd[diffusers_keys[k]] = sd.pop(k) - else: - logging.warning("{} {}".format(diffusers_keys[k], k)) + new_sd = {} + for k in diffusers_keys: + if k in sd: + new_sd[diffusers_keys[k]] = sd.pop(k) + else: + logging.warning("{} {}".format(diffusers_keys[k], k)) offload_device = model_management.unet_offload_device() unet_dtype = model_management.unet_dtype(model_params=parameters, supported_dtypes=model_config.supported_inference_dtypes) diff --git a/comfy/utils.py b/comfy/utils.py index 48618e076..1e4b5ef88 100644 --- a/comfy/utils.py +++ b/comfy/utils.py @@ -332,6 +332,76 @@ def mmdit_to_diffusers(mmdit_config, output_prefix=""): return key_map + +def auraflow_to_diffusers(mmdit_config, output_prefix=""): + n_double_layers = mmdit_config.get("n_double_layers", 0) + n_layers = mmdit_config.get("n_layers", 0) + + key_map = {} + for i in range(n_layers): + if i < n_double_layers: + index = i + prefix_from = "joint_transformer_blocks" + prefix_to = "{}double_layers".format(output_prefix) + block_map = { + "attn.to_q.weight": "attn.w2q.weight", + "attn.to_k.weight": "attn.w2k.weight", + "attn.to_v.weight": "attn.w2v.weight", + "attn.to_out.0.weight": "attn.w2o.weight", + "attn.add_q_proj.weight": "attn.w1q.weight", + "attn.add_k_proj.weight": "attn.w1k.weight", + "attn.add_v_proj.weight": "attn.w1v.weight", + "attn.to_add_out.weight": "attn.w1o.weight", + "ff.linear_1.weight": "mlpX.c_fc1.weight", + "ff.linear_2.weight": "mlpX.c_fc2.weight", + "ff.out_projection.weight": "mlpX.c_proj.weight", + "ff_context.linear_1.weight": "mlpC.c_fc1.weight", + "ff_context.linear_2.weight": "mlpC.c_fc2.weight", + "ff_context.out_projection.weight": "mlpC.c_proj.weight", + "norm1.linear.weight": "modX.1.weight", + "norm1_context.linear.weight": "modC.1.weight", + } + else: + index = i - n_double_layers + prefix_from = "single_transformer_blocks" + prefix_to = "{}single_layers".format(output_prefix) + + block_map = { + "attn.to_q.weight": "attn.w1q.weight", + "attn.to_k.weight": "attn.w1k.weight", + "attn.to_v.weight": "attn.w1v.weight", + "attn.to_out.0.weight": "attn.w1o.weight", + "norm1.linear.weight": "modCX.1.weight", + "ff.linear_1.weight": "mlp.c_fc1.weight", + "ff.linear_2.weight": "mlp.c_fc2.weight", + "ff.out_projection.weight": "mlp.c_proj.weight" + } + + for k in block_map: + key_map["{}.{}.{}".format(prefix_from, index, k)] = "{}.{}.{}".format(prefix_to, index, block_map[k]) + + MAP_BASIC = { + ("positional_encoding", "pos_embed.pos_embed"), + ("register_tokens", "register_tokens"), + ("t_embedder.mlp.0.weight", "time_step_proj.linear_1.weight"), + ("t_embedder.mlp.0.bias", "time_step_proj.linear_1.bias"), + ("t_embedder.mlp.2.weight", "time_step_proj.linear_2.weight"), + ("t_embedder.mlp.2.bias", "time_step_proj.linear_2.bias"), + ("cond_seq_linear.weight", "context_embedder.weight"), + ("init_x_linear.weight", "pos_embed.proj.weight"), + ("init_x_linear.bias", "pos_embed.proj.bias"), + ("final_linear.weight", "proj_out.weight"), + ("modF.1.weight", "norm_out.linear.weight", swap_scale_shift), + } + + for k in MAP_BASIC: + if len(k) > 2: + key_map[k[1]] = ("{}{}".format(output_prefix, k[0]), None, k[2]) + else: + key_map[k[1]] = "{}{}".format(output_prefix, k[0]) + + return key_map + def repeat_to_batch_size(tensor, batch_size, dim=0): if tensor.shape[dim] > batch_size: return tensor.narrow(dim, 0, batch_size) From 79547efb65ebb41a964ce7686170c4e6c3641eb2 Mon Sep 17 00:00:00 2001 From: pythongosssss <125205205+pythongosssss@users.noreply.github.com> Date: Sun, 14 Jul 2024 07:04:40 +0100 Subject: [PATCH 083/133] New menu fixes - fix send to workflow (#3909) * Fix send to workflow Fix center align of close workflow dialog Better support for elements around canvas * More resilent to extra elements added to body --- web/scripts/ui/menu/workflows.js | 8 +++++++- web/style.css | 25 +++++++++++++++++-------- 2 files changed, 24 insertions(+), 9 deletions(-) diff --git a/web/scripts/ui/menu/workflows.js b/web/scripts/ui/menu/workflows.js index afdff538a..3b904fb4b 100644 --- a/web/scripts/ui/menu/workflows.js +++ b/web/scripts/ui/menu/workflows.js @@ -182,6 +182,11 @@ export class ComfyWorkflowsMenu { * @param {ComfyWorkflow} workflow */ async function sendToWorkflow(img, workflow) { + const openWorkflow = app.workflowManager.openWorkflows.find((w) => w.path === workflow.path); + if (openWorkflow) { + workflow = openWorkflow; + } + await workflow.load(); let options = []; const nodes = app.graph.computeExecutionOrder(false); @@ -214,7 +219,8 @@ export class ComfyWorkflowsMenu { nodeType.prototype["getExtraMenuOptions"] = function (_, options) { const r = getExtraMenuOptions?.apply?.(this, arguments); - if (app.ui.settings.getSettingValue("Comfy.UseNewMenu", false) === true) { + const setting = app.ui.settings.getSettingValue("Comfy.UseNewMenu", false); + if (setting && setting != "Disabled") { const t = /** @type { {imageIndex?: number, overIndex?: number, imgs: string[]} } */ /** @type {any} */ (this); let img; if (t.imageIndex != null) { diff --git a/web/style.css b/web/style.css index e983b652a..8ef1d0dd1 100644 --- a/web/style.css +++ b/web/style.css @@ -41,7 +41,7 @@ body { background-color: var(--bg-color); color: var(--fg-color); grid-template-columns: auto 1fr auto; - grid-template-rows: auto auto 1fr auto; + grid-template-rows: auto 1fr auto; min-height: -webkit-fill-available; max-height: -webkit-fill-available; min-width: -webkit-fill-available; @@ -49,32 +49,37 @@ body { } .comfyui-body-top { - order: 0; + order: -5; grid-column: 1/-1; z-index: 10; + display: flex; + flex-direction: column; } .comfyui-body-left { - order: 1; + order: -4; z-index: 10; + display: flex; } #graph-canvas { width: 100%; height: 100%; - order: 2; - grid-column: 1/-1; + order: -3; } .comfyui-body-right { - order: 3; + order: -2; z-index: 10; + display: flex; } .comfyui-body-bottom { - order: 4; + order: -1; grid-column: 1/-1; z-index: 10; + display: flex; + flex-direction: column; } .comfy-multiline-input { @@ -408,8 +413,12 @@ dialog::backdrop { background: rgba(0, 0, 0, 0.5); } -.comfy-dialog.comfyui-dialog { +.comfy-dialog.comfyui-dialog.comfy-modal { top: 0; + left: 0; + right: 0; + bottom: 0; + transform: none; } .comfy-dialog.comfy-modal { From 7914c47d5afb1c5ffab49d665f9a1ac86a458821 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Sun, 14 Jul 2024 10:07:36 -0400 Subject: [PATCH 084/133] Quick fix for the promax controlnet. --- comfy/cldm/cldm.py | 6 +++--- comfy/controlnet.py | 2 +- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/comfy/cldm/cldm.py b/comfy/cldm/cldm.py index d4d32b87e..4a58c823f 100644 --- a/comfy/cldm/cldm.py +++ b/comfy/cldm/cldm.py @@ -92,7 +92,7 @@ class ControlNet(nn.Module): transformer_depth_middle=None, transformer_depth_output=None, attn_precision=None, - union_controlnet=False, + union_controlnet_num_control_type=None, device=None, operations=comfy.ops.disable_weight_init, **kwargs, @@ -320,8 +320,8 @@ class ControlNet(nn.Module): self.middle_block_out = self.make_zero_conv(ch, operations=operations, dtype=self.dtype, device=device) self._feature_size += ch - if union_controlnet: - self.num_control_type = 6 + if union_controlnet_num_control_type is not None: + self.num_control_type = union_controlnet_num_control_type num_trans_channel = 320 num_trans_head = 8 num_trans_layer = 1 diff --git a/comfy/controlnet.py b/comfy/controlnet.py index 84286f1fa..b8e27c71f 100644 --- a/comfy/controlnet.py +++ b/comfy/controlnet.py @@ -414,7 +414,7 @@ def load_controlnet(ckpt_path, model=None): new_sd[diffusers_keys[k]] = controlnet_data.pop(k) if "control_add_embedding.linear_1.bias" in controlnet_data: #Union Controlnet - controlnet_config["union_controlnet"] = True + controlnet_config["union_controlnet_num_control_type"] = controlnet_data["task_embedding"].shape[0] for k in list(controlnet_data.keys()): new_k = k.replace('.attn.in_proj_', '.attn.in_proj.') new_sd[new_k] = controlnet_data.pop(k) From 1305fb294ca69d0a44d88c5bf7ce8c682abd0c8a Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Mon, 15 Jul 2024 17:36:24 -0400 Subject: [PATCH 085/133] Refactor: Move some code to the comfy/text_encoders folder. --- comfy/sd.py | 20 +++++++++---------- comfy/supported_models.py | 8 ++++---- comfy/text_encoders/aura_t5.py | 4 ++-- comfy/{ => text_encoders}/sa_t5.py | 4 ++-- comfy/{ => text_encoders}/sd3_clip.py | 4 ++-- comfy/{ => text_encoders}/t5.py | 0 comfy/{ => text_encoders}/t5_config_base.json | 0 comfy/{ => text_encoders}/t5_config_xxl.json | 0 .../t5_tokenizer/special_tokens_map.json | 0 .../t5_tokenizer/tokenizer.json | 0 .../t5_tokenizer/tokenizer_config.json | 0 11 files changed, 20 insertions(+), 20 deletions(-) rename comfy/{ => text_encoders}/sa_t5.py (88%) rename comfy/{ => text_encoders}/sd3_clip.py (98%) rename comfy/{ => text_encoders}/t5.py (100%) rename comfy/{ => text_encoders}/t5_config_base.json (100%) rename comfy/{ => text_encoders}/t5_config_xxl.json (100%) rename comfy/{ => text_encoders}/t5_tokenizer/special_tokens_map.json (100%) rename comfy/{ => text_encoders}/t5_tokenizer/tokenizer.json (100%) rename comfy/{ => text_encoders}/t5_tokenizer/tokenizer_config.json (100%) diff --git a/comfy/sd.py b/comfy/sd.py index b5bbcef61..17df5faff 100644 --- a/comfy/sd.py +++ b/comfy/sd.py @@ -19,8 +19,8 @@ from . import model_detection from . import sd1_clip from . import sd2_clip from . import sdxl_clip -from . import sd3_clip -from . import sa_t5 +import comfy.text_encoders.sd3_clip +import comfy.text_encoders.sa_t5 import comfy.text_encoders.aura_t5 import comfy.model_patcher @@ -414,27 +414,27 @@ def load_clip(ckpt_paths, embedding_directory=None, clip_type=CLIPType.STABLE_DI weight = clip_data[0]["encoder.block.23.layer.1.DenseReluDense.wi_1.weight"] dtype_t5 = weight.dtype if weight.shape[-1] == 4096: - clip_target.clip = sd3_clip.sd3_clip(clip_l=False, clip_g=False, t5=True, dtype_t5=dtype_t5) - clip_target.tokenizer = sd3_clip.SD3Tokenizer + clip_target.clip = comfy.text_encoders.sd3_clip.sd3_clip(clip_l=False, clip_g=False, t5=True, dtype_t5=dtype_t5) + clip_target.tokenizer = comfy.text_encoders.sd3_clip.SD3Tokenizer elif weight.shape[-1] == 2048: clip_target.clip = comfy.text_encoders.aura_t5.AuraT5Model clip_target.tokenizer = comfy.text_encoders.aura_t5.AuraT5Tokenizer elif "encoder.block.0.layer.0.SelfAttention.k.weight" in clip_data[0]: - clip_target.clip = sa_t5.SAT5Model - clip_target.tokenizer = sa_t5.SAT5Tokenizer + clip_target.clip = comfy.text_encoders.sa_t5.SAT5Model + clip_target.tokenizer = comfy.text_encoders.sa_t5.SAT5Tokenizer else: clip_target.clip = sd1_clip.SD1ClipModel clip_target.tokenizer = sd1_clip.SD1Tokenizer elif len(clip_data) == 2: if clip_type == CLIPType.SD3: - clip_target.clip = sd3_clip.sd3_clip(clip_l=True, clip_g=True, t5=False) - clip_target.tokenizer = sd3_clip.SD3Tokenizer + clip_target.clip = comfy.text_encoders.sd3_clip.sd3_clip(clip_l=True, clip_g=True, t5=False) + clip_target.tokenizer = comfy.text_encoders.sd3_clip.SD3Tokenizer else: clip_target.clip = sdxl_clip.SDXLClipModel clip_target.tokenizer = sdxl_clip.SDXLTokenizer elif len(clip_data) == 3: - clip_target.clip = sd3_clip.SD3ClipModel - clip_target.tokenizer = sd3_clip.SD3Tokenizer + clip_target.clip = comfy.text_encoders.sd3_clip.SD3ClipModel + clip_target.tokenizer = comfy.text_encoders.sd3_clip.SD3Tokenizer clip = CLIP(clip_target, embedding_directory=embedding_directory) for c in clip_data: diff --git a/comfy/supported_models.py b/comfy/supported_models.py index a030f6229..b4d1059ef 100644 --- a/comfy/supported_models.py +++ b/comfy/supported_models.py @@ -5,8 +5,8 @@ from . import utils from . import sd1_clip from . import sd2_clip from . import sdxl_clip -from . import sd3_clip -from . import sa_t5 +import comfy.text_encoders.sd3_clip +import comfy.text_encoders.sa_t5 import comfy.text_encoders.aura_t5 from . import supported_models_base @@ -524,7 +524,7 @@ class SD3(supported_models_base.BASE): t5 = True dtype_t5 = state_dict[t5_key].dtype - return supported_models_base.ClipTarget(sd3_clip.SD3Tokenizer, sd3_clip.sd3_clip(clip_l=clip_l, clip_g=clip_g, t5=t5, dtype_t5=dtype_t5)) + return supported_models_base.ClipTarget(comfy.text_encoders.sd3_clip.SD3Tokenizer, comfy.text_encoders.sd3_clip.sd3_clip(clip_l=clip_l, clip_g=clip_g, t5=t5, dtype_t5=dtype_t5)) class StableAudio(supported_models_base.BASE): unet_config = { @@ -555,7 +555,7 @@ class StableAudio(supported_models_base.BASE): return utils.state_dict_prefix_replace(state_dict, replace_prefix) def clip_target(self, state_dict={}): - return supported_models_base.ClipTarget(sa_t5.SAT5Tokenizer, sa_t5.SAT5Model) + return supported_models_base.ClipTarget(comfy.text_encoders.sa_t5.SAT5Tokenizer, comfy.text_encoders.sa_t5.SAT5Model) class AuraFlow(supported_models_base.BASE): unet_config = { diff --git a/comfy/text_encoders/aura_t5.py b/comfy/text_encoders/aura_t5.py index 95f942ef5..6b9e4fe53 100644 --- a/comfy/text_encoders/aura_t5.py +++ b/comfy/text_encoders/aura_t5.py @@ -1,12 +1,12 @@ from comfy import sd1_clip from .llama_tokenizer import LLAMATokenizer -import comfy.t5 +import comfy.text_encoders.t5 import os class PT5XlModel(sd1_clip.SDClipModel): def __init__(self, device="cpu", layer="last", layer_idx=None, dtype=None): textmodel_json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "t5_pile_config_xl.json") - super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, dtype=dtype, special_tokens={"end": 2, "pad": 1}, model_class=comfy.t5.T5, enable_attention_masks=True, zero_out_masked=True) + super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, dtype=dtype, special_tokens={"end": 2, "pad": 1}, model_class=comfy.text_encoders.t5.T5, enable_attention_masks=True, zero_out_masked=True) class PT5XlTokenizer(sd1_clip.SDTokenizer): def __init__(self, embedding_directory=None): diff --git a/comfy/sa_t5.py b/comfy/text_encoders/sa_t5.py similarity index 88% rename from comfy/sa_t5.py rename to comfy/text_encoders/sa_t5.py index acc302f67..038558e7a 100644 --- a/comfy/sa_t5.py +++ b/comfy/text_encoders/sa_t5.py @@ -1,12 +1,12 @@ from comfy import sd1_clip from transformers import T5TokenizerFast -import comfy.t5 +import comfy.text_encoders.t5 import os class T5BaseModel(sd1_clip.SDClipModel): def __init__(self, device="cpu", layer="last", layer_idx=None, dtype=None): textmodel_json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "t5_config_base.json") - super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, dtype=dtype, special_tokens={"end": 1, "pad": 0}, model_class=comfy.t5.T5, enable_attention_masks=True, zero_out_masked=True) + super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, dtype=dtype, special_tokens={"end": 1, "pad": 0}, model_class=comfy.text_encoders.t5.T5, enable_attention_masks=True, zero_out_masked=True) class T5BaseTokenizer(sd1_clip.SDTokenizer): def __init__(self, embedding_directory=None): diff --git a/comfy/sd3_clip.py b/comfy/text_encoders/sd3_clip.py similarity index 98% rename from comfy/sd3_clip.py rename to comfy/text_encoders/sd3_clip.py index 0713eb285..70127e509 100644 --- a/comfy/sd3_clip.py +++ b/comfy/text_encoders/sd3_clip.py @@ -1,7 +1,7 @@ from comfy import sd1_clip from comfy import sdxl_clip from transformers import T5TokenizerFast -import comfy.t5 +import comfy.text_encoders.t5 import torch import os import comfy.model_management @@ -10,7 +10,7 @@ import logging class T5XXLModel(sd1_clip.SDClipModel): def __init__(self, device="cpu", layer="last", layer_idx=None, dtype=None): textmodel_json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "t5_config_xxl.json") - super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, dtype=dtype, special_tokens={"end": 1, "pad": 0}, model_class=comfy.t5.T5) + super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, dtype=dtype, special_tokens={"end": 1, "pad": 0}, model_class=comfy.text_encoders.t5.T5) class T5XXLTokenizer(sd1_clip.SDTokenizer): def __init__(self, embedding_directory=None): diff --git a/comfy/t5.py b/comfy/text_encoders/t5.py similarity index 100% rename from comfy/t5.py rename to comfy/text_encoders/t5.py diff --git a/comfy/t5_config_base.json b/comfy/text_encoders/t5_config_base.json similarity index 100% rename from comfy/t5_config_base.json rename to comfy/text_encoders/t5_config_base.json diff --git a/comfy/t5_config_xxl.json b/comfy/text_encoders/t5_config_xxl.json similarity index 100% rename from comfy/t5_config_xxl.json rename to comfy/text_encoders/t5_config_xxl.json diff --git a/comfy/t5_tokenizer/special_tokens_map.json b/comfy/text_encoders/t5_tokenizer/special_tokens_map.json similarity index 100% rename from comfy/t5_tokenizer/special_tokens_map.json rename to comfy/text_encoders/t5_tokenizer/special_tokens_map.json diff --git a/comfy/t5_tokenizer/tokenizer.json b/comfy/text_encoders/t5_tokenizer/tokenizer.json similarity index 100% rename from comfy/t5_tokenizer/tokenizer.json rename to comfy/text_encoders/t5_tokenizer/tokenizer.json diff --git a/comfy/t5_tokenizer/tokenizer_config.json b/comfy/text_encoders/t5_tokenizer/tokenizer_config.json similarity index 100% rename from comfy/t5_tokenizer/tokenizer_config.json rename to comfy/text_encoders/t5_tokenizer/tokenizer_config.json From 136c93cb477e4c5c308791746583499805ab29aa Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Mon, 15 Jul 2024 20:01:49 -0400 Subject: [PATCH 086/133] Fix bug with workflow not registering change. There was an issue when only the class type of a node changed with all the inputs staying the same. --- execution.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/execution.py b/execution.py index 76225a962..8b3d116c6 100644 --- a/execution.py +++ b/execution.py @@ -247,6 +247,8 @@ def recursive_output_delete_if_changed(prompt, old_prompt, outputs, current_item to_delete = True elif unique_id not in old_prompt: to_delete = True + elif class_type != old_prompt[unique_id]['class_type']: + to_delete = True elif inputs == old_prompt[unique_id]['inputs']: for x in inputs: input_data = inputs[x] From 33346fd9b8856942187ad8c818498a080a2027b5 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Mon, 15 Jul 2024 20:36:03 -0400 Subject: [PATCH 087/133] Fix bug with custom nodes on other drives. --- nodes.py | 30 +++++++++++++++--------------- 1 file changed, 15 insertions(+), 15 deletions(-) diff --git a/nodes.py b/nodes.py index 5778f0609..998b316b7 100644 --- a/nodes.py +++ b/nodes.py @@ -1890,29 +1890,29 @@ NODE_DISPLAY_NAME_MAPPINGS = { EXTENSION_WEB_DIRS = {} -def get_relative_module_name(module_path: str) -> str: +def get_module_name(module_path: str) -> str: """ Returns the module name based on the given module path. Examples: - get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node.py") -> "custom_nodes.my_custom_node" - get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node") -> "custom_nodes.my_custom_node" - get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node/") -> "custom_nodes.my_custom_node" - get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node/__init__.py") -> "custom_nodes.my_custom_node" - get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node/__init__") -> "custom_nodes.my_custom_node" - get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node/__init__/") -> "custom_nodes.my_custom_node" - get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node.disabled") -> "custom_nodes.my + get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node.py") -> "my_custom_node" + get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node") -> "my_custom_node" + get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node/") -> "my_custom_node" + get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node/__init__.py") -> "my_custom_node" + get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node/__init__") -> "my_custom_node" + get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node/__init__/") -> "my_custom_node" + get_module_name("C:/Users/username/ComfyUI/custom_nodes/my_custom_node.disabled") -> "custom_nodes Args: module_path (str): The path of the module. Returns: str: The module name. """ - relative_path = os.path.relpath(module_path, folder_paths.base_path) + base_path = os.path.basename(module_path) if os.path.isfile(module_path): - relative_path = os.path.splitext(relative_path)[0] - return relative_path.replace(os.sep, '.') + base_path = os.path.splitext(base_path)[0] + return base_path -def load_custom_node(module_path: str, ignore=set()) -> bool: +def load_custom_node(module_path: str, ignore=set(), module_parent="custom_nodes") -> bool: module_name = os.path.basename(module_path) if os.path.isfile(module_path): sp = os.path.splitext(module_path) @@ -1939,7 +1939,7 @@ def load_custom_node(module_path: str, ignore=set()) -> bool: for name, node_cls in module.NODE_CLASS_MAPPINGS.items(): if name not in ignore: NODE_CLASS_MAPPINGS[name] = node_cls - node_cls.RELATIVE_PYTHON_MODULE = get_relative_module_name(module_path) + node_cls.RELATIVE_PYTHON_MODULE = "{}.{}".format(module_parent, get_module_name(module_path)) if hasattr(module, "NODE_DISPLAY_NAME_MAPPINGS") and getattr(module, "NODE_DISPLAY_NAME_MAPPINGS") is not None: NODE_DISPLAY_NAME_MAPPINGS.update(module.NODE_DISPLAY_NAME_MAPPINGS) return True @@ -1974,7 +1974,7 @@ def init_external_custom_nodes(): if os.path.isfile(module_path) and os.path.splitext(module_path)[1] != ".py": continue if module_path.endswith(".disabled"): continue time_before = time.perf_counter() - success = load_custom_node(module_path, base_node_names) + success = load_custom_node(module_path, base_node_names, module_parent="custom_nodes") node_import_times.append((time.perf_counter() - time_before, module_path, success)) if len(node_import_times) > 0: @@ -2040,7 +2040,7 @@ def init_builtin_extra_nodes(): import_failed = [] for node_file in extras_files: - if not load_custom_node(os.path.join(extras_dir, node_file)): + if not load_custom_node(os.path.join(extras_dir, node_file), module_parent="comfy_extras"): import_failed.append(node_file) return import_failed From 99458e8aca3c48c7b2de3c404f66536991c37182 Mon Sep 17 00:00:00 2001 From: Chenlei Hu Date: Tue, 16 Jul 2024 11:26:11 -0400 Subject: [PATCH 088/133] Add `FrontendManager` to manage non-default front-end impl (#3897) * Add frontend manager * Add tests * nit * Add unit test to github CI * Fix path * nit * ignore * Add logging * Install test deps * Remove 'stable' keyword support * Update test * Add web-root arg * Rename web-root to front-end-root * Add test on non-exist version number * Use repo owner/name to replace hard coded provider list * Inline cmd args * nit * Fix unit test --- .github/workflows/test-ui.yaml | 4 + .gitignore | 3 +- app/__init__.py | 0 app/frontend_management.py | 187 +++++++++++++++++++ comfy/cli_args.py | 35 ++++ pytest.ini | 7 +- server.py | 11 +- tests-unit/README.md | 8 + tests-unit/app_test/__init__.py | 0 tests-unit/app_test/frontend_manager_test.py | 100 ++++++++++ tests-unit/requirements.txt | 1 + 11 files changed, 350 insertions(+), 6 deletions(-) create mode 100644 app/__init__.py create mode 100644 app/frontend_management.py create mode 100644 tests-unit/README.md create mode 100644 tests-unit/app_test/__init__.py create mode 100644 tests-unit/app_test/frontend_manager_test.py create mode 100644 tests-unit/requirements.txt diff --git a/.github/workflows/test-ui.yaml b/.github/workflows/test-ui.yaml index 4b8b97934..d947e9d5f 100644 --- a/.github/workflows/test-ui.yaml +++ b/.github/workflows/test-ui.yaml @@ -24,3 +24,7 @@ jobs: npm run test:generate npm test -- --verbose working-directory: ./tests-ui + - name: Run Unit Tests + run: | + pip install -r tests-unit/requirements.txt + python -m pytest tests-unit diff --git a/.gitignore b/.gitignore index a9beebe73..5092c98f4 100644 --- a/.gitignore +++ b/.gitignore @@ -17,4 +17,5 @@ venv/ !/web/extensions/core/ /tests-ui/data/object_info.json /user/ -*.log \ No newline at end of file +*.log +web_custom_versions/ \ No newline at end of file diff --git a/app/__init__.py b/app/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/app/frontend_management.py b/app/frontend_management.py new file mode 100644 index 000000000..0855f4160 --- /dev/null +++ b/app/frontend_management.py @@ -0,0 +1,187 @@ +import argparse +import logging +import os +import re +import tempfile +import zipfile +from dataclasses import dataclass +from functools import cached_property +from pathlib import Path +from typing import TypedDict + +import requests +from typing_extensions import NotRequired +from comfy.cli_args import DEFAULT_VERSION_STRING + + +REQUEST_TIMEOUT = 10 # seconds + + +class Asset(TypedDict): + url: str + + +class Release(TypedDict): + id: int + tag_name: str + name: str + prerelease: bool + created_at: str + published_at: str + body: str + assets: NotRequired[list[Asset]] + + +@dataclass +class FrontEndProvider: + owner: str + repo: str + + @property + def folder_name(self) -> str: + return f"{self.owner}_{self.repo}" + + @property + def release_url(self) -> str: + return f"https://api.github.com/repos/{self.owner}/{self.repo}/releases" + + @cached_property + def all_releases(self) -> list[Release]: + releases = [] + api_url = self.release_url + while api_url: + response = requests.get(api_url, timeout=REQUEST_TIMEOUT) + response.raise_for_status() # Raises an HTTPError if the response was an error + releases.extend(response.json()) + # GitHub uses the Link header to provide pagination links. Check if it exists and update api_url accordingly. + if "next" in response.links: + api_url = response.links["next"]["url"] + else: + api_url = None + return releases + + @cached_property + def latest_release(self) -> Release: + latest_release_url = f"{self.release_url}/latest" + response = requests.get(latest_release_url, timeout=REQUEST_TIMEOUT) + response.raise_for_status() # Raises an HTTPError if the response was an error + return response.json() + + def get_release(self, version: str) -> Release: + if version == "latest": + return self.latest_release + else: + for release in self.all_releases: + if release["tag_name"] in [version, f"v{version}"]: + return release + raise ValueError(f"Version {version} not found in releases") + + +def download_release_asset_zip(release: Release, destination_path: str) -> None: + """Download dist.zip from github release.""" + asset_url = None + for asset in release.get("assets", []): + if asset["name"] == "dist.zip": + asset_url = asset["url"] + break + + if not asset_url: + raise ValueError("dist.zip not found in the release assets") + + # Use a temporary file to download the zip content + with tempfile.TemporaryFile() as tmp_file: + headers = {"Accept": "application/octet-stream"} + response = requests.get( + asset_url, headers=headers, allow_redirects=True, timeout=REQUEST_TIMEOUT + ) + response.raise_for_status() # Ensure we got a successful response + + # Write the content to the temporary file + tmp_file.write(response.content) + + # Go back to the beginning of the temporary file + tmp_file.seek(0) + + # Extract the zip file content to the destination path + with zipfile.ZipFile(tmp_file, "r") as zip_ref: + zip_ref.extractall(destination_path) + + +class FrontendManager: + DEFAULT_FRONTEND_PATH = str(Path(__file__).parents[1] / "web") + CUSTOM_FRONTENDS_ROOT = str(Path(__file__).parents[1] / "web_custom_versions") + + @classmethod + def parse_version_string(cls, value: str) -> tuple[str, str, str]: + """ + Args: + value (str): The version string to parse. + + Returns: + tuple[str, str]: A tuple containing provider name and version. + + Raises: + argparse.ArgumentTypeError: If the version string is invalid. + """ + VERSION_PATTERN = r"^([a-zA-Z0-9][a-zA-Z0-9-]{0,38})/([a-zA-Z0-9_.-]+)@(\d+\.\d+\.\d+|latest)$" + match_result = re.match(VERSION_PATTERN, value) + if match_result is None: + raise argparse.ArgumentTypeError(f"Invalid version string: {value}") + + return match_result.group(1), match_result.group(2), match_result.group(3) + + @classmethod + def init_frontend_unsafe(cls, version_string: str) -> str: + """ + Initializes the frontend for the specified version. + + Args: + version_string (str): The version string. + + Returns: + str: The path to the initialized frontend. + + Raises: + Exception: If there is an error during the initialization process. + main error source might be request timeout or invalid URL. + """ + if version_string == DEFAULT_VERSION_STRING: + return cls.DEFAULT_FRONTEND_PATH + + repo_owner, repo_name, version = cls.parse_version_string(version_string) + provider = FrontEndProvider(repo_owner, repo_name) + release = provider.get_release(version) + + semantic_version = release["tag_name"].lstrip("v") + web_root = str( + Path(cls.CUSTOM_FRONTENDS_ROOT) / provider.folder_name / semantic_version + ) + if not os.path.exists(web_root): + os.makedirs(web_root, exist_ok=True) + logging.info( + "Downloading frontend(%s) version(%s) to (%s)", + provider.folder_name, + semantic_version, + web_root, + ) + logging.debug(release) + download_release_asset_zip(release, destination_path=web_root) + return web_root + + @classmethod + def init_frontend(cls, version_string: str) -> str: + """ + Initializes the frontend with the specified version string. + + Args: + version_string (str): The version string to initialize the frontend with. + + Returns: + str: The path of the initialized frontend. + """ + try: + return cls.init_frontend_unsafe(version_string) + except Exception as e: + logging.error("Failed to initialize frontend: %s", e) + logging.info("Falling back to the default frontend.") + return cls.DEFAULT_FRONTEND_PATH diff --git a/comfy/cli_args.py b/comfy/cli_args.py index b72bf3998..6251e3d28 100644 --- a/comfy/cli_args.py +++ b/comfy/cli_args.py @@ -1,7 +1,10 @@ import argparse import enum +import os +from typing import Optional import comfy.options + class EnumAction(argparse.Action): """ Argparse action for handling Enums @@ -124,6 +127,38 @@ parser.add_argument("--multi-user", action="store_true", help="Enables per-user parser.add_argument("--verbose", action="store_true", help="Enables more debug prints.") +# The default built-in provider hosted under web/ +DEFAULT_VERSION_STRING = "comfyanonymous/ComfyUI@latest" + +parser.add_argument( + "--front-end-version", + type=str, + default=DEFAULT_VERSION_STRING, + help=""" + Specifies the version of the frontend to be used. This command needs internet connectivity to query and + download available frontend implementations from GitHub releases. + + The version string should be in the format of: + [repoOwner]/[repoName]@[version] + where version is one of: "latest" or a valid version number (e.g. "1.0.0") + """, +) + +def is_valid_directory(path: Optional[str]) -> Optional[str]: + """Validate if the given path is a directory.""" + if path is None: + return None + + if not os.path.isdir(path): + raise argparse.ArgumentTypeError(f"{path} is not a valid directory.") + return path + +parser.add_argument( + "--front-end-root", + type=is_valid_directory, + default=None, + help="The local filesystem path to the directory where the frontend is located. Overrides --front-end-version.", +) if comfy.options.args_parsing: args = parser.parse_args() diff --git a/pytest.ini b/pytest.ini index b5a68e0f1..8b7a747e7 100644 --- a/pytest.ini +++ b/pytest.ini @@ -1,5 +1,8 @@ [pytest] markers = inference: mark as inference test (deselect with '-m "not inference"') -testpaths = tests -addopts = -s \ No newline at end of file +testpaths = + tests + tests-unit +addopts = -s +pythonpath = . diff --git a/server.py b/server.py index ce7c7532d..03c4c4219 100644 --- a/server.py +++ b/server.py @@ -25,9 +25,10 @@ import mimetypes from comfy.cli_args import args import comfy.utils import comfy.model_management - +from app.frontend_management import FrontendManager from app.user_manager import UserManager + class BinaryEventTypes: PREVIEW_IMAGE = 1 UNENCODED_PREVIEW_IMAGE = 2 @@ -83,8 +84,12 @@ class PromptServer(): max_upload_size = round(args.max_upload_size * 1024 * 1024) self.app = web.Application(client_max_size=max_upload_size, middlewares=middlewares) self.sockets = dict() - self.web_root = os.path.join(os.path.dirname( - os.path.realpath(__file__)), "web") + self.web_root = ( + FrontendManager.init_frontend(args.front_end_version) + if args.front_end_root is None + else args.front_end_root + ) + logging.info(f"[Prompt Server] web root: {self.web_root}") routes = web.RouteTableDef() self.routes = routes self.last_node_id = None diff --git a/tests-unit/README.md b/tests-unit/README.md new file mode 100644 index 000000000..94abd9853 --- /dev/null +++ b/tests-unit/README.md @@ -0,0 +1,8 @@ +# Pytest Unit Tests + +## Install test dependencies + +`pip install -r tests-units/requirements.txt` + +## Run tests +`pytest tests-units/` diff --git a/tests-unit/app_test/__init__.py b/tests-unit/app_test/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/tests-unit/app_test/frontend_manager_test.py b/tests-unit/app_test/frontend_manager_test.py new file mode 100644 index 000000000..637869cfb --- /dev/null +++ b/tests-unit/app_test/frontend_manager_test.py @@ -0,0 +1,100 @@ +import argparse +import pytest +from requests.exceptions import HTTPError + +from app.frontend_management import ( + FrontendManager, + FrontEndProvider, + Release, +) +from comfy.cli_args import DEFAULT_VERSION_STRING + + +@pytest.fixture +def mock_releases(): + return [ + Release( + id=1, + tag_name="1.0.0", + name="Release 1.0.0", + prerelease=False, + created_at="2022-01-01T00:00:00Z", + published_at="2022-01-01T00:00:00Z", + body="Release notes for 1.0.0", + assets=[{"name": "dist.zip", "url": "https://example.com/dist.zip"}], + ), + Release( + id=2, + tag_name="2.0.0", + name="Release 2.0.0", + prerelease=False, + created_at="2022-02-01T00:00:00Z", + published_at="2022-02-01T00:00:00Z", + body="Release notes for 2.0.0", + assets=[{"name": "dist.zip", "url": "https://example.com/dist.zip"}], + ), + ] + + +@pytest.fixture +def mock_provider(mock_releases): + provider = FrontEndProvider( + owner="test-owner", + repo="test-repo", + ) + provider.all_releases = mock_releases + provider.latest_release = mock_releases[1] + FrontendManager.PROVIDERS = [provider] + return provider + + +def test_get_release(mock_provider, mock_releases): + version = "1.0.0" + release = mock_provider.get_release(version) + assert release == mock_releases[0] + + +def test_get_release_latest(mock_provider, mock_releases): + version = "latest" + release = mock_provider.get_release(version) + assert release == mock_releases[1] + + +def test_get_release_invalid_version(mock_provider): + version = "invalid" + with pytest.raises(ValueError): + mock_provider.get_release(version) + + +def test_init_frontend_default(): + version_string = DEFAULT_VERSION_STRING + frontend_path = FrontendManager.init_frontend(version_string) + assert frontend_path == FrontendManager.DEFAULT_FRONTEND_PATH + + +def test_init_frontend_invalid_version(): + version_string = "test-owner/test-repo@1.100.99" + with pytest.raises(HTTPError): + FrontendManager.init_frontend_unsafe(version_string) + + +def test_init_frontend_invalid_provider(): + version_string = "invalid/invalid@latest" + with pytest.raises(HTTPError): + FrontendManager.init_frontend_unsafe(version_string) + + +def test_parse_version_string(): + version_string = "owner/repo@1.0.0" + repo_owner, repo_name, version = FrontendManager.parse_version_string( + version_string + ) + assert repo_owner == "owner" + assert repo_name == "repo" + assert version == "1.0.0" + + +def test_parse_version_string_invalid(): + version_string = "invalid" + with pytest.raises(argparse.ArgumentTypeError): + FrontendManager.parse_version_string(version_string) diff --git a/tests-unit/requirements.txt b/tests-unit/requirements.txt new file mode 100644 index 000000000..0587502f8 --- /dev/null +++ b/tests-unit/requirements.txt @@ -0,0 +1 @@ +pytest>=7.8.0 From e1630391d6d190c3dd9ef4609f0c84af72be54af Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Tue, 16 Jul 2024 11:29:38 -0400 Subject: [PATCH 089/133] Allow version names like v0.0.1 for the FrontendManager. --- app/frontend_management.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/app/frontend_management.py b/app/frontend_management.py index 0855f4160..5452f6e11 100644 --- a/app/frontend_management.py +++ b/app/frontend_management.py @@ -123,7 +123,7 @@ class FrontendManager: Raises: argparse.ArgumentTypeError: If the version string is invalid. """ - VERSION_PATTERN = r"^([a-zA-Z0-9][a-zA-Z0-9-]{0,38})/([a-zA-Z0-9_.-]+)@(\d+\.\d+\.\d+|latest)$" + VERSION_PATTERN = r"^([a-zA-Z0-9][a-zA-Z0-9-]{0,38})/([a-zA-Z0-9_.-]+)@(v?\d+\.\d+\.\d+|latest)$" match_result = re.match(VERSION_PATTERN, value) if match_result is None: raise argparse.ArgumentTypeError(f"Invalid version string: {value}") From 821f93872ecf3f1769b8abebd640a804839f4ab9 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Tue, 16 Jul 2024 15:18:24 -0400 Subject: [PATCH 090/133] Allow model sampling to set number of timesteps. --- comfy/model_sampling.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/comfy/model_sampling.py b/comfy/model_sampling.py index 2d95a83dc..25bb7e043 100644 --- a/comfy/model_sampling.py +++ b/comfy/model_sampling.py @@ -59,8 +59,9 @@ class ModelSamplingDiscrete(torch.nn.Module): beta_schedule = sampling_settings.get("beta_schedule", "linear") linear_start = sampling_settings.get("linear_start", 0.00085) linear_end = sampling_settings.get("linear_end", 0.012) + timesteps = sampling_settings.get("timesteps", 1000) - self._register_schedule(given_betas=None, beta_schedule=beta_schedule, timesteps=1000, linear_start=linear_start, linear_end=linear_end, cosine_s=8e-3) + self._register_schedule(given_betas=None, beta_schedule=beta_schedule, timesteps=timesteps, linear_start=linear_start, linear_end=linear_end, cosine_s=8e-3) self.sigma_data = 1.0 def _register_schedule(self, given_betas=None, beta_schedule="linear", timesteps=1000, From 8270c625301034767c77b7d7b1e5a135172d1ebb Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Tue, 16 Jul 2024 17:01:40 -0400 Subject: [PATCH 091/133] Add SetUnionControlNetType to set the type of the union controlnet model. --- comfy/controlnet.py | 8 ++++++- comfy_extras/nodes_controlnet.py | 37 ++++++++++++++++++++++++++++++++ nodes.py | 1 + 3 files changed, 45 insertions(+), 1 deletion(-) create mode 100644 comfy_extras/nodes_controlnet.py diff --git a/comfy/controlnet.py b/comfy/controlnet.py index b8e27c71f..12e5f16c8 100644 --- a/comfy/controlnet.py +++ b/comfy/controlnet.py @@ -45,6 +45,7 @@ class ControlBase: self.timestep_range = None self.compression_ratio = 8 self.upscale_algorithm = 'nearest-exact' + self.extra_args = {} if device is None: device = comfy.model_management.get_torch_device() @@ -90,6 +91,7 @@ class ControlBase: c.compression_ratio = self.compression_ratio c.upscale_algorithm = self.upscale_algorithm c.latent_format = self.latent_format + c.extra_args = self.extra_args.copy() c.vae = self.vae def inference_memory_requirements(self, dtype): @@ -135,6 +137,10 @@ class ControlBase: o[i] = prev_val + o[i] #TODO: change back to inplace add if shared tensors stop being an issue return out + def set_extra_arg(self, argument, value=None): + self.extra_args[argument] = value + + class ControlNet(ControlBase): def __init__(self, control_model=None, global_average_pooling=False, compression_ratio=8, latent_format=None, device=None, load_device=None, manual_cast_dtype=None): super().__init__(device) @@ -191,7 +197,7 @@ class ControlNet(ControlBase): timestep = self.model_sampling_current.timestep(t) x_noisy = self.model_sampling_current.calculate_input(t, x_noisy) - control = self.control_model(x=x_noisy.to(dtype), hint=self.cond_hint, timesteps=timestep.float(), context=context.to(dtype), y=y) + control = self.control_model(x=x_noisy.to(dtype), hint=self.cond_hint, timesteps=timestep.float(), context=context.to(dtype), y=y, **self.extra_args) return self.control_merge(control, control_prev, output_dtype) def copy(self): diff --git a/comfy_extras/nodes_controlnet.py b/comfy_extras/nodes_controlnet.py new file mode 100644 index 000000000..e550436b0 --- /dev/null +++ b/comfy_extras/nodes_controlnet.py @@ -0,0 +1,37 @@ + +UNION_CONTROLNET_TYPES = {"auto": -1, + "openpose": 0, + "depth": 1, + "hed/pidi/scribble/ted": 2, + "canny/lineart/anime_lineart/mlsd": 3, + "normal": 4, + "segment": 5, + "tile": 6, + "repaint": 7, + } + +class SetUnionControlNetType: + @classmethod + def INPUT_TYPES(s): + return {"required": {"control_net": ("CONTROL_NET", ), + "type": (list(UNION_CONTROLNET_TYPES.keys()),) + }} + + CATEGORY = "conditioning" + RETURN_TYPES = ("CONTROL_NET",) + + FUNCTION = "set_controlnet_type" + + def set_controlnet_type(self, control_net, type): + control_net = control_net.copy() + type_number = UNION_CONTROLNET_TYPES[type] + if type_number >= 0: + control_net.set_extra_arg("control_type", [type_number]) + else: + control_net.set_extra_arg("control_type", []) + + return (control_net,) + +NODE_CLASS_MAPPINGS = { + "SetUnionControlNetType": SetUnionControlNetType, +} diff --git a/nodes.py b/nodes.py index 998b316b7..89a2f21d2 100644 --- a/nodes.py +++ b/nodes.py @@ -2036,6 +2036,7 @@ def init_builtin_extra_nodes(): "nodes_audio.py", "nodes_sd3.py", "nodes_gits.py", + "nodes_controlnet.py", ] import_failed = [] From 60383f3b64aa4477edfea325879bb04d3695161c Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Tue, 16 Jul 2024 17:08:25 -0400 Subject: [PATCH 092/133] Move controlnet nodes to conditioning/controlnet. --- comfy_extras/nodes_controlnet.py | 2 +- comfy_extras/nodes_sd3.py | 2 +- nodes.py | 4 ++-- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/comfy_extras/nodes_controlnet.py b/comfy_extras/nodes_controlnet.py index e550436b0..ef7cfc6ab 100644 --- a/comfy_extras/nodes_controlnet.py +++ b/comfy_extras/nodes_controlnet.py @@ -17,7 +17,7 @@ class SetUnionControlNetType: "type": (list(UNION_CONTROLNET_TYPES.keys()),) }} - CATEGORY = "conditioning" + CATEGORY = "conditioning/controlnet" RETURN_TYPES = ("CONTROL_NET",) FUNCTION = "set_controlnet_type" diff --git a/comfy_extras/nodes_sd3.py b/comfy_extras/nodes_sd3.py index 548b1ad6a..0aafa2426 100644 --- a/comfy_extras/nodes_sd3.py +++ b/comfy_extras/nodes_sd3.py @@ -92,7 +92,7 @@ class ControlNetApplySD3(nodes.ControlNetApplyAdvanced): "start_percent": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001}), "end_percent": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.001}) }} - CATEGORY = "_for_testing/sd3" + CATEGORY = "conditioning/controlnet" NODE_CLASS_MAPPINGS = { "TripleCLIPLoader": TripleCLIPLoader, diff --git a/nodes.py b/nodes.py index 89a2f21d2..fbdcb6c91 100644 --- a/nodes.py +++ b/nodes.py @@ -748,7 +748,7 @@ class ControlNetApply: RETURN_TYPES = ("CONDITIONING",) FUNCTION = "apply_controlnet" - CATEGORY = "conditioning" + CATEGORY = "conditioning/controlnet" def apply_controlnet(self, conditioning, control_net, image, strength): if strength == 0: @@ -783,7 +783,7 @@ class ControlNetApplyAdvanced: RETURN_NAMES = ("positive", "negative") FUNCTION = "apply_controlnet" - CATEGORY = "conditioning" + CATEGORY = "conditioning/controlnet" def apply_controlnet(self, positive, negative, control_net, image, strength, start_percent, end_percent, vae=None): if strength == 0: From f2298799ba58e915a1f22fec336d455c0913f409 Mon Sep 17 00:00:00 2001 From: Chenlei Hu Date: Tue, 16 Jul 2024 18:20:39 -0400 Subject: [PATCH 093/133] Fix annotation (#4035) --- app/frontend_management.py | 1 + 1 file changed, 1 insertion(+) diff --git a/app/frontend_management.py b/app/frontend_management.py index 5452f6e11..fb57b23f3 100644 --- a/app/frontend_management.py +++ b/app/frontend_management.py @@ -1,3 +1,4 @@ +from __future__ import annotations import argparse import logging import os From c5a48b15bddab089f0054af0ed72eea868263ef6 Mon Sep 17 00:00:00 2001 From: Thomas Ward Date: Tue, 16 Jul 2024 18:27:09 -0400 Subject: [PATCH 094/133] Make default hash lib configurable without code changes via CLI argument (#3947) * cli_args: Add --duplicate-check-hash-function. * server.py: compare_image_hash configurable hash function Uses an argument added in cli_args to specify the type of hashing to default to for duplicate hash checking. Uses an `eval()` to identify the specific hashlib class to utilize, but ultimately safely operates because we have specific options and only those options/choices in the arg parser. So we don't have any unsafe input there. * Add hasher() to node_helpers * hashlib selection moved to node_helpers * default-hashing-function instead of dupe checking hasher This makes a default-hashing-function option instead of previous selected option. * Use args.default_hashing_function * Use safer handling for node_helpers.hasher() Uses a safer handling method than `eval` to evaluate default hashing function. * Stray parentheses are evil. * Indentation fix. Somehow when I hit save I didn't notice I missed a space to make indentation work proper. Oops! --- comfy/cli_args.py | 1 + node_helpers.py | 13 +++++++++++++ server.py | 7 +++++-- 3 files changed, 19 insertions(+), 2 deletions(-) diff --git a/comfy/cli_args.py b/comfy/cli_args.py index 6251e3d28..2397de3d6 100644 --- a/comfy/cli_args.py +++ b/comfy/cli_args.py @@ -112,6 +112,7 @@ vram_group.add_argument("--lowvram", action="store_true", help="Split the unet i vram_group.add_argument("--novram", action="store_true", help="When lowvram isn't enough.") vram_group.add_argument("--cpu", action="store_true", help="To use the CPU for everything (slow).") +parser.add_argument("--default-hashing-function", type=str, choices=['md5', 'sha1', 'sha256', 'sha512'], default='sha256', help="Allows you to choose the hash function to use for duplicate filename / contents comparison. Default is sha256.") parser.add_argument("--disable-smart-memory", action="store_true", help="Force ComfyUI to agressively offload to regular ram instead of keeping models in vram when it can.") parser.add_argument("--deterministic", action="store_true", help="Make pytorch use slower deterministic algorithms when it can. Note that this might not make images deterministic in all cases.") diff --git a/node_helpers.py b/node_helpers.py index 43b9e829f..fee628790 100644 --- a/node_helpers.py +++ b/node_helpers.py @@ -1,3 +1,7 @@ +import hashlib + +from comfy.cli_args import args + from PIL import ImageFile, UnidentifiedImageError def conditioning_set_values(conditioning, values={}): @@ -22,3 +26,12 @@ def pillow(fn, arg): if prev_value is not None: ImageFile.LOAD_TRUNCATED_IMAGES = prev_value return x + +def hasher(): + hashfuncs = { + "md5": hashlib.md5, + "sha1": hashlib.sha1, + "sha256": hashlib.sha256, + "sha512": hashlib.sha512 + } + return hashfuncs[args.default_hashing_function] diff --git a/server.py b/server.py index 03c4c4219..23ca2fd33 100644 --- a/server.py +++ b/server.py @@ -25,6 +25,7 @@ import mimetypes from comfy.cli_args import args import comfy.utils import comfy.model_management +import node_helpers from app.frontend_management import FrontendManager from app.user_manager import UserManager @@ -161,10 +162,12 @@ class PromptServer(): return type_dir, dir_type def compare_image_hash(filepath, image): + hasher = node_helpers.hasher() + # function to compare hashes of two images to see if it already exists, fix to #3465 if os.path.exists(filepath): - a = hashlib.sha256() - b = hashlib.sha256() + a = hasher() + b = hasher() with open(filepath, "rb") as f: a.update(f.read()) b.update(image.file.read()) From 1cde6b2eff5721175725e9cc5f80191d8276e1e8 Mon Sep 17 00:00:00 2001 From: Chenlei Hu Date: Tue, 16 Jul 2024 21:15:08 -0400 Subject: [PATCH 095/133] Disallow use of eval with pylint (#4033) --- .github/workflows/pylint.yml | 23 +++++++++++++++++++++++ .pylintrc | 3 +++ 2 files changed, 26 insertions(+) create mode 100644 .github/workflows/pylint.yml create mode 100644 .pylintrc diff --git a/.github/workflows/pylint.yml b/.github/workflows/pylint.yml new file mode 100644 index 000000000..5effbea35 --- /dev/null +++ b/.github/workflows/pylint.yml @@ -0,0 +1,23 @@ +name: Python Linting + +on: [push, pull_request] + +jobs: + pylint: + name: Run Pylint + runs-on: ubuntu-latest + + steps: + - name: Checkout repository + uses: actions/checkout@v4 + + - name: Set up Python + uses: actions/setup-python@v2 + with: + python-version: 3.x + + - name: Install Pylint + run: pip install pylint + + - name: Run Pylint + run: pylint --rcfile=.pylintrc $(find . -type f -name "*.py") diff --git a/.pylintrc b/.pylintrc new file mode 100644 index 000000000..a5da56e57 --- /dev/null +++ b/.pylintrc @@ -0,0 +1,3 @@ +[MESSAGES CONTROL] +disable=all +enable=eval-used From 281ad42df4fae74ed11c1e7ff14cff6b7db6498c Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Wed, 17 Jul 2024 10:16:31 -0400 Subject: [PATCH 096/133] Fix lowvram union controlnet bug. --- comfy/cldm/cldm.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/comfy/cldm/cldm.py b/comfy/cldm/cldm.py index 4a58c823f..1d7294bd6 100644 --- a/comfy/cldm/cldm.py +++ b/comfy/cldm/cldm.py @@ -361,7 +361,7 @@ class ControlNet(nn.Module): controlnet_cond = self.input_hint_block(hint[idx], emb, context) feat_seq = torch.mean(controlnet_cond, dim=(2, 3)) if idx < len(control_type): - feat_seq += self.task_embedding[control_type[idx]] + feat_seq += self.task_embedding[control_type[idx]].to(dtype=feat_seq.dtype, device=feat_seq.device) inputs.append(feat_seq.unsqueeze(1)) condition_list.append(controlnet_cond) From 6f7869f365ca4ec34b017f9002b9dcb9bce56b1a Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Wed, 17 Jul 2024 13:05:38 -0400 Subject: [PATCH 097/133] Get clip vision image size from config. --- comfy/clip_vision.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/comfy/clip_vision.py b/comfy/clip_vision.py index acc86be85..ac39c6227 100644 --- a/comfy/clip_vision.py +++ b/comfy/clip_vision.py @@ -34,6 +34,7 @@ class ClipVisionModel(): with open(json_config) as f: config = json.load(f) + self.image_size = config.get("image_size", 224) self.load_device = comfy.model_management.text_encoder_device() offload_device = comfy.model_management.text_encoder_offload_device() self.dtype = comfy.model_management.text_encoder_dtype(self.load_device) @@ -50,7 +51,7 @@ class ClipVisionModel(): def encode_image(self, image): comfy.model_management.load_model_gpu(self.patcher) - pixel_values = clip_preprocess(image.to(self.load_device)).float() + pixel_values = clip_preprocess(image.to(self.load_device), size=self.image_size).float() out = self.model(pixel_values=pixel_values, intermediate_output=-2) outputs = Output() From 855789403b346c7d7772e2c7ed0a6a327f56047f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E5=96=B5=E5=93=A9=E4=B8=AA=E5=92=AA?= Date: Thu, 18 Jul 2024 01:12:50 +0800 Subject: [PATCH 098/133] support clip-vit-large-patch14-336 (#4042) * support clip-vit-large-patch14-336 * support clip-vit-large-patch14-336 --- comfy/clip_vision.py | 5 ++++- comfy/clip_vision_config_vitl_336.json | 18 ++++++++++++++++++ 2 files changed, 22 insertions(+), 1 deletion(-) create mode 100644 comfy/clip_vision_config_vitl_336.json diff --git a/comfy/clip_vision.py b/comfy/clip_vision.py index ac39c6227..20dc3345d 100644 --- a/comfy/clip_vision.py +++ b/comfy/clip_vision.py @@ -94,7 +94,10 @@ def load_clipvision_from_sd(sd, prefix="", convert_keys=False): elif "vision_model.encoder.layers.30.layer_norm1.weight" in sd: json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "clip_vision_config_h.json") elif "vision_model.encoder.layers.22.layer_norm1.weight" in sd: - json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "clip_vision_config_vitl.json") + if sd["vision_model.embeddings.position_embedding.weight"].shape[0] == 577: + json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "clip_vision_config_vitl_336.json") + else: + json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "clip_vision_config_vitl.json") else: return None diff --git a/comfy/clip_vision_config_vitl_336.json b/comfy/clip_vision_config_vitl_336.json new file mode 100644 index 000000000..f26945273 --- /dev/null +++ b/comfy/clip_vision_config_vitl_336.json @@ -0,0 +1,18 @@ +{ + "attention_dropout": 0.0, + "dropout": 0.0, + "hidden_act": "quick_gelu", + "hidden_size": 1024, + "image_size": 336, + "initializer_factor": 1.0, + "initializer_range": 0.02, + "intermediate_size": 4096, + "layer_norm_eps": 1e-5, + "model_type": "clip_vision_model", + "num_attention_heads": 16, + "num_channels": 3, + "num_hidden_layers": 24, + "patch_size": 14, + "projection_dim": 768, + "torch_dtype": "float32" +} From 374e093e09c94b528d7c9dfc337c65cc5c433ee3 Mon Sep 17 00:00:00 2001 From: bymyself Date: Wed, 17 Jul 2024 13:11:10 -0700 Subject: [PATCH 099/133] Disable audio widget trying to get previews (#4044) --- web/extensions/core/uploadAudio.js | 1 - 1 file changed, 1 deletion(-) diff --git a/web/extensions/core/uploadAudio.js b/web/extensions/core/uploadAudio.js index 0ac9cb807..6cc3863a1 100644 --- a/web/extensions/core/uploadAudio.js +++ b/web/extensions/core/uploadAudio.js @@ -17,7 +17,6 @@ function getResourceURL(subfolder, filename, type = "input") { "filename=" + encodeURIComponent(filename), "type=" + type, "subfolder=" + subfolder, - app.getPreviewFormatParam().substring(1), app.getRandParam().substring(1) ].join("&") From ff6ca2a892c25c5c6edb25c0c674445a7fe6b562 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Thu, 18 Jul 2024 17:20:05 -0400 Subject: [PATCH 100/133] Move PAG to model_patches/unet section. Move other unet model_patches nodes to model_patches/unet section. --- comfy_extras/nodes_freelunch.py | 4 ++-- comfy_extras/nodes_hypertile.py | 2 +- comfy_extras/nodes_pag.py | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/comfy_extras/nodes_freelunch.py b/comfy_extras/nodes_freelunch.py index c5ebcf26f..e3ac58447 100644 --- a/comfy_extras/nodes_freelunch.py +++ b/comfy_extras/nodes_freelunch.py @@ -34,7 +34,7 @@ class FreeU: RETURN_TYPES = ("MODEL",) FUNCTION = "patch" - CATEGORY = "model_patches" + CATEGORY = "model_patches/unet" def patch(self, model, b1, b2, s1, s2): model_channels = model.model.model_config.unet_config["model_channels"] @@ -73,7 +73,7 @@ class FreeU_V2: RETURN_TYPES = ("MODEL",) FUNCTION = "patch" - CATEGORY = "model_patches" + CATEGORY = "model_patches/unet" def patch(self, model, b1, b2, s1, s2): model_channels = model.model.model_config.unet_config["model_channels"] diff --git a/comfy_extras/nodes_hypertile.py b/comfy_extras/nodes_hypertile.py index ae55d23dd..227133f39 100644 --- a/comfy_extras/nodes_hypertile.py +++ b/comfy_extras/nodes_hypertile.py @@ -32,7 +32,7 @@ class HyperTile: RETURN_TYPES = ("MODEL",) FUNCTION = "patch" - CATEGORY = "model_patches" + CATEGORY = "model_patches/unet" def patch(self, model, tile_size, swap_size, max_depth, scale_depth): model_channels = model.model.model_config.unet_config["model_channels"] diff --git a/comfy_extras/nodes_pag.py b/comfy_extras/nodes_pag.py index 63f43fd62..aec78bd8a 100644 --- a/comfy_extras/nodes_pag.py +++ b/comfy_extras/nodes_pag.py @@ -19,7 +19,7 @@ class PerturbedAttentionGuidance: RETURN_TYPES = ("MODEL",) FUNCTION = "patch" - CATEGORY = "_for_testing" + CATEGORY = "model_patches/unet" def patch(self, model, scale): unet_block = "middle" From 011b11d8d767da3355555fe1253b162f55e985c5 Mon Sep 17 00:00:00 2001 From: bymyself Date: Thu, 18 Jul 2024 18:59:18 -0700 Subject: [PATCH 101/133] LoadAudio restores file value from workflow (#4043) * LoadAudio restores file value from workflow * use onAfterGraphConfigured * Don't use anonnymous function --- web/extensions/core/uploadAudio.js | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/web/extensions/core/uploadAudio.js b/web/extensions/core/uploadAudio.js index 6cc3863a1..9dfa029bf 100644 --- a/web/extensions/core/uploadAudio.js +++ b/web/extensions/core/uploadAudio.js @@ -149,6 +149,15 @@ app.registerExtension({ } audioWidget.callback = onAudioWidgetUpdate + // Load saved audio file widget values if restoring from workflow + const onGraphConfigured = node.onGraphConfigured; + node.onGraphConfigured = function() { + onGraphConfigured?.apply(this, arguments) + if (audioWidget.value) { + onAudioWidgetUpdate() + } + } + const fileInput = document.createElement("input") fileInput.type = "file" fileInput.accept = "audio/*" From 6ab8cad22ee376c0a9a506924cca278bb650afcc Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Fri, 19 Jul 2024 17:44:56 -0400 Subject: [PATCH 102/133] Implement beta sampling scheduler. It is based on: https://arxiv.org/abs/2407.12173 Add "beta" to the list of schedulers and the BetaSamplingScheduler node. --- comfy/samplers.py | 18 +++++++++++++++++- comfy_extras/nodes_custom_sampler.py | 20 ++++++++++++++++++++ 2 files changed, 37 insertions(+), 1 deletion(-) diff --git a/comfy/samplers.py b/comfy/samplers.py index bbf9219f7..0ab08a4cd 100644 --- a/comfy/samplers.py +++ b/comfy/samplers.py @@ -6,6 +6,8 @@ from comfy import model_management import math import logging import comfy.sampler_helpers +import scipy +import numpy def get_area_and_mult(conds, x_in, timestep_in): dims = tuple(x_in.shape[2:]) @@ -337,6 +339,18 @@ def normal_scheduler(model_sampling, steps, sgm=False, floor=False): sigs += [0.0] return torch.FloatTensor(sigs) +# Implemented based on: https://arxiv.org/abs/2407.12173 +def beta_scheduler(model_sampling, steps, alpha=0.6, beta=0.6): + total_timesteps = (len(model_sampling.sigmas) - 1) + ts = 1 - numpy.linspace(0, 1, steps, endpoint=False) + ts = numpy.rint(scipy.stats.beta.ppf(ts, alpha, beta) * total_timesteps) + + sigs = [] + for t in ts: + sigs += [float(model_sampling.sigmas[int(t)])] + sigs += [0.0] + return torch.FloatTensor(sigs) + def get_mask_aabb(masks): if masks.numel() == 0: return torch.zeros((0, 4), device=masks.device, dtype=torch.int) @@ -703,7 +717,7 @@ def sample(model, noise, positive, negative, cfg, device, sampler, sigmas, model return cfg_guider.sample(noise, latent_image, sampler, sigmas, denoise_mask, callback, disable_pbar, seed) -SCHEDULER_NAMES = ["normal", "karras", "exponential", "sgm_uniform", "simple", "ddim_uniform"] +SCHEDULER_NAMES = ["normal", "karras", "exponential", "sgm_uniform", "simple", "ddim_uniform", "beta"] SAMPLER_NAMES = KSAMPLER_NAMES + ["ddim", "uni_pc", "uni_pc_bh2"] def calculate_sigmas(model_sampling, scheduler_name, steps): @@ -719,6 +733,8 @@ def calculate_sigmas(model_sampling, scheduler_name, steps): sigmas = ddim_scheduler(model_sampling, steps) elif scheduler_name == "sgm_uniform": sigmas = normal_scheduler(model_sampling, steps, sgm=True) + elif scheduler_name == "beta": + sigmas = beta_scheduler(model_sampling, steps) else: logging.error("error invalid scheduler {}".format(scheduler_name)) return sigmas diff --git a/comfy_extras/nodes_custom_sampler.py b/comfy_extras/nodes_custom_sampler.py index 64a8c0631..b7ab88c27 100644 --- a/comfy_extras/nodes_custom_sampler.py +++ b/comfy_extras/nodes_custom_sampler.py @@ -111,6 +111,25 @@ class SDTurboScheduler: sigmas = torch.cat([sigmas, sigmas.new_zeros([1])]) return (sigmas, ) +class BetaSamplingScheduler: + @classmethod + def INPUT_TYPES(s): + return {"required": + {"model": ("MODEL",), + "steps": ("INT", {"default": 20, "min": 1, "max": 10000}), + "alpha": ("FLOAT", {"default": 0.6, "min": 0.0, "max": 50.0, "step":0.01, "round": False}), + "beta": ("FLOAT", {"default": 0.6, "min": 0.0, "max": 50.0, "step":0.01, "round": False}), + } + } + RETURN_TYPES = ("SIGMAS",) + CATEGORY = "sampling/custom_sampling/schedulers" + + FUNCTION = "get_sigmas" + + def get_sigmas(self, model, steps, alpha, beta): + sigmas = comfy.samplers.beta_scheduler(model.get_model_object("model_sampling"), steps, alpha=alpha, beta=beta) + return (sigmas, ) + class VPScheduler: @classmethod def INPUT_TYPES(s): @@ -638,6 +657,7 @@ NODE_CLASS_MAPPINGS = { "ExponentialScheduler": ExponentialScheduler, "PolyexponentialScheduler": PolyexponentialScheduler, "VPScheduler": VPScheduler, + "BetaSamplingScheduler": BetaSamplingScheduler, "SDTurboScheduler": SDTurboScheduler, "KSamplerSelect": KSamplerSelect, "SamplerEulerAncestral": SamplerEulerAncestral, From 11b74147ee67944c1707b4cc0b4db1cedc73aacc Mon Sep 17 00:00:00 2001 From: Greg Wainer Date: Fri, 19 Jul 2024 17:39:04 -0500 Subject: [PATCH 103/133] Fix/webp exif little endian (#4061) * Fix for isLittleEndian flag in parseExifData. * Add break after reading first exif chunk in getWebpMetadata. --- web/scripts/pnginfo.js | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/web/scripts/pnginfo.js b/web/scripts/pnginfo.js index 2c03cf74a..8b1b2c61c 100644 --- a/web/scripts/pnginfo.js +++ b/web/scripts/pnginfo.js @@ -49,7 +49,7 @@ export function getPngMetadata(file) { function parseExifData(exifData) { // Check for the correct TIFF header (0x4949 for little-endian or 0x4D4D for big-endian) - const isLittleEndian = new Uint16Array(exifData.slice(0, 2))[0] === 0x4949; + const isLittleEndian = String.fromCharCode(...exifData.slice(0, 2)) === "II"; // Function to read 16-bit and 32-bit integers from binary data function readInt(offset, isLittleEndian, length) { @@ -134,6 +134,7 @@ export function getWebpMetadata(file) { let index = value.indexOf(':'); txt_chunks[value.slice(0, index)] = value.slice(index + 1); } + break; } offset += 8 + chunk_length; From 95fa9545f167ccf4010849c70045a67a8800aa31 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Sat, 20 Jul 2024 12:27:42 -0400 Subject: [PATCH 104/133] Only append zero to noise schedule if last sigma isn't zero. --- comfy/samplers.py | 20 ++++++++++++++++---- 1 file changed, 16 insertions(+), 4 deletions(-) diff --git a/comfy/samplers.py b/comfy/samplers.py index 0ab08a4cd..3f7633814 100644 --- a/comfy/samplers.py +++ b/comfy/samplers.py @@ -313,13 +313,18 @@ def simple_scheduler(model_sampling, steps): def ddim_scheduler(model_sampling, steps): s = model_sampling sigs = [] - ss = max(len(s.sigmas) // steps, 1) x = 1 + if math.isclose(float(s.sigmas[x]), 0, abs_tol=0.00001): + steps += 1 + sigs = [] + else: + sigs = [0.0] + + ss = max(len(s.sigmas) // steps, 1) while x < len(s.sigmas): sigs += [float(s.sigmas[x])] x += ss sigs = sigs[::-1] - sigs += [0.0] return torch.FloatTensor(sigs) def normal_scheduler(model_sampling, steps, sgm=False, floor=False): @@ -327,16 +332,23 @@ def normal_scheduler(model_sampling, steps, sgm=False, floor=False): start = s.timestep(s.sigma_max) end = s.timestep(s.sigma_min) + append_zero = True if sgm: timesteps = torch.linspace(start, end, steps + 1)[:-1] else: + if math.isclose(float(s.sigma(end)), 0, abs_tol=0.00001): + steps += 1 + append_zero = False timesteps = torch.linspace(start, end, steps) sigs = [] for x in range(len(timesteps)): ts = timesteps[x] - sigs.append(s.sigma(ts)) - sigs += [0.0] + sigs.append(float(s.sigma(ts))) + + if append_zero: + sigs += [0.0] + return torch.FloatTensor(sigs) # Implemented based on: https://arxiv.org/abs/2407.12173 From 5b69cfe7c343e8672fc350ec35e17f0d046297ca Mon Sep 17 00:00:00 2001 From: Chenlei Hu Date: Sun, 21 Jul 2024 15:29:10 -0400 Subject: [PATCH 105/133] Add timestamp to execution messages (#4076) * Add timestamp to execution messages * Add execution_end message * Rename to execution_success --- execution.py | 10 +++++++++- 1 file changed, 9 insertions(+), 1 deletion(-) diff --git a/execution.py b/execution.py index 8b3d116c6..0a2e62e7e 100644 --- a/execution.py +++ b/execution.py @@ -3,6 +3,7 @@ import copy import logging import threading import heapq +import time import traceback import inspect from typing import List, Literal, NamedTuple, Optional @@ -283,7 +284,11 @@ class PromptExecutor: self.success = True self.old_prompt = {} - def add_message(self, event, data, broadcast: bool): + def add_message(self, event, data: dict, broadcast: bool): + data = { + **data, + "timestamp": int(time.time() * 1000), + } self.status_messages.append((event, data)) if self.server.client_id is not None or broadcast: self.server.send_sync(event, data, self.server.client_id) @@ -394,6 +399,9 @@ class PromptExecutor: if self.success is not True: self.handle_execution_error(prompt_id, prompt, current_outputs, executed, error, ex) break + else: + # Only execute when the while-loop ends without break + self.add_message("execution_success", { "prompt_id": prompt_id }, broadcast=False) for x in executed: self.old_prompt[x] = copy.deepcopy(prompt[x]) From f836e69346844c65dcf2418346db9a9a9b32a445 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Sun, 21 Jul 2024 16:16:45 -0400 Subject: [PATCH 106/133] Fix bug with SaveAudio node with --gpu-only --- comfy_extras/nodes_audio.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/comfy_extras/nodes_audio.py b/comfy_extras/nodes_audio.py index 64d241e98..6f0e26365 100644 --- a/comfy_extras/nodes_audio.py +++ b/comfy_extras/nodes_audio.py @@ -147,7 +147,7 @@ class SaveAudio: for x in extra_pnginfo: metadata[x] = json.dumps(extra_pnginfo[x]) - for (batch_number, waveform) in enumerate(audio["waveform"]): + for (batch_number, waveform) in enumerate(audio["waveform"].cpu()): filename_with_batch_num = filename.replace("%batch_num%", str(batch_number)) file = f"{filename_with_batch_num}_{counter:05}_.flac" From 6045ed31f898e278e4693f2a4e210393fc9153d0 Mon Sep 17 00:00:00 2001 From: Chenlei Hu Date: Sun, 21 Jul 2024 21:15:01 -0400 Subject: [PATCH 107/133] Supress frontend exception on unhandled message type (#4078) * Supress frontend exception on unhandled message type * nit --- web/scripts/api.js | 3 +++ 1 file changed, 3 insertions(+) diff --git a/web/scripts/api.js b/web/scripts/api.js index 39f0a9bb2..03c3fb607 100644 --- a/web/scripts/api.js +++ b/web/scripts/api.js @@ -136,6 +136,9 @@ class ComfyApi extends EventTarget { case "execution_start": this.dispatchEvent(new CustomEvent("execution_start", { detail: msg.data })); break; + case "execution_success": + this.dispatchEvent(new CustomEvent("execution_success", { detail: msg.data })); + break; case "execution_error": this.dispatchEvent(new CustomEvent("execution_error", { detail: msg.data })); break; From 4151fbfa8ab705d0a7e632c7d7c23ea5c436a60b Mon Sep 17 00:00:00 2001 From: Chenlei Hu Date: Mon, 22 Jul 2024 11:27:32 -0400 Subject: [PATCH 108/133] Add error message on union controlnet (#4081) --- comfy/cldm/cldm.py | 13 +++++++++++++ comfy/cldm/control_types.py | 11 +++++++++++ comfy_extras/nodes_controlnet.py | 12 +----------- 3 files changed, 25 insertions(+), 11 deletions(-) create mode 100644 comfy/cldm/control_types.py diff --git a/comfy/cldm/cldm.py b/comfy/cldm/cldm.py index 1d7294bd6..9ec64a227 100644 --- a/comfy/cldm/cldm.py +++ b/comfy/cldm/cldm.py @@ -13,6 +13,7 @@ from ..ldm.modules.diffusionmodules.util import ( from ..ldm.modules.attention import SpatialTransformer from ..ldm.modules.diffusionmodules.openaimodel import UNetModel, TimestepEmbedSequential, ResBlock, Downsample from ..ldm.util import exists +from .control_types import UNION_CONTROLNET_TYPES from collections import OrderedDict import comfy.ops from comfy.ldm.modules.attention import optimized_attention @@ -390,6 +391,18 @@ class ControlNet(nn.Module): if self.control_add_embedding is not None: #Union Controlnet control_type = kwargs.get("control_type", []) + if any([c >= self.num_control_type for c in control_type]): + max_type = max(control_type) + max_type_name = { + v: k for k, v in UNION_CONTROLNET_TYPES.items() + }[max_type] + raise ValueError( + f"Control type {max_type_name}({max_type}) is out of range for the number of control types" + + f"({self.num_control_type}) supported.\n" + + "Please consider using the ProMax ControlNet Union model.\n" + + "https://huggingface.co/xinsir/controlnet-union-sdxl-1.0/tree/main" + ) + emb += self.control_add_embedding(control_type, emb.dtype, emb.device) if len(control_type) > 0: if len(hint.shape) < 5: diff --git a/comfy/cldm/control_types.py b/comfy/cldm/control_types.py new file mode 100644 index 000000000..fd6e56e8f --- /dev/null +++ b/comfy/cldm/control_types.py @@ -0,0 +1,11 @@ +UNION_CONTROLNET_TYPES = { + "auto": -1, + "openpose": 0, + "depth": 1, + "hed/pidi/scribble/ted": 2, + "canny/lineart/anime_lineart/mlsd": 3, + "normal": 4, + "segment": 5, + "tile": 6, + "repaint": 7, +} diff --git a/comfy_extras/nodes_controlnet.py b/comfy_extras/nodes_controlnet.py index ef7cfc6ab..566d51e33 100644 --- a/comfy_extras/nodes_controlnet.py +++ b/comfy_extras/nodes_controlnet.py @@ -1,14 +1,4 @@ - -UNION_CONTROLNET_TYPES = {"auto": -1, - "openpose": 0, - "depth": 1, - "hed/pidi/scribble/ted": 2, - "canny/lineart/anime_lineart/mlsd": 3, - "normal": 4, - "segment": 5, - "tile": 6, - "repaint": 7, - } +from comfy.cldm.control_types import UNION_CONTROLNET_TYPES class SetUnionControlNetType: @classmethod From b2c995f623fd7169db87dfd6d356e535d0bb99ce Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Mon, 22 Jul 2024 11:30:38 -0400 Subject: [PATCH 109/133] "auto" type is only relevant to the SetUnionControlNetType node. --- comfy/cldm/control_types.py | 1 - comfy_extras/nodes_controlnet.py | 4 ++-- 2 files changed, 2 insertions(+), 3 deletions(-) diff --git a/comfy/cldm/control_types.py b/comfy/cldm/control_types.py index fd6e56e8f..4128631a3 100644 --- a/comfy/cldm/control_types.py +++ b/comfy/cldm/control_types.py @@ -1,5 +1,4 @@ UNION_CONTROLNET_TYPES = { - "auto": -1, "openpose": 0, "depth": 1, "hed/pidi/scribble/ted": 2, diff --git a/comfy_extras/nodes_controlnet.py b/comfy_extras/nodes_controlnet.py index 566d51e33..0773c8a5b 100644 --- a/comfy_extras/nodes_controlnet.py +++ b/comfy_extras/nodes_controlnet.py @@ -4,7 +4,7 @@ class SetUnionControlNetType: @classmethod def INPUT_TYPES(s): return {"required": {"control_net": ("CONTROL_NET", ), - "type": (list(UNION_CONTROLNET_TYPES.keys()),) + "type": (["auto"] + list(UNION_CONTROLNET_TYPES.keys()),) }} CATEGORY = "conditioning/controlnet" @@ -14,7 +14,7 @@ class SetUnionControlNetType: def set_controlnet_type(self, control_net, type): control_net = control_net.copy() - type_number = UNION_CONTROLNET_TYPES[type] + type_number = UNION_CONTROLNET_TYPES.get(type, -1) if type_number >= 0: control_net.set_extra_arg("control_type", [type_number]) else: From 14764aa2e2e2b282c4a4dffbfab4c01d3e46e8a7 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Mon, 22 Jul 2024 12:21:45 -0400 Subject: [PATCH 110/133] Rename LLAMATokenizer to SPieceTokenizer. --- comfy/text_encoders/aura_t5.py | 4 ++-- .../text_encoders/{llama_tokenizer.py => spiece_tokenizer.py} | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) rename comfy/text_encoders/{llama_tokenizer.py => spiece_tokenizer.py} (90%) diff --git a/comfy/text_encoders/aura_t5.py b/comfy/text_encoders/aura_t5.py index 6b9e4fe53..409867af3 100644 --- a/comfy/text_encoders/aura_t5.py +++ b/comfy/text_encoders/aura_t5.py @@ -1,5 +1,5 @@ from comfy import sd1_clip -from .llama_tokenizer import LLAMATokenizer +from .spiece_tokenizer import SPieceTokenizer import comfy.text_encoders.t5 import os @@ -11,7 +11,7 @@ class PT5XlModel(sd1_clip.SDClipModel): class PT5XlTokenizer(sd1_clip.SDTokenizer): def __init__(self, embedding_directory=None): tokenizer_path = os.path.join(os.path.join(os.path.dirname(os.path.realpath(__file__)), "t5_pile_tokenizer"), "tokenizer.model") - super().__init__(tokenizer_path, pad_with_end=False, embedding_size=2048, embedding_key='pile_t5xl', tokenizer_class=LLAMATokenizer, has_start_token=False, pad_to_max_length=False, max_length=99999999, min_length=256, pad_token=1) + super().__init__(tokenizer_path, pad_with_end=False, embedding_size=2048, embedding_key='pile_t5xl', tokenizer_class=SPieceTokenizer, has_start_token=False, pad_to_max_length=False, max_length=99999999, min_length=256, pad_token=1) class AuraT5Tokenizer(sd1_clip.SD1Tokenizer): def __init__(self, embedding_directory=None): diff --git a/comfy/text_encoders/llama_tokenizer.py b/comfy/text_encoders/spiece_tokenizer.py similarity index 90% rename from comfy/text_encoders/llama_tokenizer.py rename to comfy/text_encoders/spiece_tokenizer.py index a6db1da62..d611d5bb7 100644 --- a/comfy/text_encoders/llama_tokenizer.py +++ b/comfy/text_encoders/spiece_tokenizer.py @@ -1,9 +1,9 @@ import os -class LLAMATokenizer: +class SPieceTokenizer: @staticmethod def from_pretrained(path): - return LLAMATokenizer(path) + return SPieceTokenizer(path) def __init__(self, tokenizer_path): import sentencepiece From 334ba48cea2961994e92c2fb25de9417b19897ed Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Tue, 23 Jul 2024 14:13:32 -0400 Subject: [PATCH 111/133] More generic unet prefix detection code. --- comfy/model_detection.py | 21 +++++++++++++++------ 1 file changed, 15 insertions(+), 6 deletions(-) diff --git a/comfy/model_detection.py b/comfy/model_detection.py index c62e2b822..ae88eeb97 100644 --- a/comfy/model_detection.py +++ b/comfy/model_detection.py @@ -261,13 +261,22 @@ def model_config_from_unet(state_dict, unet_key_prefix, use_base_if_no_match=Fal return model_config def unet_prefix_from_state_dict(state_dict): - if "model.model.postprocess_conv.weight" in state_dict: #audio models - unet_key_prefix = "model.model." - elif "model.double_layers.0.attn.w1q.weight" in state_dict: #aura flow - unet_key_prefix = "model." + candidates = ["model.diffusion_model.", #ldm/sgm models + "model.model.", #audio models + ] + counts = {k: 0 for k in candidates} + for k in state_dict: + for c in candidates: + if k.startswith(c): + counts[c] += 1 + break + + top = max(counts, key=counts.get) + if counts[top] > 5: + return top else: - unet_key_prefix = "model.diffusion_model." - return unet_key_prefix + return "model." #aura flow and others + def convert_config(unet_config): new_config = unet_config.copy() From 88ed89303463ab030654ef87f7f54d72ee3979bb Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Tue, 23 Jul 2024 14:17:42 -0400 Subject: [PATCH 112/133] Allow SPieceTokenizer to load model from a byte string. --- comfy/text_encoders/spiece_tokenizer.py | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) diff --git a/comfy/text_encoders/spiece_tokenizer.py b/comfy/text_encoders/spiece_tokenizer.py index d611d5bb7..fa303da0b 100644 --- a/comfy/text_encoders/spiece_tokenizer.py +++ b/comfy/text_encoders/spiece_tokenizer.py @@ -1,14 +1,18 @@ import os class SPieceTokenizer: + add_eos = True + @staticmethod def from_pretrained(path): return SPieceTokenizer(path) def __init__(self, tokenizer_path): import sentencepiece - self.tokenizer = sentencepiece.SentencePieceProcessor(model_file=tokenizer_path) - self.end = self.tokenizer.eos_id() + if isinstance(tokenizer_path, bytes): + self.tokenizer = sentencepiece.SentencePieceProcessor(model_proto=tokenizer_path, add_eos=self.add_eos) + else: + self.tokenizer = sentencepiece.SentencePieceProcessor(model_file=tokenizer_path, add_eos=self.add_eos) def get_vocab(self): out = {} @@ -18,5 +22,4 @@ class SPieceTokenizer: def __call__(self, string): out = self.tokenizer.encode(string) - out += [self.end] return {"input_ids": out} From 0a4c49c57ca792535174d27aea87449257527b2f Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Tue, 23 Jul 2024 15:35:28 -0400 Subject: [PATCH 113/133] Support MT5. --- comfy/text_encoders/t5.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/comfy/text_encoders/t5.py b/comfy/text_encoders/t5.py index 448c5aad3..ba628478d 100644 --- a/comfy/text_encoders/t5.py +++ b/comfy/text_encoders/t5.py @@ -223,7 +223,7 @@ class T5(torch.nn.Module): self.num_layers = config_dict["num_layers"] model_dim = config_dict["d_model"] - self.encoder = T5Stack(self.num_layers, model_dim, model_dim, config_dict["d_ff"], config_dict["dense_act_fn"], config_dict["is_gated_act"], config_dict["num_heads"], config_dict["model_type"] == "t5", dtype, device, operations) + self.encoder = T5Stack(self.num_layers, model_dim, model_dim, config_dict["d_ff"], config_dict["dense_act_fn"], config_dict["is_gated_act"], config_dict["num_heads"], config_dict["model_type"] != "umt5", dtype, device, operations) self.dtype = dtype self.shared = torch.nn.Embedding(config_dict["vocab_size"], model_dim, device=device) From 10b43ceea52d86395d10a7029eda2822fd65dfd1 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Wed, 24 Jul 2024 01:12:59 -0400 Subject: [PATCH 114/133] Remove duplicate code. --- comfy/ldm/modules/diffusionmodules/mmdit.py | 29 ++------------------- 1 file changed, 2 insertions(+), 27 deletions(-) diff --git a/comfy/ldm/modules/diffusionmodules/mmdit.py b/comfy/ldm/modules/diffusionmodules/mmdit.py index 927451534..f37f7ff77 100644 --- a/comfy/ldm/modules/diffusionmodules/mmdit.py +++ b/comfy/ldm/modules/diffusionmodules/mmdit.py @@ -7,6 +7,7 @@ import torch import torch.nn as nn from .. import attention from einops import rearrange, repeat +from .util import timestep_embedding def default(x, y): if x is not None: @@ -230,34 +231,8 @@ class TimestepEmbedder(nn.Module): ) self.frequency_embedding_size = frequency_embedding_size - @staticmethod - def timestep_embedding(t, dim, max_period=10000): - """ - Create sinusoidal timestep embeddings. - :param t: a 1-D Tensor of N indices, one per batch element. - These may be fractional. - :param dim: the dimension of the output. - :param max_period: controls the minimum frequency of the embeddings. - :return: an (N, D) Tensor of positional embeddings. - """ - half = dim // 2 - freqs = torch.exp( - -math.log(max_period) - * torch.arange(start=0, end=half, dtype=torch.float32, device=t.device) - / half - ) - args = t[:, None].float() * freqs[None] - embedding = torch.cat([torch.cos(args), torch.sin(args)], dim=-1) - if dim % 2: - embedding = torch.cat( - [embedding, torch.zeros_like(embedding[:, :1])], dim=-1 - ) - if torch.is_floating_point(t): - embedding = embedding.to(dtype=t.dtype) - return embedding - def forward(self, t, dtype, **kwargs): - t_freq = self.timestep_embedding(t, self.frequency_embedding_size).to(dtype) + t_freq = timestep_embedding(t, self.frequency_embedding_size).to(dtype) t_emb = self.mlp(t_freq) return t_emb From 19944ad252106e46a40e0b952c86c1cebc8486ab Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Wed, 24 Jul 2024 12:49:29 -0400 Subject: [PATCH 115/133] Add code to fix issues with new pytorch version on the standalone. --- fix_torch.py | 16 ++++++++++++++++ main.py | 6 ++++++ 2 files changed, 22 insertions(+) create mode 100644 fix_torch.py diff --git a/fix_torch.py b/fix_torch.py new file mode 100644 index 000000000..b60a0bbb4 --- /dev/null +++ b/fix_torch.py @@ -0,0 +1,16 @@ +import importlib.util +import shutil +import os +import ctypes +import logging + + +torch_spec = importlib.util.find_spec("torch") +for folder in torch_spec.submodule_search_locations: + lib_folder = os.path.join(folder, "lib") + test_file = os.path.join(lib_folder, "fbgemm.dll") + try: + mydll = ctypes.cdll.LoadLibrary(test_file) + except FileNotFoundError as e: + logging.warning("Detected pytorch version with libomp issue, patching.") + shutil.copyfile(os.path.join(lib_folder, "libiomp5md.dll"), os.path.join(lib_folder, "libomp140.x86_64.dll")) diff --git a/main.py b/main.py index 196351a3d..479643b84 100644 --- a/main.py +++ b/main.py @@ -74,6 +74,12 @@ if __name__ == "__main__": import cuda_malloc +if args.windows_standalone_build: + try: + import fix_torch + except: + pass + import comfy.utils import yaml From ce80e69fb89f5f8e48273977e94b7a3b0421f6e6 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Wed, 24 Jul 2024 13:50:34 -0400 Subject: [PATCH 116/133] Avoid loading the dll when it's not necessary. --- fix_torch.py | 10 +++++++++- 1 file changed, 9 insertions(+), 1 deletion(-) diff --git a/fix_torch.py b/fix_torch.py index b60a0bbb4..e350f5c7d 100644 --- a/fix_torch.py +++ b/fix_torch.py @@ -9,8 +9,16 @@ torch_spec = importlib.util.find_spec("torch") for folder in torch_spec.submodule_search_locations: lib_folder = os.path.join(folder, "lib") test_file = os.path.join(lib_folder, "fbgemm.dll") + dest = os.path.join(lib_folder, "libomp140.x86_64.dll") + if os.path.exists(dest): + break + + with open(test_file, 'rb') as f: + contents = f.read() + if b"libomp140.x86_64.dll" not in contents: + break try: mydll = ctypes.cdll.LoadLibrary(test_file) except FileNotFoundError as e: logging.warning("Detected pytorch version with libomp issue, patching.") - shutil.copyfile(os.path.join(lib_folder, "libiomp5md.dll"), os.path.join(lib_folder, "libomp140.x86_64.dll")) + shutil.copyfile(os.path.join(lib_folder, "libiomp5md.dll"), dest) From 10c919f4c77b3615f0efa9014e8b77f294c23a2d Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Wed, 24 Jul 2024 16:43:53 -0400 Subject: [PATCH 117/133] Make it possible to load tokenizer data from checkpoints. --- comfy/sd.py | 6 +++--- comfy/sd1_clip.py | 6 +++--- comfy/sd2_clip.py | 6 +++--- comfy/sdxl_clip.py | 10 +++++----- comfy/text_encoders/aura_t5.py | 6 +++--- comfy/text_encoders/sa_t5.py | 6 +++--- comfy/text_encoders/sd3_clip.py | 13 ++----------- comfy/text_encoders/spiece_tokenizer.py | 4 ++++ 8 files changed, 26 insertions(+), 31 deletions(-) diff --git a/comfy/sd.py b/comfy/sd.py index 17df5faff..fe6ce4c96 100644 --- a/comfy/sd.py +++ b/comfy/sd.py @@ -60,7 +60,7 @@ def load_lora_for_models(model, clip, lora, strength_model, strength_clip): class CLIP: - def __init__(self, target=None, embedding_directory=None, no_init=False): + def __init__(self, target=None, embedding_directory=None, no_init=False, tokenizer_data={}): if no_init: return params = target.params.copy() @@ -79,7 +79,7 @@ class CLIP: if not model_management.supports_cast(load_device, dt): load_device = offload_device - self.tokenizer = tokenizer(embedding_directory=embedding_directory) + self.tokenizer = tokenizer(embedding_directory=embedding_directory, tokenizer_data=tokenizer_data) self.patcher = comfy.model_patcher.ModelPatcher(self.cond_stage_model, load_device=load_device, offload_device=offload_device) self.layer_idx = None logging.debug("CLIP model load device: {}, offload device: {}".format(load_device, offload_device)) @@ -520,7 +520,7 @@ def load_checkpoint_guess_config(ckpt_path, output_vae=True, output_clip=True, o if clip_target is not None: clip_sd = model_config.process_clip_state_dict(sd) if len(clip_sd) > 0: - clip = CLIP(clip_target, embedding_directory=embedding_directory) + clip = CLIP(clip_target, embedding_directory=embedding_directory, tokenizer_data=clip_sd) m, u = clip.load_sd(clip_sd, full_model=True) if len(m) > 0: m_filter = list(filter(lambda a: ".logit_scale" not in a and ".transformer.text_projection.weight" not in a, m)) diff --git a/comfy/sd1_clip.py b/comfy/sd1_clip.py index 565ad69da..ea66da00b 100644 --- a/comfy/sd1_clip.py +++ b/comfy/sd1_clip.py @@ -386,7 +386,7 @@ def load_embed(embedding_name, embedding_directory, embedding_size, embed_key=No return embed_out class SDTokenizer: - def __init__(self, tokenizer_path=None, max_length=77, pad_with_end=True, embedding_directory=None, embedding_size=768, embedding_key='clip_l', tokenizer_class=CLIPTokenizer, has_start_token=True, pad_to_max_length=True, min_length=None, pad_token=None): + def __init__(self, tokenizer_path=None, max_length=77, pad_with_end=True, embedding_directory=None, embedding_size=768, embedding_key='clip_l', tokenizer_class=CLIPTokenizer, has_start_token=True, pad_to_max_length=True, min_length=None, pad_token=None, tokenizer_data={}): if tokenizer_path is None: tokenizer_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "sd1_tokenizer") self.tokenizer = tokenizer_class.from_pretrained(tokenizer_path) @@ -521,10 +521,10 @@ class SDTokenizer: class SD1Tokenizer: - def __init__(self, embedding_directory=None, clip_name="l", tokenizer=SDTokenizer): + def __init__(self, embedding_directory=None, tokenizer_data={}, clip_name="l", tokenizer=SDTokenizer): self.clip_name = clip_name self.clip = "clip_{}".format(self.clip_name) - setattr(self, self.clip, tokenizer(embedding_directory=embedding_directory)) + setattr(self, self.clip, tokenizer(embedding_directory=embedding_directory, tokenizer_data=tokenizer_data)) def tokenize_with_weights(self, text:str, return_word_ids=False): out = {} diff --git a/comfy/sd2_clip.py b/comfy/sd2_clip.py index d14b44544..8ea8e1cd0 100644 --- a/comfy/sd2_clip.py +++ b/comfy/sd2_clip.py @@ -11,12 +11,12 @@ class SD2ClipHModel(sd1_clip.SDClipModel): super().__init__(device=device, freeze=freeze, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, dtype=dtype, special_tokens={"start": 49406, "end": 49407, "pad": 0}) class SD2ClipHTokenizer(sd1_clip.SDTokenizer): - def __init__(self, tokenizer_path=None, embedding_directory=None): + def __init__(self, tokenizer_path=None, embedding_directory=None, tokenizer_data={}): super().__init__(tokenizer_path, pad_with_end=False, embedding_directory=embedding_directory, embedding_size=1024) class SD2Tokenizer(sd1_clip.SD1Tokenizer): - def __init__(self, embedding_directory=None): - super().__init__(embedding_directory=embedding_directory, clip_name="h", tokenizer=SD2ClipHTokenizer) + def __init__(self, embedding_directory=None, tokenizer_data={}): + super().__init__(embedding_directory=embedding_directory, tokenizer_data=tokenizer_data, clip_name="h", tokenizer=SD2ClipHTokenizer) class SD2ClipModel(sd1_clip.SD1ClipModel): def __init__(self, device="cpu", dtype=None, **kwargs): diff --git a/comfy/sdxl_clip.py b/comfy/sdxl_clip.py index 1257cba1e..57c30f2e6 100644 --- a/comfy/sdxl_clip.py +++ b/comfy/sdxl_clip.py @@ -16,12 +16,12 @@ class SDXLClipG(sd1_clip.SDClipModel): return super().load_sd(sd) class SDXLClipGTokenizer(sd1_clip.SDTokenizer): - def __init__(self, tokenizer_path=None, embedding_directory=None): + def __init__(self, tokenizer_path=None, embedding_directory=None, tokenizer_data={}): super().__init__(tokenizer_path, pad_with_end=False, embedding_directory=embedding_directory, embedding_size=1280, embedding_key='clip_g') class SDXLTokenizer: - def __init__(self, embedding_directory=None): + def __init__(self, embedding_directory=None, tokenizer_data={}): self.clip_l = sd1_clip.SDTokenizer(embedding_directory=embedding_directory) self.clip_g = SDXLClipGTokenizer(embedding_directory=embedding_directory) @@ -68,12 +68,12 @@ class SDXLRefinerClipModel(sd1_clip.SD1ClipModel): class StableCascadeClipGTokenizer(sd1_clip.SDTokenizer): - def __init__(self, tokenizer_path=None, embedding_directory=None): + def __init__(self, tokenizer_path=None, embedding_directory=None, tokenizer_data={}): super().__init__(tokenizer_path, pad_with_end=True, embedding_directory=embedding_directory, embedding_size=1280, embedding_key='clip_g') class StableCascadeTokenizer(sd1_clip.SD1Tokenizer): - def __init__(self, embedding_directory=None): - super().__init__(embedding_directory=embedding_directory, clip_name="g", tokenizer=StableCascadeClipGTokenizer) + def __init__(self, embedding_directory=None, tokenizer_data={}): + super().__init__(embedding_directory=embedding_directory, tokenizer_data=tokenizer_data, clip_name="g", tokenizer=StableCascadeClipGTokenizer) class StableCascadeClipG(sd1_clip.SDClipModel): def __init__(self, device="cpu", max_length=77, freeze=True, layer="hidden", layer_idx=-1, dtype=None): diff --git a/comfy/text_encoders/aura_t5.py b/comfy/text_encoders/aura_t5.py index 409867af3..8500c7b70 100644 --- a/comfy/text_encoders/aura_t5.py +++ b/comfy/text_encoders/aura_t5.py @@ -9,13 +9,13 @@ class PT5XlModel(sd1_clip.SDClipModel): super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, dtype=dtype, special_tokens={"end": 2, "pad": 1}, model_class=comfy.text_encoders.t5.T5, enable_attention_masks=True, zero_out_masked=True) class PT5XlTokenizer(sd1_clip.SDTokenizer): - def __init__(self, embedding_directory=None): + def __init__(self, embedding_directory=None, tokenizer_data={}): tokenizer_path = os.path.join(os.path.join(os.path.dirname(os.path.realpath(__file__)), "t5_pile_tokenizer"), "tokenizer.model") super().__init__(tokenizer_path, pad_with_end=False, embedding_size=2048, embedding_key='pile_t5xl', tokenizer_class=SPieceTokenizer, has_start_token=False, pad_to_max_length=False, max_length=99999999, min_length=256, pad_token=1) class AuraT5Tokenizer(sd1_clip.SD1Tokenizer): - def __init__(self, embedding_directory=None): - super().__init__(embedding_directory=embedding_directory, clip_name="pile_t5xl", tokenizer=PT5XlTokenizer) + def __init__(self, embedding_directory=None, tokenizer_data={}): + super().__init__(embedding_directory=embedding_directory, tokenizer_data=tokenizer_data, clip_name="pile_t5xl", tokenizer=PT5XlTokenizer) class AuraT5Model(sd1_clip.SD1ClipModel): def __init__(self, device="cpu", dtype=None, **kwargs): diff --git a/comfy/text_encoders/sa_t5.py b/comfy/text_encoders/sa_t5.py index 038558e7a..189f8c181 100644 --- a/comfy/text_encoders/sa_t5.py +++ b/comfy/text_encoders/sa_t5.py @@ -9,13 +9,13 @@ class T5BaseModel(sd1_clip.SDClipModel): super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, dtype=dtype, special_tokens={"end": 1, "pad": 0}, model_class=comfy.text_encoders.t5.T5, enable_attention_masks=True, zero_out_masked=True) class T5BaseTokenizer(sd1_clip.SDTokenizer): - def __init__(self, embedding_directory=None): + def __init__(self, embedding_directory=None, tokenizer_data={}): tokenizer_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "t5_tokenizer") super().__init__(tokenizer_path, pad_with_end=False, embedding_size=768, embedding_key='t5base', tokenizer_class=T5TokenizerFast, has_start_token=False, pad_to_max_length=False, max_length=99999999, min_length=128) class SAT5Tokenizer(sd1_clip.SD1Tokenizer): - def __init__(self, embedding_directory=None): - super().__init__(embedding_directory=embedding_directory, clip_name="t5base", tokenizer=T5BaseTokenizer) + def __init__(self, embedding_directory=None, tokenizer_data={}): + super().__init__(embedding_directory=embedding_directory, tokenizer_data=tokenizer_data, clip_name="t5base", tokenizer=T5BaseTokenizer) class SAT5Model(sd1_clip.SD1ClipModel): def __init__(self, device="cpu", dtype=None, **kwargs): diff --git a/comfy/text_encoders/sd3_clip.py b/comfy/text_encoders/sd3_clip.py index 70127e509..286c5dc05 100644 --- a/comfy/text_encoders/sd3_clip.py +++ b/comfy/text_encoders/sd3_clip.py @@ -13,22 +13,13 @@ class T5XXLModel(sd1_clip.SDClipModel): super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, dtype=dtype, special_tokens={"end": 1, "pad": 0}, model_class=comfy.text_encoders.t5.T5) class T5XXLTokenizer(sd1_clip.SDTokenizer): - def __init__(self, embedding_directory=None): + def __init__(self, embedding_directory=None, tokenizer_data={}): tokenizer_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "t5_tokenizer") super().__init__(tokenizer_path, pad_with_end=False, embedding_size=4096, embedding_key='t5xxl', tokenizer_class=T5TokenizerFast, has_start_token=False, pad_to_max_length=False, max_length=99999999, min_length=77) -class SDT5XXLTokenizer(sd1_clip.SD1Tokenizer): - def __init__(self, embedding_directory=None): - super().__init__(embedding_directory=embedding_directory, clip_name="t5xxl", tokenizer=T5XXLTokenizer) - -class SDT5XXLModel(sd1_clip.SD1ClipModel): - def __init__(self, device="cpu", dtype=None, **kwargs): - super().__init__(device=device, dtype=dtype, clip_name="t5xxl", clip_model=T5XXLModel, **kwargs) - - class SD3Tokenizer: - def __init__(self, embedding_directory=None): + def __init__(self, embedding_directory=None, tokenizer_data={}): self.clip_l = sd1_clip.SDTokenizer(embedding_directory=embedding_directory) self.clip_g = sdxl_clip.SDXLClipGTokenizer(embedding_directory=embedding_directory) self.t5xxl = T5XXLTokenizer(embedding_directory=embedding_directory) diff --git a/comfy/text_encoders/spiece_tokenizer.py b/comfy/text_encoders/spiece_tokenizer.py index fa303da0b..deb026ffd 100644 --- a/comfy/text_encoders/spiece_tokenizer.py +++ b/comfy/text_encoders/spiece_tokenizer.py @@ -1,4 +1,5 @@ import os +import torch class SPieceTokenizer: add_eos = True @@ -9,6 +10,9 @@ class SPieceTokenizer: def __init__(self, tokenizer_path): import sentencepiece + if torch.is_tensor(tokenizer_path): + tokenizer_path = tokenizer_path.numpy().tobytes() + if isinstance(tokenizer_path, bytes): self.tokenizer = sentencepiece.SentencePieceProcessor(model_proto=tokenizer_path, add_eos=self.add_eos) else: From f87810cd3ed2cc3922811422181d0572f98b103d Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Thu, 25 Jul 2024 10:52:09 -0400 Subject: [PATCH 118/133] Let tokenizers return weights to be stored in the saved checkpoint. --- comfy/sd.py | 6 +++++- comfy/sd1_clip.py | 4 ++++ comfy/sdxl_clip.py | 3 +++ comfy/text_encoders/sd3_clip.py | 3 +++ 4 files changed, 15 insertions(+), 1 deletion(-) diff --git a/comfy/sd.py b/comfy/sd.py index fe6ce4c96..c6fcd810c 100644 --- a/comfy/sd.py +++ b/comfy/sd.py @@ -135,7 +135,11 @@ class CLIP: return self.cond_stage_model.load_sd(sd) def get_sd(self): - return self.cond_stage_model.state_dict() + sd_clip = self.cond_stage_model.state_dict() + sd_tokenizer = self.tokenizer.state_dict() + for k in sd_tokenizer: + sd_clip[k] = sd_tokenizer[k] + return sd_clip def load_model(self): model_management.load_model_gpu(self.patcher) diff --git a/comfy/sd1_clip.py b/comfy/sd1_clip.py index ea66da00b..c7bc1e4dc 100644 --- a/comfy/sd1_clip.py +++ b/comfy/sd1_clip.py @@ -519,6 +519,8 @@ class SDTokenizer: def untokenize(self, token_weight_pair): return list(map(lambda a: (a, self.inv_vocab[a[0]]), token_weight_pair)) + def state_dict(self): + return {} class SD1Tokenizer: def __init__(self, embedding_directory=None, tokenizer_data={}, clip_name="l", tokenizer=SDTokenizer): @@ -534,6 +536,8 @@ class SD1Tokenizer: def untokenize(self, token_weight_pair): return getattr(self, self.clip).untokenize(token_weight_pair) + def state_dict(self): + return {} class SD1ClipModel(torch.nn.Module): def __init__(self, device="cpu", dtype=None, clip_name="l", clip_model=SDClipModel, name=None, **kwargs): diff --git a/comfy/sdxl_clip.py b/comfy/sdxl_clip.py index 57c30f2e6..6e6b87d62 100644 --- a/comfy/sdxl_clip.py +++ b/comfy/sdxl_clip.py @@ -34,6 +34,9 @@ class SDXLTokenizer: def untokenize(self, token_weight_pair): return self.clip_g.untokenize(token_weight_pair) + def state_dict(self): + return {} + class SDXLClipModel(torch.nn.Module): def __init__(self, device="cpu", dtype=None): super().__init__() diff --git a/comfy/text_encoders/sd3_clip.py b/comfy/text_encoders/sd3_clip.py index 286c5dc05..b01fad221 100644 --- a/comfy/text_encoders/sd3_clip.py +++ b/comfy/text_encoders/sd3_clip.py @@ -34,6 +34,9 @@ class SD3Tokenizer: def untokenize(self, token_weight_pair): return self.clip_g.untokenize(token_weight_pair) + def state_dict(self): + return {} + class SD3ClipModel(torch.nn.Module): def __init__(self, clip_l=True, clip_g=True, t5=True, dtype_t5=None, device="cpu", dtype=None): super().__init__() From a5f4292f9f41ab78759e6e2de490fe6240f5d9ea Mon Sep 17 00:00:00 2001 From: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com> Date: Thu, 25 Jul 2024 18:21:08 -0400 Subject: [PATCH 119/133] Basic hunyuan dit implementation. (#4102) * Let tokenizers return weights to be stored in the saved checkpoint. * Basic hunyuan dit implementation. * Fix some resolutions not working. * Support hydit checkpoint save. * Init with right dtype. * Switch to optimized attention in pooler. * Fix black images on hunyuan dit. --- comfy/ldm/hydit/attn_layers.py | 219 + comfy/ldm/hydit/models.py | 402 + comfy/ldm/hydit/poolers.py | 36 + comfy/ldm/hydit/posemb_layers.py | 224 + comfy/model_base.py | 33 + comfy/model_detection.py | 13 + comfy/sd.py | 5 + comfy/supported_models.py | 42 +- comfy/text_encoders/hydit.py | 120 + comfy/text_encoders/hydit_clip.json | 35 + .../special_tokens_map.json | 7 + .../tokenizer_config.json | 16 + .../hydit_clip_tokenizer/vocab.txt | 47020 ++++++++++++++++ comfy/text_encoders/mt5_config_xl.json | 22 + comfy/text_encoders/spiece_tokenizer.py | 3 + 15 files changed, 48196 insertions(+), 1 deletion(-) create mode 100644 comfy/ldm/hydit/attn_layers.py create mode 100644 comfy/ldm/hydit/models.py create mode 100644 comfy/ldm/hydit/poolers.py create mode 100644 comfy/ldm/hydit/posemb_layers.py create mode 100644 comfy/text_encoders/hydit.py create mode 100644 comfy/text_encoders/hydit_clip.json create mode 100644 comfy/text_encoders/hydit_clip_tokenizer/special_tokens_map.json create mode 100644 comfy/text_encoders/hydit_clip_tokenizer/tokenizer_config.json create mode 100644 comfy/text_encoders/hydit_clip_tokenizer/vocab.txt create mode 100644 comfy/text_encoders/mt5_config_xl.json diff --git a/comfy/ldm/hydit/attn_layers.py b/comfy/ldm/hydit/attn_layers.py new file mode 100644 index 000000000..920b84286 --- /dev/null +++ b/comfy/ldm/hydit/attn_layers.py @@ -0,0 +1,219 @@ +import torch +import torch.nn as nn +from typing import Tuple, Union, Optional +from comfy.ldm.modules.attention import optimized_attention + + +def reshape_for_broadcast(freqs_cis: Union[torch.Tensor, Tuple[torch.Tensor]], x: torch.Tensor, head_first=False): + """ + Reshape frequency tensor for broadcasting it with another tensor. + + This function reshapes the frequency tensor to have the same shape as the target tensor 'x' + for the purpose of broadcasting the frequency tensor during element-wise operations. + + Args: + freqs_cis (Union[torch.Tensor, Tuple[torch.Tensor]]): Frequency tensor to be reshaped. + x (torch.Tensor): Target tensor for broadcasting compatibility. + head_first (bool): head dimension first (except batch dim) or not. + + Returns: + torch.Tensor: Reshaped frequency tensor. + + Raises: + AssertionError: If the frequency tensor doesn't match the expected shape. + AssertionError: If the target tensor 'x' doesn't have the expected number of dimensions. + """ + ndim = x.ndim + assert 0 <= 1 < ndim + + if isinstance(freqs_cis, tuple): + # freqs_cis: (cos, sin) in real space + if head_first: + assert freqs_cis[0].shape == (x.shape[-2], x.shape[-1]), f'freqs_cis shape {freqs_cis[0].shape} does not match x shape {x.shape}' + shape = [d if i == ndim - 2 or i == ndim - 1 else 1 for i, d in enumerate(x.shape)] + else: + assert freqs_cis[0].shape == (x.shape[1], x.shape[-1]), f'freqs_cis shape {freqs_cis[0].shape} does not match x shape {x.shape}' + shape = [d if i == 1 or i == ndim - 1 else 1 for i, d in enumerate(x.shape)] + return freqs_cis[0].view(*shape), freqs_cis[1].view(*shape) + else: + # freqs_cis: values in complex space + if head_first: + assert freqs_cis.shape == (x.shape[-2], x.shape[-1]), f'freqs_cis shape {freqs_cis.shape} does not match x shape {x.shape}' + shape = [d if i == ndim - 2 or i == ndim - 1 else 1 for i, d in enumerate(x.shape)] + else: + assert freqs_cis.shape == (x.shape[1], x.shape[-1]), f'freqs_cis shape {freqs_cis.shape} does not match x shape {x.shape}' + shape = [d if i == 1 or i == ndim - 1 else 1 for i, d in enumerate(x.shape)] + return freqs_cis.view(*shape) + + +def rotate_half(x): + x_real, x_imag = x.float().reshape(*x.shape[:-1], -1, 2).unbind(-1) # [B, S, H, D//2] + return torch.stack([-x_imag, x_real], dim=-1).flatten(3) + + +def apply_rotary_emb( + xq: torch.Tensor, + xk: Optional[torch.Tensor], + freqs_cis: Union[torch.Tensor, Tuple[torch.Tensor]], + head_first: bool = False, +) -> Tuple[torch.Tensor, torch.Tensor]: + """ + Apply rotary embeddings to input tensors using the given frequency tensor. + + This function applies rotary embeddings to the given query 'xq' and key 'xk' tensors using the provided + frequency tensor 'freqs_cis'. The input tensors are reshaped as complex numbers, and the frequency tensor + is reshaped for broadcasting compatibility. The resulting tensors contain rotary embeddings and are + returned as real tensors. + + Args: + xq (torch.Tensor): Query tensor to apply rotary embeddings. [B, S, H, D] + xk (torch.Tensor): Key tensor to apply rotary embeddings. [B, S, H, D] + freqs_cis (Union[torch.Tensor, Tuple[torch.Tensor]]): Precomputed frequency tensor for complex exponentials. + head_first (bool): head dimension first (except batch dim) or not. + + Returns: + Tuple[torch.Tensor, torch.Tensor]: Tuple of modified query tensor and key tensor with rotary embeddings. + + """ + xk_out = None + if isinstance(freqs_cis, tuple): + cos, sin = reshape_for_broadcast(freqs_cis, xq, head_first) # [S, D] + cos, sin = cos.to(xq.device), sin.to(xq.device) + xq_out = (xq.float() * cos + rotate_half(xq.float()) * sin).type_as(xq) + if xk is not None: + xk_out = (xk.float() * cos + rotate_half(xk.float()) * sin).type_as(xk) + else: + xq_ = torch.view_as_complex(xq.float().reshape(*xq.shape[:-1], -1, 2)) # [B, S, H, D//2] + freqs_cis = reshape_for_broadcast(freqs_cis, xq_, head_first).to(xq.device) # [S, D//2] --> [1, S, 1, D//2] + xq_out = torch.view_as_real(xq_ * freqs_cis).flatten(3).type_as(xq) + if xk is not None: + xk_ = torch.view_as_complex(xk.float().reshape(*xk.shape[:-1], -1, 2)) # [B, S, H, D//2] + xk_out = torch.view_as_real(xk_ * freqs_cis).flatten(3).type_as(xk) + + return xq_out, xk_out + + + +class CrossAttention(nn.Module): + """ + Use QK Normalization. + """ + def __init__(self, + qdim, + kdim, + num_heads, + qkv_bias=True, + qk_norm=False, + attn_drop=0.0, + proj_drop=0.0, + attn_precision=None, + device=None, + dtype=None, + operations=None, + ): + factory_kwargs = {'device': device, 'dtype': dtype} + super().__init__() + self.attn_precision = attn_precision + self.qdim = qdim + self.kdim = kdim + self.num_heads = num_heads + assert self.qdim % num_heads == 0, "self.qdim must be divisible by num_heads" + self.head_dim = self.qdim // num_heads + assert self.head_dim % 8 == 0 and self.head_dim <= 128, "Only support head_dim <= 128 and divisible by 8" + self.scale = self.head_dim ** -0.5 + + self.q_proj = operations.Linear(qdim, qdim, bias=qkv_bias, **factory_kwargs) + self.kv_proj = operations.Linear(kdim, 2 * qdim, bias=qkv_bias, **factory_kwargs) + + # TODO: eps should be 1 / 65530 if using fp16 + self.q_norm = operations.LayerNorm(self.head_dim, elementwise_affine=True, eps=1e-6, dtype=dtype, device=device) if qk_norm else nn.Identity() + self.k_norm = operations.LayerNorm(self.head_dim, elementwise_affine=True, eps=1e-6, dtype=dtype, device=device) if qk_norm else nn.Identity() + self.attn_drop = nn.Dropout(attn_drop) + self.out_proj = operations.Linear(qdim, qdim, bias=qkv_bias, **factory_kwargs) + self.proj_drop = nn.Dropout(proj_drop) + + def forward(self, x, y, freqs_cis_img=None): + """ + Parameters + ---------- + x: torch.Tensor + (batch, seqlen1, hidden_dim) (where hidden_dim = num heads * head dim) + y: torch.Tensor + (batch, seqlen2, hidden_dim2) + freqs_cis_img: torch.Tensor + (batch, hidden_dim // 2), RoPE for image + """ + b, s1, c = x.shape # [b, s1, D] + _, s2, c = y.shape # [b, s2, 1024] + + q = self.q_proj(x).view(b, s1, self.num_heads, self.head_dim) # [b, s1, h, d] + kv = self.kv_proj(y).view(b, s2, 2, self.num_heads, self.head_dim) # [b, s2, 2, h, d] + k, v = kv.unbind(dim=2) # [b, s, h, d] + q = self.q_norm(q) + k = self.k_norm(k) + + # Apply RoPE if needed + if freqs_cis_img is not None: + qq, _ = apply_rotary_emb(q, None, freqs_cis_img) + assert qq.shape == q.shape, f'qq: {qq.shape}, q: {q.shape}' + q = qq + + q = q.transpose(-2, -3).contiguous() # q -> B, L1, H, C - B, H, L1, C + k = k.transpose(-2, -3).contiguous() # k -> B, L2, H, C - B, H, C, L2 + v = v.transpose(-2, -3).contiguous() + + context = optimized_attention(q, k, v, self.num_heads, skip_reshape=True, attn_precision=self.attn_precision) + + out = self.out_proj(context) # context.reshape - B, L1, -1 + out = self.proj_drop(out) + + out_tuple = (out,) + + return out_tuple + + +class Attention(nn.Module): + """ + We rename some layer names to align with flash attention + """ + def __init__(self, dim, num_heads, qkv_bias=True, qk_norm=False, attn_drop=0., proj_drop=0., attn_precision=None, dtype=None, device=None, operations=None): + super().__init__() + self.attn_precision = attn_precision + self.dim = dim + self.num_heads = num_heads + assert self.dim % num_heads == 0, 'dim should be divisible by num_heads' + self.head_dim = self.dim // num_heads + # This assertion is aligned with flash attention + assert self.head_dim % 8 == 0 and self.head_dim <= 128, "Only support head_dim <= 128 and divisible by 8" + self.scale = self.head_dim ** -0.5 + + # qkv --> Wqkv + self.Wqkv = operations.Linear(dim, dim * 3, bias=qkv_bias, dtype=dtype, device=device) + # TODO: eps should be 1 / 65530 if using fp16 + self.q_norm = operations.LayerNorm(self.head_dim, elementwise_affine=True, eps=1e-6, dtype=dtype, device=device) if qk_norm else nn.Identity() + self.k_norm = operations.LayerNorm(self.head_dim, elementwise_affine=True, eps=1e-6, dtype=dtype, device=device) if qk_norm else nn.Identity() + self.attn_drop = nn.Dropout(attn_drop) + self.out_proj = operations.Linear(dim, dim, dtype=dtype, device=device) + self.proj_drop = nn.Dropout(proj_drop) + + def forward(self, x, freqs_cis_img=None): + B, N, C = x.shape + qkv = self.Wqkv(x).reshape(B, N, 3, self.num_heads, self.head_dim).permute(2, 0, 3, 1, 4) # [3, b, h, s, d] + q, k, v = qkv.unbind(0) # [b, h, s, d] + q = self.q_norm(q) # [b, h, s, d] + k = self.k_norm(k) # [b, h, s, d] + + # Apply RoPE if needed + if freqs_cis_img is not None: + qq, kk = apply_rotary_emb(q, k, freqs_cis_img, head_first=True) + assert qq.shape == q.shape and kk.shape == k.shape, \ + f'qq: {qq.shape}, q: {q.shape}, kk: {kk.shape}, k: {k.shape}' + q, k = qq, kk + + x = optimized_attention(q, k, v, self.num_heads, skip_reshape=True, attn_precision=self.attn_precision) + x = self.out_proj(x) + x = self.proj_drop(x) + + out_tuple = (x,) + + return out_tuple diff --git a/comfy/ldm/hydit/models.py b/comfy/ldm/hydit/models.py new file mode 100644 index 000000000..4bd7abab6 --- /dev/null +++ b/comfy/ldm/hydit/models.py @@ -0,0 +1,402 @@ +from typing import Any + +import torch +import torch.nn as nn +import torch.nn.functional as F + +from comfy.ldm.modules.diffusionmodules.mmdit import Mlp, TimestepEmbedder, PatchEmbed, RMSNorm +from comfy.ldm.modules.diffusionmodules.util import timestep_embedding +from torch.utils import checkpoint + +from .attn_layers import Attention, CrossAttention +from .poolers import AttentionPool +from .posemb_layers import get_2d_rotary_pos_embed, get_fill_resize_and_crop + +def calc_rope(x, patch_size, head_size): + th = (x.shape[2] + (patch_size // 2)) // patch_size + tw = (x.shape[3] + (patch_size // 2)) // patch_size + base_size = 512 // 8 // patch_size + start, stop = get_fill_resize_and_crop((th, tw), base_size) + sub_args = [start, stop, (th, tw)] + # head_size = HUNYUAN_DIT_CONFIG['DiT-g/2']['hidden_size'] // HUNYUAN_DIT_CONFIG['DiT-g/2']['num_heads'] + rope = get_2d_rotary_pos_embed(head_size, *sub_args) + return rope + + +def modulate(x, shift, scale): + return x * (1 + scale.unsqueeze(1)) + shift.unsqueeze(1) + + +class HunYuanDiTBlock(nn.Module): + """ + A HunYuanDiT block with `add` conditioning. + """ + def __init__(self, + hidden_size, + c_emb_size, + num_heads, + mlp_ratio=4.0, + text_states_dim=1024, + qk_norm=False, + norm_type="layer", + skip=False, + attn_precision=None, + dtype=None, + device=None, + operations=None, + ): + super().__init__() + use_ele_affine = True + + if norm_type == "layer": + norm_layer = operations.LayerNorm + elif norm_type == "rms": + norm_layer = RMSNorm + else: + raise ValueError(f"Unknown norm_type: {norm_type}") + + # ========================= Self-Attention ========================= + self.norm1 = norm_layer(hidden_size, elementwise_affine=use_ele_affine, eps=1e-6, dtype=dtype, device=device) + self.attn1 = Attention(hidden_size, num_heads=num_heads, qkv_bias=True, qk_norm=qk_norm, attn_precision=attn_precision, dtype=dtype, device=device, operations=operations) + + # ========================= FFN ========================= + self.norm2 = norm_layer(hidden_size, elementwise_affine=use_ele_affine, eps=1e-6, dtype=dtype, device=device) + mlp_hidden_dim = int(hidden_size * mlp_ratio) + approx_gelu = lambda: nn.GELU(approximate="tanh") + self.mlp = Mlp(in_features=hidden_size, hidden_features=mlp_hidden_dim, act_layer=approx_gelu, drop=0, dtype=dtype, device=device, operations=operations) + + # ========================= Add ========================= + # Simply use add like SDXL. + self.default_modulation = nn.Sequential( + nn.SiLU(), + operations.Linear(c_emb_size, hidden_size, bias=True, dtype=dtype, device=device) + ) + + # ========================= Cross-Attention ========================= + self.attn2 = CrossAttention(hidden_size, text_states_dim, num_heads=num_heads, qkv_bias=True, + qk_norm=qk_norm, attn_precision=attn_precision, dtype=dtype, device=device, operations=operations) + self.norm3 = norm_layer(hidden_size, elementwise_affine=True, eps=1e-6, dtype=dtype, device=device) + + # ========================= Skip Connection ========================= + if skip: + self.skip_norm = norm_layer(2 * hidden_size, elementwise_affine=True, eps=1e-6, dtype=dtype, device=device) + self.skip_linear = operations.Linear(2 * hidden_size, hidden_size, dtype=dtype, device=device) + else: + self.skip_linear = None + + self.gradient_checkpointing = False + + def _forward(self, x, c=None, text_states=None, freq_cis_img=None, skip=None): + # Long Skip Connection + if self.skip_linear is not None: + cat = torch.cat([x, skip], dim=-1) + cat = self.skip_norm(cat) + x = self.skip_linear(cat) + + # Self-Attention + shift_msa = self.default_modulation(c).unsqueeze(dim=1) + attn_inputs = ( + self.norm1(x) + shift_msa, freq_cis_img, + ) + x = x + self.attn1(*attn_inputs)[0] + + # Cross-Attention + cross_inputs = ( + self.norm3(x), text_states, freq_cis_img + ) + x = x + self.attn2(*cross_inputs)[0] + + # FFN Layer + mlp_inputs = self.norm2(x) + x = x + self.mlp(mlp_inputs) + + return x + + def forward(self, x, c=None, text_states=None, freq_cis_img=None, skip=None): + if self.gradient_checkpointing and self.training: + return checkpoint.checkpoint(self._forward, x, c, text_states, freq_cis_img, skip) + return self._forward(x, c, text_states, freq_cis_img, skip) + + +class FinalLayer(nn.Module): + """ + The final layer of HunYuanDiT. + """ + def __init__(self, final_hidden_size, c_emb_size, patch_size, out_channels, dtype=None, device=None, operations=None): + super().__init__() + self.norm_final = operations.LayerNorm(final_hidden_size, elementwise_affine=False, eps=1e-6, dtype=dtype, device=device) + self.linear = operations.Linear(final_hidden_size, patch_size * patch_size * out_channels, bias=True, dtype=dtype, device=device) + self.adaLN_modulation = nn.Sequential( + nn.SiLU(), + operations.Linear(c_emb_size, 2 * final_hidden_size, bias=True, dtype=dtype, device=device) + ) + + def forward(self, x, c): + shift, scale = self.adaLN_modulation(c).chunk(2, dim=1) + x = modulate(self.norm_final(x), shift, scale) + x = self.linear(x) + return x + + +class HunYuanDiT(nn.Module): + """ + HunYuanDiT: Diffusion model with a Transformer backbone. + + Inherit ModelMixin and ConfigMixin to be compatible with the sampler StableDiffusionPipeline of diffusers. + + Inherit PeftAdapterMixin to be compatible with the PEFT training pipeline. + + Parameters + ---------- + args: argparse.Namespace + The arguments parsed by argparse. + input_size: tuple + The size of the input image. + patch_size: int + The size of the patch. + in_channels: int + The number of input channels. + hidden_size: int + The hidden size of the transformer backbone. + depth: int + The number of transformer blocks. + num_heads: int + The number of attention heads. + mlp_ratio: float + The ratio of the hidden size of the MLP in the transformer block. + log_fn: callable + The logging function. + """ + #@register_to_config + def __init__(self, + input_size: tuple = 32, + patch_size: int = 2, + in_channels: int = 4, + hidden_size: int = 1152, + depth: int = 28, + num_heads: int = 16, + mlp_ratio: float = 4.0, + text_states_dim = 1024, + text_states_dim_t5 = 2048, + text_len = 77, + text_len_t5 = 256, + qk_norm = True,# See http://arxiv.org/abs/2302.05442 for details. + size_cond = False, + use_style_cond = False, + learn_sigma = True, + norm = "layer", + log_fn: callable = print, + attn_precision=None, + dtype=None, + device=None, + operations=None, + **kwargs, + ): + super().__init__() + self.log_fn = log_fn + self.depth = depth + self.learn_sigma = learn_sigma + self.in_channels = in_channels + self.out_channels = in_channels * 2 if learn_sigma else in_channels + self.patch_size = patch_size + self.num_heads = num_heads + self.hidden_size = hidden_size + self.text_states_dim = text_states_dim + self.text_states_dim_t5 = text_states_dim_t5 + self.text_len = text_len + self.text_len_t5 = text_len_t5 + self.size_cond = size_cond + self.use_style_cond = use_style_cond + self.norm = norm + self.dtype = dtype + #import pdb + #pdb.set_trace() + + self.mlp_t5 = nn.Sequential( + operations.Linear(self.text_states_dim_t5, self.text_states_dim_t5 * 4, bias=True, dtype=dtype, device=device), + nn.SiLU(), + operations.Linear(self.text_states_dim_t5 * 4, self.text_states_dim, bias=True, dtype=dtype, device=device), + ) + # learnable replace + self.text_embedding_padding = nn.Parameter( + torch.empty(self.text_len + self.text_len_t5, self.text_states_dim, dtype=dtype, device=device)) + + # Attention pooling + pooler_out_dim = 1024 + self.pooler = AttentionPool(self.text_len_t5, self.text_states_dim_t5, num_heads=8, output_dim=pooler_out_dim, dtype=dtype, device=device, operations=operations) + + # Dimension of the extra input vectors + self.extra_in_dim = pooler_out_dim + + if self.size_cond: + # Image size and crop size conditions + self.extra_in_dim += 6 * 256 + + if self.use_style_cond: + # Here we use a default learned embedder layer for future extension. + self.style_embedder = nn.Embedding(1, hidden_size, dtype=dtype, device=device) + self.extra_in_dim += hidden_size + + # Text embedding for `add` + self.x_embedder = PatchEmbed(input_size, patch_size, in_channels, hidden_size, dtype=dtype, device=device, operations=operations) + self.t_embedder = TimestepEmbedder(hidden_size, dtype=dtype, device=device, operations=operations) + self.extra_embedder = nn.Sequential( + operations.Linear(self.extra_in_dim, hidden_size * 4, dtype=dtype, device=device), + nn.SiLU(), + operations.Linear(hidden_size * 4, hidden_size, bias=True, dtype=dtype, device=device), + ) + + # Image embedding + num_patches = self.x_embedder.num_patches + + # HUnYuanDiT Blocks + self.blocks = nn.ModuleList([ + HunYuanDiTBlock(hidden_size=hidden_size, + c_emb_size=hidden_size, + num_heads=num_heads, + mlp_ratio=mlp_ratio, + text_states_dim=self.text_states_dim, + qk_norm=qk_norm, + norm_type=self.norm, + skip=layer > depth // 2, + attn_precision=attn_precision, + dtype=dtype, + device=device, + operations=operations, + ) + for layer in range(depth) + ]) + + self.final_layer = FinalLayer(hidden_size, hidden_size, patch_size, self.out_channels, dtype=dtype, device=device, operations=operations) + self.unpatchify_channels = self.out_channels + + + + def forward(self, + x, + t, + context,#encoder_hidden_states=None, + text_embedding_mask=None, + encoder_hidden_states_t5=None, + text_embedding_mask_t5=None, + image_meta_size=None, + style=None, + return_dict=False, + control=None, + transformer_options=None, + ): + """ + Forward pass of the encoder. + + Parameters + ---------- + x: torch.Tensor + (B, D, H, W) + t: torch.Tensor + (B) + encoder_hidden_states: torch.Tensor + CLIP text embedding, (B, L_clip, D) + text_embedding_mask: torch.Tensor + CLIP text embedding mask, (B, L_clip) + encoder_hidden_states_t5: torch.Tensor + T5 text embedding, (B, L_t5, D) + text_embedding_mask_t5: torch.Tensor + T5 text embedding mask, (B, L_t5) + image_meta_size: torch.Tensor + (B, 6) + style: torch.Tensor + (B) + cos_cis_img: torch.Tensor + sin_cis_img: torch.Tensor + return_dict: bool + Whether to return a dictionary. + """ + #import pdb + #pdb.set_trace() + encoder_hidden_states = context + text_states = encoder_hidden_states # 2,77,1024 + text_states_t5 = encoder_hidden_states_t5 # 2,256,2048 + text_states_mask = text_embedding_mask.bool() # 2,77 + text_states_t5_mask = text_embedding_mask_t5.bool() # 2,256 + b_t5, l_t5, c_t5 = text_states_t5.shape + text_states_t5 = self.mlp_t5(text_states_t5.view(-1, c_t5)) + text_states = torch.cat([text_states, text_states_t5.view(b_t5, l_t5, -1)], dim=1) # 2,205，1024 + + clip_t5_mask = torch.cat([text_states_mask, text_states_t5_mask], dim=-1) + + clip_t5_mask = clip_t5_mask + text_states = torch.where(clip_t5_mask.unsqueeze(2), text_states, self.text_embedding_padding.to(text_states)) + + _, _, oh, ow = x.shape + th, tw = (oh + (self.patch_size // 2)) // self.patch_size, (ow + (self.patch_size // 2)) // self.patch_size + + + # Get image RoPE embedding according to `reso`lution. + freqs_cis_img = calc_rope(x, self.patch_size, self.hidden_size // self.num_heads) #(cos_cis_img, sin_cis_img) + + # ========================= Build time and image embedding ========================= + t = self.t_embedder(t, dtype=x.dtype) + x = self.x_embedder(x) + + # ========================= Concatenate all extra vectors ========================= + # Build text tokens with pooling + extra_vec = self.pooler(encoder_hidden_states_t5) + + # Build image meta size tokens if applicable + if self.size_cond: + image_meta_size = timestep_embedding(image_meta_size.view(-1), 256).to(x.dtype) # [B * 6, 256] + image_meta_size = image_meta_size.view(-1, 6 * 256) + extra_vec = torch.cat([extra_vec, image_meta_size], dim=1) # [B, D + 6 * 256] + + # Build style tokens + if self.use_style_cond: + if style is None: + style = torch.zeros((extra_vec.shape[0],), device=x.device, dtype=torch.int) + style_embedding = self.style_embedder(style) + extra_vec = torch.cat([extra_vec, style_embedding], dim=1) + + # Concatenate all extra vectors + c = t + self.extra_embedder(extra_vec) # [B, D] + + controls = None + # ========================= Forward pass through HunYuanDiT blocks ========================= + skips = [] + for layer, block in enumerate(self.blocks): + if layer > self.depth // 2: + if controls is not None: + skip = skips.pop() + controls.pop() + else: + skip = skips.pop() + x = block(x, c, text_states, freqs_cis_img, skip) # (N, L, D) + else: + x = block(x, c, text_states, freqs_cis_img) # (N, L, D) + + if layer < (self.depth // 2 - 1): + skips.append(x) + if controls is not None and len(controls) != 0: + raise ValueError("The number of controls is not equal to the number of skip connections.") + + # ========================= Final layer ========================= + x = self.final_layer(x, c) # (N, L, patch_size ** 2 * out_channels) + x = self.unpatchify(x, th, tw) # (N, out_channels, H, W) + + if return_dict: + return {'x': x} + if self.learn_sigma: + return x[:,:self.out_channels // 2,:oh,:ow] + return x[:,:,:oh,:ow] + + def unpatchify(self, x, h, w): + """ + x: (N, T, patch_size**2 * C) + imgs: (N, H, W, C) + """ + c = self.unpatchify_channels + p = self.x_embedder.patch_size[0] + # h = w = int(x.shape[1] ** 0.5) + assert h * w == x.shape[1] + + x = x.reshape(shape=(x.shape[0], h, w, p, p, c)) + x = torch.einsum('nhwpqc->nchpwq', x) + imgs = x.reshape(shape=(x.shape[0], c, h * p, w * p)) + return imgs diff --git a/comfy/ldm/hydit/poolers.py b/comfy/ldm/hydit/poolers.py new file mode 100644 index 000000000..3470041b5 --- /dev/null +++ b/comfy/ldm/hydit/poolers.py @@ -0,0 +1,36 @@ +import torch +import torch.nn as nn +import torch.nn.functional as F +from comfy.ldm.modules.attention import optimized_attention #TODO + + +class AttentionPool(nn.Module): + def __init__(self, spacial_dim: int, embed_dim: int, num_heads: int, output_dim: int = None, dtype=None, device=None, operations=None): + super().__init__() + self.positional_embedding = nn.Parameter(torch.empty(spacial_dim + 1, embed_dim, dtype=dtype, device=device)) + self.k_proj = operations.Linear(embed_dim, embed_dim, dtype=dtype, device=device) + self.q_proj = operations.Linear(embed_dim, embed_dim, dtype=dtype, device=device) + self.v_proj = operations.Linear(embed_dim, embed_dim, dtype=dtype, device=device) + self.c_proj = operations.Linear(embed_dim, output_dim or embed_dim, dtype=dtype, device=device) + self.num_heads = num_heads + self.embed_dim = embed_dim + + def forward(self, x): + x = x.permute(1, 0, 2) # NLC -> LNC + x = torch.cat([x.mean(dim=0, keepdim=True), x], dim=0) # (L+1)NC + x = x + self.positional_embedding[:, None, :].to(dtype=x.dtype, device=x.device) # (L+1)NC + + q = self.q_proj(x[:1]) + k = self.k_proj(x) + v = self.v_proj(x) + + batch_size = q.shape[1] + head_dim = self.embed_dim // self.num_heads + q = q.view(1, batch_size * self.num_heads, head_dim).transpose(0, 1).view(batch_size, self.num_heads, -1, head_dim) + k = k.view(k.shape[0], batch_size * self.num_heads, head_dim).transpose(0, 1).view(batch_size, self.num_heads, -1, head_dim) + v = v.view(v.shape[0], batch_size * self.num_heads, head_dim).transpose(0, 1).view(batch_size, self.num_heads, -1, head_dim) + + attn_output = optimized_attention(q, k, v, self.num_heads, skip_reshape=True).transpose(0, 1) + + attn_output = self.c_proj(attn_output) + return attn_output.squeeze(0) diff --git a/comfy/ldm/hydit/posemb_layers.py b/comfy/ldm/hydit/posemb_layers.py new file mode 100644 index 000000000..dcb41a713 --- /dev/null +++ b/comfy/ldm/hydit/posemb_layers.py @@ -0,0 +1,224 @@ +import torch +import numpy as np +from typing import Union + + +def _to_tuple(x): + if isinstance(x, int): + return x, x + else: + return x + + +def get_fill_resize_and_crop(src, tgt): + th, tw = _to_tuple(tgt) + h, w = _to_tuple(src) + + tr = th / tw # base resolution + r = h / w # target resolution + + # resize + if r > tr: + resize_height = th + resize_width = int(round(th / h * w)) + else: + resize_width = tw + resize_height = int(round(tw / w * h)) # resize the target resolution down based on the base resolution + + crop_top = int(round((th - resize_height) / 2.0)) + crop_left = int(round((tw - resize_width) / 2.0)) + + return (crop_top, crop_left), (crop_top + resize_height, crop_left + resize_width) + + +def get_meshgrid(start, *args): + if len(args) == 0: + # start is grid_size + num = _to_tuple(start) + start = (0, 0) + stop = num + elif len(args) == 1: + # start is start, args[0] is stop, step is 1 + start = _to_tuple(start) + stop = _to_tuple(args[0]) + num = (stop[0] - start[0], stop[1] - start[1]) + elif len(args) == 2: + # start is start, args[0] is stop, args[1] is num + start = _to_tuple(start) + stop = _to_tuple(args[0]) + num = _to_tuple(args[1]) + else: + raise ValueError(f"len(args) should be 0, 1 or 2, but got {len(args)}") + + grid_h = np.linspace(start[0], stop[0], num[0], endpoint=False, dtype=np.float32) + grid_w = np.linspace(start[1], stop[1], num[1], endpoint=False, dtype=np.float32) + grid = np.meshgrid(grid_w, grid_h) # here w goes first + grid = np.stack(grid, axis=0) # [2, W, H] + return grid + +################################################################################# +# Sine/Cosine Positional Embedding Functions # +################################################################################# +# https://github.com/facebookresearch/mae/blob/main/util/pos_embed.py + +def get_2d_sincos_pos_embed(embed_dim, start, *args, cls_token=False, extra_tokens=0): + """ + grid_size: int of the grid height and width + return: + pos_embed: [grid_size*grid_size, embed_dim] or [1+grid_size*grid_size, embed_dim] (w/ or w/o cls_token) + """ + grid = get_meshgrid(start, *args) # [2, H, w] + # grid_h = np.arange(grid_size, dtype=np.float32) + # grid_w = np.arange(grid_size, dtype=np.float32) + # grid = np.meshgrid(grid_w, grid_h) # here w goes first + # grid = np.stack(grid, axis=0) # [2, W, H] + + grid = grid.reshape([2, 1, *grid.shape[1:]]) + pos_embed = get_2d_sincos_pos_embed_from_grid(embed_dim, grid) + if cls_token and extra_tokens > 0: + pos_embed = np.concatenate([np.zeros([extra_tokens, embed_dim]), pos_embed], axis=0) + return pos_embed + + +def get_2d_sincos_pos_embed_from_grid(embed_dim, grid): + assert embed_dim % 2 == 0 + + # use half of dimensions to encode grid_h + emb_h = get_1d_sincos_pos_embed_from_grid(embed_dim // 2, grid[0]) # (H*W, D/2) + emb_w = get_1d_sincos_pos_embed_from_grid(embed_dim // 2, grid[1]) # (H*W, D/2) + + emb = np.concatenate([emb_h, emb_w], axis=1) # (H*W, D) + return emb + + +def get_1d_sincos_pos_embed_from_grid(embed_dim, pos): + """ + embed_dim: output dimension for each position + pos: a list of positions to be encoded: size (W,H) + out: (M, D) + """ + assert embed_dim % 2 == 0 + omega = np.arange(embed_dim // 2, dtype=np.float64) + omega /= embed_dim / 2. + omega = 1. / 10000**omega # (D/2,) + + pos = pos.reshape(-1) # (M,) + out = np.einsum('m,d->md', pos, omega) # (M, D/2), outer product + + emb_sin = np.sin(out) # (M, D/2) + emb_cos = np.cos(out) # (M, D/2) + + emb = np.concatenate([emb_sin, emb_cos], axis=1) # (M, D) + return emb + + +################################################################################# +# Rotary Positional Embedding Functions # +################################################################################# +# https://github.com/facebookresearch/llama/blob/main/llama/model.py#L443 + +def get_2d_rotary_pos_embed(embed_dim, start, *args, use_real=True): + """ + This is a 2d version of precompute_freqs_cis, which is a RoPE for image tokens with 2d structure. + + Parameters + ---------- + embed_dim: int + embedding dimension size + start: int or tuple of int + If len(args) == 0, start is num; If len(args) == 1, start is start, args[0] is stop, step is 1; + If len(args) == 2, start is start, args[0] is stop, args[1] is num. + use_real: bool + If True, return real part and imaginary part separately. Otherwise, return complex numbers. + + Returns + ------- + pos_embed: torch.Tensor + [HW, D/2] + """ + grid = get_meshgrid(start, *args) # [2, H, w] + grid = grid.reshape([2, 1, *grid.shape[1:]]) # Returns a sampling matrix with the same resolution as the target resolution + pos_embed = get_2d_rotary_pos_embed_from_grid(embed_dim, grid, use_real=use_real) + return pos_embed + + +def get_2d_rotary_pos_embed_from_grid(embed_dim, grid, use_real=False): + assert embed_dim % 4 == 0 + + # use half of dimensions to encode grid_h + emb_h = get_1d_rotary_pos_embed(embed_dim // 2, grid[0].reshape(-1), use_real=use_real) # (H*W, D/4) + emb_w = get_1d_rotary_pos_embed(embed_dim // 2, grid[1].reshape(-1), use_real=use_real) # (H*W, D/4) + + if use_real: + cos = torch.cat([emb_h[0], emb_w[0]], dim=1) # (H*W, D/2) + sin = torch.cat([emb_h[1], emb_w[1]], dim=1) # (H*W, D/2) + return cos, sin + else: + emb = torch.cat([emb_h, emb_w], dim=1) # (H*W, D/2) + return emb + + +def get_1d_rotary_pos_embed(dim: int, pos: Union[np.ndarray, int], theta: float = 10000.0, use_real=False): + """ + Precompute the frequency tensor for complex exponentials (cis) with given dimensions. + + This function calculates a frequency tensor with complex exponentials using the given dimension 'dim' + and the end index 'end'. The 'theta' parameter scales the frequencies. + The returned tensor contains complex values in complex64 data type. + + Args: + dim (int): Dimension of the frequency tensor. + pos (np.ndarray, int): Position indices for the frequency tensor. [S] or scalar + theta (float, optional): Scaling factor for frequency computation. Defaults to 10000.0. + use_real (bool, optional): If True, return real part and imaginary part separately. + Otherwise, return complex numbers. + + Returns: + torch.Tensor: Precomputed frequency tensor with complex exponentials. [S, D/2] + + """ + if isinstance(pos, int): + pos = np.arange(pos) + freqs = 1.0 / (theta ** (torch.arange(0, dim, 2)[: (dim // 2)].float() / dim)) # [D/2] + t = torch.from_numpy(pos).to(freqs.device) # type: ignore # [S] + freqs = torch.outer(t, freqs).float() # type: ignore # [S, D/2] + if use_real: + freqs_cos = freqs.cos().repeat_interleave(2, dim=1) # [S, D] + freqs_sin = freqs.sin().repeat_interleave(2, dim=1) # [S, D] + return freqs_cos, freqs_sin + else: + freqs_cis = torch.polar(torch.ones_like(freqs), freqs) # complex64 # [S, D/2] + return freqs_cis + + + +def calc_sizes(rope_img, patch_size, th, tw): + if rope_img == 'extend': + # Expansion mode + sub_args = [(th, tw)] + elif rope_img.startswith('base'): + # Based on the specified dimensions, other dimensions are obtained through interpolation. + base_size = int(rope_img[4:]) // 8 // patch_size + start, stop = get_fill_resize_and_crop((th, tw), base_size) + sub_args = [start, stop, (th, tw)] + else: + raise ValueError(f"Unknown rope_img: {rope_img}") + return sub_args + + +def init_image_posemb(rope_img, + resolutions, + patch_size, + hidden_size, + num_heads, + log_fn, + rope_real=True, + ): + freqs_cis_img = {} + for reso in resolutions: + th, tw = reso.height // 8 // patch_size, reso.width // 8 // patch_size + sub_args = calc_sizes(rope_img, patch_size, th, tw) + freqs_cis_img[str(reso)] = get_2d_rotary_pos_embed(hidden_size // num_heads, *sub_args, use_real=rope_real) + log_fn(f" Using image RoPE ({rope_img}) ({'real' if rope_real else 'complex'}): {sub_args} | ({reso}) " + f"{freqs_cis_img[str(reso)][0].shape if rope_real else freqs_cis_img[str(reso)].shape}") + return freqs_cis_img diff --git a/comfy/model_base.py b/comfy/model_base.py index 0e0e69d3b..9d60c1fb4 100644 --- a/comfy/model_base.py +++ b/comfy/model_base.py @@ -7,6 +7,7 @@ from comfy.ldm.modules.encoders.noise_aug_modules import CLIPEmbeddingNoiseAugme from comfy.ldm.modules.diffusionmodules.upscaling import ImageConcatWithNoiseAugmentation from comfy.ldm.modules.diffusionmodules.mmdit import OpenAISignatureMMDITWrapper import comfy.ldm.aura.mmdit +import comfy.ldm.hydit.models import comfy.ldm.audio.dit import comfy.ldm.audio.embedders import comfy.model_management @@ -648,3 +649,35 @@ class StableAudio1(BaseModel): for l in s: sd["{}{}".format(k, l)] = s[l] return sd + +class HunyuanDiT(BaseModel): + def __init__(self, model_config, model_type=ModelType.V_PREDICTION, device=None): + super().__init__(model_config, model_type, device=device, unet_model=comfy.ldm.hydit.models.HunYuanDiT) + + def extra_conds(self, **kwargs): + out = super().extra_conds(**kwargs) + cross_attn = kwargs.get("cross_attn", None) + if cross_attn is not None: + out['c_crossattn'] = comfy.conds.CONDRegular(cross_attn) + + attention_mask = kwargs.get("attention_mask", None) + if attention_mask is not None: + out['text_embedding_mask'] = comfy.conds.CONDRegular(attention_mask) + + conditioning_mt5xl = kwargs.get("conditioning_mt5xl", None) + if conditioning_mt5xl is not None: + out['encoder_hidden_states_t5'] = comfy.conds.CONDRegular(conditioning_mt5xl) + + attention_mask_mt5xl = kwargs.get("attention_mask_mt5xl", None) + if attention_mask_mt5xl is not None: + out['text_embedding_mask_t5'] = comfy.conds.CONDRegular(attention_mask_mt5xl) + + width = kwargs.get("width", 768) + height = kwargs.get("height", 768) + crop_w = kwargs.get("crop_w", 0) + crop_h = kwargs.get("crop_h", 0) + target_width = kwargs.get("target_width", width) + target_height = kwargs.get("target_height", height) + + out['image_meta_size'] = comfy.conds.CONDRegular(torch.FloatTensor([[height, width, target_height, target_width, 0, 0]])) + return out diff --git a/comfy/model_detection.py b/comfy/model_detection.py index ae88eeb97..ea4959370 100644 --- a/comfy/model_detection.py +++ b/comfy/model_detection.py @@ -115,6 +115,19 @@ def detect_unet_config(state_dict, key_prefix): unet_config["n_layers"] = double_layers + single_layers return unet_config + if '{}mlp_t5.0.weight'.format(key_prefix) in state_dict_keys: #Hunyuan DiT + unet_config = {} + unet_config["image_model"] = "hydit" + unet_config["depth"] = count_blocks(state_dict_keys, '{}blocks.'.format(key_prefix) + '{}.') + unet_config["hidden_size"] = state_dict['{}x_embedder.proj.weight'.format(key_prefix)].shape[0] + if unet_config["hidden_size"] == 1408 and unet_config["depth"] == 40: #DiT-g/2 + unet_config["mlp_ratio"] = 4.3637 + if state_dict['{}extra_embedder.0.weight'.format(key_prefix)].shape[1] == 3968: + unet_config["size_cond"] = True + unet_config["use_style_cond"] = True + unet_config["image_model"] = "hydit1" + return unet_config + if '{}input_blocks.0.0.weight'.format(key_prefix) not in state_dict_keys: return None diff --git a/comfy/sd.py b/comfy/sd.py index c6fcd810c..b1d38c4b2 100644 --- a/comfy/sd.py +++ b/comfy/sd.py @@ -22,6 +22,7 @@ from . import sdxl_clip import comfy.text_encoders.sd3_clip import comfy.text_encoders.sa_t5 import comfy.text_encoders.aura_t5 +import comfy.text_encoders.hydit import comfy.model_patcher import comfy.lora @@ -385,6 +386,7 @@ class CLIPType(Enum): STABLE_CASCADE = 2 SD3 = 3 STABLE_AUDIO = 4 + HUNYUAN_DIT = 5 def load_clip(ckpt_paths, embedding_directory=None, clip_type=CLIPType.STABLE_DIFFUSION): clip_data = [] @@ -433,6 +435,9 @@ def load_clip(ckpt_paths, embedding_directory=None, clip_type=CLIPType.STABLE_DI if clip_type == CLIPType.SD3: clip_target.clip = comfy.text_encoders.sd3_clip.sd3_clip(clip_l=True, clip_g=True, t5=False) clip_target.tokenizer = comfy.text_encoders.sd3_clip.SD3Tokenizer + elif clip_type == CLIPType.HUNYUAN_DIT: + clip_target.clip = comfy.text_encoders.hydit.HyditModel + clip_target.tokenizer = comfy.text_encoders.hydit.HyditTokenizer else: clip_target.clip = sdxl_clip.SDXLClipModel clip_target.tokenizer = sdxl_clip.SDXLTokenizer diff --git a/comfy/supported_models.py b/comfy/supported_models.py index b4d1059ef..40417eb4d 100644 --- a/comfy/supported_models.py +++ b/comfy/supported_models.py @@ -8,6 +8,7 @@ from . import sdxl_clip import comfy.text_encoders.sd3_clip import comfy.text_encoders.sa_t5 import comfy.text_encoders.aura_t5 +import comfy.text_encoders.hydit from . import supported_models_base from . import latent_formats @@ -580,6 +581,45 @@ class AuraFlow(supported_models_base.BASE): def clip_target(self, state_dict={}): return supported_models_base.ClipTarget(comfy.text_encoders.aura_t5.AuraT5Tokenizer, comfy.text_encoders.aura_t5.AuraT5Model) -models = [Stable_Zero123, SD15_instructpix2pix, SD15, SD20, SD21UnclipL, SD21UnclipH, SDXL_instructpix2pix, SDXLRefiner, SDXL, SSD1B, KOALA_700M, KOALA_1B, Segmind_Vega, SD_X4Upscaler, Stable_Cascade_C, Stable_Cascade_B, SV3D_u, SV3D_p, SD3, StableAudio, AuraFlow] +class HunyuanDiT(supported_models_base.BASE): + unet_config = { + "image_model": "hydit", + } + + unet_extra_config = { + "attn_precision": torch.float32, + } + + sampling_settings = { + "linear_start": 0.00085, + "linear_end": 0.018, + } + + latent_format = latent_formats.SDXL + + vae_key_prefix = ["vae."] + text_encoder_key_prefix = ["text_encoders."] + + def get_model(self, state_dict, prefix="", device=None): + out = model_base.HunyuanDiT(self, device=device) + return out + + def clip_target(self, state_dict={}): + return supported_models_base.ClipTarget(comfy.text_encoders.hydit.HyditTokenizer, comfy.text_encoders.hydit.HyditModel) + +class HunyuanDiT1(HunyuanDiT): + unet_config = { + "image_model": "hydit1", + } + + unet_extra_config = {} + + sampling_settings = { + "linear_start" : 0.00085, + "linear_end" : 0.03, + } + + +models = [Stable_Zero123, SD15_instructpix2pix, SD15, SD20, SD21UnclipL, SD21UnclipH, SDXL_instructpix2pix, SDXLRefiner, SDXL, SSD1B, KOALA_700M, KOALA_1B, Segmind_Vega, SD_X4Upscaler, Stable_Cascade_C, Stable_Cascade_B, SV3D_u, SV3D_p, SD3, StableAudio, AuraFlow, HunyuanDiT, HunyuanDiT1] models += [SVD_img2vid] diff --git a/comfy/text_encoders/hydit.py b/comfy/text_encoders/hydit.py new file mode 100644 index 000000000..e47c8cb20 --- /dev/null +++ b/comfy/text_encoders/hydit.py @@ -0,0 +1,120 @@ +from comfy import sd1_clip +from transformers import T5TokenizerFast, BertTokenizer, BertModel, modeling_utils, BertConfig +from .spiece_tokenizer import SPieceTokenizer +import comfy.text_encoders.t5 +import os + +import torch +import contextlib + +@contextlib.contextmanager +def use_comfy_ops(ops, device=None, dtype=None): + old_torch_nn_linear = torch.nn.Linear + force_device = device + force_dtype = dtype + def linear_with_dtype(in_features: int, out_features: int, bias: bool = True, device=None, dtype=None): + if force_device is not None: + device = force_device + if force_dtype is not None: + dtype = force_dtype + return ops.Linear(in_features, out_features, bias=bias, device=device, dtype=dtype) + + torch.nn.Linear = linear_with_dtype + try: + yield + finally: + torch.nn.Linear = old_torch_nn_linear + + +class RobertaWrapper(torch.nn.Module): + def __init__(self, config_dict, dtype, device, operations): + super().__init__() + config = BertConfig(**config_dict) + with use_comfy_ops(operations, device, dtype): + with modeling_utils.no_init_weights(): + self.bert = BertModel(config, add_pooling_layer=False) + + self.num_layers = config.num_hidden_layers + + def get_input_embeddings(self): + return self.bert.get_input_embeddings() + + def set_input_embeddings(self, value): + return self.bert.set_input_embeddings(value) + + def forward(self, input_tokens, attention_mask=None, intermediate_output=None, final_layer_norm_intermediate=True): + intermediate = None + out = self.bert(input_ids=input_tokens, output_hidden_states=intermediate_output is not None, attention_mask=attention_mask) + return out.last_hidden_state, intermediate, out.pooler_output + +class HyditBertModel(sd1_clip.SDClipModel): + def __init__(self, device="cpu", layer="last", layer_idx=None, dtype=None): + textmodel_json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "hydit_clip.json") + super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, dtype=dtype, special_tokens={"start": 101, "end": 102, "pad": 0}, model_class=RobertaWrapper, enable_attention_masks=True, return_attention_masks=True) + +class HyditBertTokenizer(sd1_clip.SDTokenizer): + def __init__(self, embedding_directory=None, tokenizer_data={}): + tokenizer_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "hydit_clip_tokenizer") + super().__init__(tokenizer_path, pad_with_end=False, embedding_size=1024, embedding_key='chinese_roberta', tokenizer_class=BertTokenizer) + + +class MT5XLModel(sd1_clip.SDClipModel): + def __init__(self, device="cpu", layer="last", layer_idx=None, dtype=None): + textmodel_json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "mt5_config_xl.json") + super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, dtype=dtype, special_tokens={"end": 1, "pad": 0}, model_class=comfy.text_encoders.t5.T5, enable_attention_masks=True, return_attention_masks=True) + +class MT5XLTokenizer(sd1_clip.SDTokenizer): + def __init__(self, embedding_directory=None, tokenizer_data={}): + #tokenizer_path = os.path.join(os.path.join(os.path.dirname(os.path.realpath(__file__)), "mt5_tokenizer"), "spiece.model") + tokenizer = tokenizer_data.get("spiece_model", None) + super().__init__(tokenizer, pad_with_end=False, embedding_size=2048, embedding_key='mt5xl', tokenizer_class=SPieceTokenizer, has_start_token=False, pad_to_max_length=False, max_length=99999999, min_length=256) + + def state_dict(self): + return {"spiece_model": self.tokenizer.serialize_model()} + +class HyditTokenizer: + def __init__(self, embedding_directory=None, tokenizer_data={}): + mt5_tokenizer_data = tokenizer_data.get("mt5xl.spiece_model", None) + self.hydit_clip = HyditBertTokenizer(embedding_directory=embedding_directory) + self.mt5xl = MT5XLTokenizer(tokenizer_data={"spiece_model": mt5_tokenizer_data}, embedding_directory=embedding_directory) + + def tokenize_with_weights(self, text:str, return_word_ids=False): + out = {} + out["hydit_clip"] = self.hydit_clip.tokenize_with_weights(text, return_word_ids) + out["mt5xl"] = self.mt5xl.tokenize_with_weights(text, return_word_ids) + return out + + def untokenize(self, token_weight_pair): + return self.hydit_clip.untokenize(token_weight_pair) + + def state_dict(self): + return {"mt5xl.spiece_model": self.mt5xl.state_dict()["spiece_model"]} + +class HyditModel(torch.nn.Module): + def __init__(self, device="cpu", dtype=None): + super().__init__() + self.hydit_clip = HyditBertModel() + self.mt5xl = MT5XLModel() + + self.dtypes = set() + if dtype is not None: + self.dtypes.add(dtype) + + def encode_token_weights(self, token_weight_pairs): + hydit_out = self.hydit_clip.encode_token_weights(token_weight_pairs["hydit_clip"]) + mt5_out = self.mt5xl.encode_token_weights(token_weight_pairs["mt5xl"]) + return hydit_out[0], hydit_out[1], {"attention_mask": hydit_out[2]["attention_mask"], "conditioning_mt5xl": mt5_out[0], "attention_mask_mt5xl": mt5_out[2]["attention_mask"]} + + def load_sd(self, sd): + if "bert.encoder.layer.0.attention.self.query.weight" in sd: + return self.hydit_clip.load_sd(sd) + else: + return self.mt5xl.load_sd(sd) + + def set_clip_options(self, options): + self.hydit_clip.set_clip_options(options) + self.mt5xl.set_clip_options(options) + + def reset_clip_options(self): + self.hydit_clip.reset_clip_options() + self.mt5xl.reset_clip_options() diff --git a/comfy/text_encoders/hydit_clip.json b/comfy/text_encoders/hydit_clip.json new file mode 100644 index 000000000..c41c7c1ff --- /dev/null +++ b/comfy/text_encoders/hydit_clip.json @@ -0,0 +1,35 @@ +{ + "_name_or_path": "hfl/chinese-roberta-wwm-ext-large", + "architectures": [ + "BertModel" + ], + "attention_probs_dropout_prob": 0.1, + "bos_token_id": 0, + "classifier_dropout": null, + "directionality": "bidi", + "eos_token_id": 2, + "hidden_act": "gelu", + "hidden_dropout_prob": 0.1, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": 4096, + "layer_norm_eps": 1e-12, + "max_position_embeddings": 512, + "model_type": "bert", + "num_attention_heads": 16, + "num_hidden_layers": 24, + "output_past": true, + "pad_token_id": 0, + "pooler_fc_size": 768, + "pooler_num_attention_heads": 12, + "pooler_num_fc_layers": 3, + "pooler_size_per_head": 128, + "pooler_type": "first_token_transform", + "position_embedding_type": "absolute", + "torch_dtype": "float32", + "transformers_version": "4.22.1", + "type_vocab_size": 2, + "use_cache": true, + "vocab_size": 47020 +} + diff --git a/comfy/text_encoders/hydit_clip_tokenizer/special_tokens_map.json b/comfy/text_encoders/hydit_clip_tokenizer/special_tokens_map.json new file mode 100644 index 000000000..a8b3208c2 --- /dev/null +++ b/comfy/text_encoders/hydit_clip_tokenizer/special_tokens_map.json @@ -0,0 +1,7 @@ +{ + "cls_token": "[CLS]", + "mask_token": "[MASK]", + "pad_token": "[PAD]", + "sep_token": "[SEP]", + "unk_token": "[UNK]" +} diff --git a/comfy/text_encoders/hydit_clip_tokenizer/tokenizer_config.json b/comfy/text_encoders/hydit_clip_tokenizer/tokenizer_config.json new file mode 100644 index 000000000..a14356073 --- /dev/null +++ b/comfy/text_encoders/hydit_clip_tokenizer/tokenizer_config.json @@ -0,0 +1,16 @@ +{ + "cls_token": "[CLS]", + "do_basic_tokenize": true, + "do_lower_case": true, + "mask_token": "[MASK]", + "name_or_path": "hfl/chinese-roberta-wwm-ext", + "never_split": null, + "pad_token": "[PAD]", + "sep_token": "[SEP]", + "special_tokens_map_file": "/home/chenweifeng/.cache/huggingface/hub/models--hfl--chinese-roberta-wwm-ext/snapshots/5c58d0b8ec1d9014354d691c538661bf00bfdb44/special_tokens_map.json", + "strip_accents": null, + "tokenize_chinese_chars": true, + "tokenizer_class": "BertTokenizer", + "unk_token": "[UNK]", + "model_max_length": 77 +} diff --git a/comfy/text_encoders/hydit_clip_tokenizer/vocab.txt b/comfy/text_encoders/hydit_clip_tokenizer/vocab.txt new file mode 100644 index 000000000..624690680 --- /dev/null +++ b/comfy/text_encoders/hydit_clip_tokenizer/vocab.txt @@ -0,0 +1,47020 @@ +[PAD] +[unused1] +[unused2] +[unused3] +[unused4] +[unused5] +[unused6] +[unused7] +[unused8] +[unused9] +[unused10] +[unused11] +[unused12] +[unused13] +[unused14] +[unused15] +[unused16] +[unused17] +[unused18] +[unused19] +[unused20] +[unused21] +[unused22] +[unused23] +[unused24] +[unused25] +[unused26] +[unused27] +[unused28] +[unused29] +[unused30] +[unused31] +[unused32] +[unused33] +[unused34] +[unused35] +[unused36] +[unused37] +[unused38] +[unused39] +[unused40] +[unused41] +[unused42] +[unused43] +[unused44] +[unused45] +[unused46] +[unused47] +[unused48] +[unused49] +[unused50] +[unused51] +[unused52] +[unused53] +[unused54] +[unused55] +[unused56] +[unused57] +[unused58] +[unused59] +[unused60] +[unused61] +[unused62] +[unused63] +[unused64] +[unused65] +[unused66] +[unused67] +[unused68] +[unused69] +[unused70] +[unused71] +[unused72] +[unused73] +[unused74] +[unused75] +[unused76] +[unused77] +[unused78] +[unused79] +[unused80] +[unused81] +[unused82] +[unused83] +[unused84] +[unused85] +[unused86] +[unused87] +[unused88] +[unused89] +[unused90] +[unused91] +[unused92] +[unused93] +[unused94] +[unused95] +[unused96] +[unused97] +[unused98] +[unused99] +[UNK] +[CLS] +[SEP] +[MASK] + + +! +" +# +$ +% +& +' +( +) +* ++ +, +- +. +/ +0 +1 +2 +3 +4 +5 +6 +7 +8 +9 +: +; +< += +> +? +@ +[ +\ +] +^ +_ +a +b +c +d +e +f +g +h +i +j +k +l +m +n +o +p +q +r +s +t +u +v +w +x +y +z +{ +| +} +~ +£ +¤ +¥ +§ +© +« +® +° +± +² +³ +µ +· +¹ +º +» +¼ +× +ß +æ +÷ +ø +đ +ŋ +ɔ +ə +ɡ +ʰ +ˇ +ˈ +ˊ +ˋ +ˍ +ː +˙ +˚ +ˢ +α +β +γ +δ +ε +η +θ +ι +κ +λ +μ +ν +ο +π +ρ +ς +σ +τ +υ +φ +χ +ψ +ω +а +б +в +г +д +е +ж 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+##ᵀ +##ᵇ +##ᵈ +##ᵖ +##ᵗ +##ᵣ +##ᵤ +##ᵥ +##ᶜ +##ᶠ +##‐ +##‑ +##‒ +##– +##— +##― +##‘ +##’ +##‚ +##“ +##” +##‡ +##… +##⁰ +##⁴ +##⁵ +##⁶ +##⁷ +##⁸ +##⁹ +##⁻ +##₅ +##₆ +##₇ +##₈ +##₉ +##₊ +##₍ +##₎ +##ₐ +##ₑ +##ₒ +##ₓ +##ₕ +##ₖ +##ₗ +##ₘ +##ₚ +##ₛ +##ₜ +##₤ +##₩ +##₱ +##₹ +##ℓ +##ℝ +##⅓ +##⅔ +##↦ +##⇄ +##⇌ +##∂ +##∅ +##∆ +##∇ +##∈ +##∗ +##∘ +##∧ +##∨ +##∪ +##⊂ +##⊆ +##⊕ +##⊗ +##☉ +##♯ +##⟨ +##⟩ +##ⱼ +##⺩ +##⺼ +##⽥ +##亻 +##宀 +##彳 +##忄 +##扌 +##氵 +##疒 +##糹 +##訁 +##辶 +##阝 +##龸 +##fi +##fl diff --git a/comfy/text_encoders/mt5_config_xl.json b/comfy/text_encoders/mt5_config_xl.json new file mode 100644 index 000000000..092fefd6e --- /dev/null +++ b/comfy/text_encoders/mt5_config_xl.json @@ -0,0 +1,22 @@ +{ + "d_ff": 5120, + "d_kv": 64, + "d_model": 2048, + "decoder_start_token_id": 0, + "dropout_rate": 0.1, + "eos_token_id": 1, + "dense_act_fn": "gelu_pytorch_tanh", + "initializer_factor": 1.0, + "is_encoder_decoder": true, + "is_gated_act": true, + "layer_norm_epsilon": 1e-06, + "model_type": "mt5", + "num_decoder_layers": 24, + "num_heads": 32, + "num_layers": 24, + "output_past": true, + "pad_token_id": 0, + "relative_attention_num_buckets": 32, + "tie_word_embeddings": false, + "vocab_size": 250112 +} diff --git a/comfy/text_encoders/spiece_tokenizer.py b/comfy/text_encoders/spiece_tokenizer.py index deb026ffd..73739553d 100644 --- a/comfy/text_encoders/spiece_tokenizer.py +++ b/comfy/text_encoders/spiece_tokenizer.py @@ -27,3 +27,6 @@ class SPieceTokenizer: def __call__(self, string): out = self.tokenizer.encode(string) return {"input_ids": out} + + def serialize_model(self): + return torch.ByteTensor(list(self.tokenizer.serialized_model_proto())) From 61a2b00bc2f06dec3b570dfde2eb43890613d054 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Thu, 25 Jul 2024 19:06:43 -0400 Subject: [PATCH 120/133] Add HunyuanDiT support to readme. --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index 5f747321f..c2100cab2 100644 --- a/README.md +++ b/README.md @@ -33,6 +33,7 @@ This ui will let you design and execute advanced stable diffusion pipelines usin - [LCM models and Loras](https://comfyanonymous.github.io/ComfyUI_examples/lcm/) - [SDXL Turbo](https://comfyanonymous.github.io/ComfyUI_examples/sdturbo/) - [AuraFlow](https://comfyanonymous.github.io/ComfyUI_examples/aura_flow/) +- [HunyuanDiT](https://comfyanonymous.github.io/ComfyUI_examples/hunyuan_dit/) - Latent previews with [TAESD](#how-to-show-high-quality-previews) - Starts up very fast. - Works fully offline: will never download anything. From 25b51b1a8b6be9c3dadd1d755c78394009c4d1d4 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Thu, 25 Jul 2024 22:42:54 -0400 Subject: [PATCH 121/133] Hunyuan DiT lora support. --- comfy/lora.py | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/comfy/lora.py b/comfy/lora.py index e36b354f0..fdc128c09 100644 --- a/comfy/lora.py +++ b/comfy/lora.py @@ -282,4 +282,10 @@ def model_lora_keys_unet(model, key_map={}): key_lora = "transformer.{}".format(k[:-len(".weight")]) #simpletrainer and probably regular diffusers lora format key_map[key_lora] = to + if isinstance(model, comfy.model_base.HunyuanDiT): + for k in sdk: + if k.startswith("diffusion_model.") and k.endswith(".weight"): + key_lora = k[len("diffusion_model."):-len(".weight")] + key_map["base_model.model.{}".format(key_lora)] = k #official hunyuan lora format + return key_map From a9ac56fc0db5777de0edf2fe4b8ed628ccab1293 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Fri, 26 Jul 2024 04:32:33 -0400 Subject: [PATCH 122/133] Own BertModel implementation that works with lowvram. --- comfy/text_encoders/bert.py | 139 +++++++++++++++++++++++++++++++++++ comfy/text_encoders/hydit.py | 47 +----------- 2 files changed, 142 insertions(+), 44 deletions(-) create mode 100644 comfy/text_encoders/bert.py diff --git a/comfy/text_encoders/bert.py b/comfy/text_encoders/bert.py new file mode 100644 index 000000000..b76e76660 --- /dev/null +++ b/comfy/text_encoders/bert.py @@ -0,0 +1,139 @@ +import torch +from comfy.ldm.modules.attention import optimized_attention_for_device + +class BertAttention(torch.nn.Module): + def __init__(self, embed_dim, heads, dtype, device, operations): + super().__init__() + + self.heads = heads + self.query = operations.Linear(embed_dim, embed_dim, bias=True, dtype=dtype, device=device) + self.key = operations.Linear(embed_dim, embed_dim, bias=True, dtype=dtype, device=device) + self.value = operations.Linear(embed_dim, embed_dim, bias=True, dtype=dtype, device=device) + + + def forward(self, x, mask=None, optimized_attention=None): + q = self.query(x) + k = self.key(x) + v = self.value(x) + + out = optimized_attention(q, k, v, self.heads, mask) + return out + +class BertOutput(torch.nn.Module): + def __init__(self, input_dim, output_dim, layer_norm_eps, dtype, device, operations): + super().__init__() + self.dense = operations.Linear(input_dim, output_dim, dtype=dtype, device=device) + self.LayerNorm = operations.LayerNorm(output_dim, eps=layer_norm_eps, dtype=dtype, device=device) + # self.dropout = nn.Dropout(0.0) + + def forward(self, x, y): + x = self.dense(x) + # hidden_states = self.dropout(hidden_states) + x = self.LayerNorm(x + y) + return x + +class BertAttentionBlock(torch.nn.Module): + def __init__(self, embed_dim, heads, layer_norm_eps, dtype, device, operations): + super().__init__() + self.self = BertAttention(embed_dim, heads, dtype, device, operations) + self.output = BertOutput(embed_dim, embed_dim, layer_norm_eps, dtype, device, operations) + + def forward(self, x, mask, optimized_attention): + y = self.self(x, mask, optimized_attention) + return self.output(y, x) + +class BertIntermediate(torch.nn.Module): + def __init__(self, embed_dim, intermediate_dim, dtype, device, operations): + super().__init__() + self.dense = operations.Linear(embed_dim, intermediate_dim, dtype=dtype, device=device) + + def forward(self, x): + x = self.dense(x) + return torch.nn.functional.gelu(x) + + +class BertBlock(torch.nn.Module): + def __init__(self, embed_dim, intermediate_dim, heads, layer_norm_eps, dtype, device, operations): + super().__init__() + self.attention = BertAttentionBlock(embed_dim, heads, layer_norm_eps, dtype, device, operations) + self.intermediate = BertIntermediate(embed_dim, intermediate_dim, dtype, device, operations) + self.output = BertOutput(intermediate_dim, embed_dim, layer_norm_eps, dtype, device, operations) + + def forward(self, x, mask, optimized_attention): + x = self.attention(x, mask, optimized_attention) + y = self.intermediate(x) + return self.output(y, x) + +class BertEncoder(torch.nn.Module): + def __init__(self, num_layers, embed_dim, intermediate_dim, heads, layer_norm_eps, dtype, device, operations): + super().__init__() + self.layer = torch.nn.ModuleList([BertBlock(embed_dim, intermediate_dim, heads, layer_norm_eps, dtype, device, operations) for i in range(num_layers)]) + + def forward(self, x, mask=None, intermediate_output=None): + optimized_attention = optimized_attention_for_device(x.device, mask=mask is not None, small_input=True) + + if intermediate_output is not None: + if intermediate_output < 0: + intermediate_output = len(self.layer) + intermediate_output + + intermediate = None + for i, l in enumerate(self.layer): + x = l(x, mask, optimized_attention) + if i == intermediate_output: + intermediate = x.clone() + return x, intermediate + +class BertEmbeddings(torch.nn.Module): + def __init__(self, vocab_size, max_position_embeddings, type_vocab_size, pad_token_id, embed_dim, layer_norm_eps, dtype, device, operations): + super().__init__() + self.word_embeddings = torch.nn.Embedding(vocab_size, embed_dim, padding_idx=pad_token_id, dtype=dtype, device=device) + self.position_embeddings = torch.nn.Embedding(max_position_embeddings, embed_dim, dtype=dtype, device=device) + self.token_type_embeddings = torch.nn.Embedding(type_vocab_size, embed_dim, dtype=dtype, device=device) + + self.LayerNorm = operations.LayerNorm(embed_dim, eps=layer_norm_eps, dtype=dtype, device=device) + + def forward(self, input_tokens, token_type_ids=None): + x = self.word_embeddings(input_tokens) + x += self.position_embeddings.weight[:x.shape[1]] + if token_type_ids is not None: + x += self.token_type_embeddings(token_type_ids) + else: + x += self.token_type_embeddings.weight[0] + x = self.LayerNorm(x) + return x + + +class BertModel_(torch.nn.Module): + def __init__(self, config_dict, dtype, device, operations): + super().__init__() + embed_dim = config_dict["hidden_size"] + layer_norm_eps = config_dict["layer_norm_eps"] + + self.embeddings = BertEmbeddings(config_dict["vocab_size"], config_dict["max_position_embeddings"], config_dict["type_vocab_size"], config_dict["pad_token_id"], embed_dim, layer_norm_eps, dtype, device, operations) + self.encoder = BertEncoder(config_dict["num_hidden_layers"], embed_dim, config_dict["intermediate_size"], config_dict["num_attention_heads"], layer_norm_eps, dtype, device, operations) + + def forward(self, input_tokens, attention_mask=None, intermediate_output=None, final_layer_norm_intermediate=True): + x = self.embeddings(input_tokens) + mask = None + if attention_mask is not None: + mask = 1.0 - attention_mask.to(x.dtype).reshape((attention_mask.shape[0], 1, -1, attention_mask.shape[-1])).expand(attention_mask.shape[0], 1, attention_mask.shape[-1], attention_mask.shape[-1]) + mask = mask.masked_fill(mask.to(torch.bool), float("-inf")) + + x, i = self.encoder(x, mask, intermediate_output) + return x, i + + +class BertModel(torch.nn.Module): + def __init__(self, config_dict, dtype, device, operations): + super().__init__() + self.bert = BertModel_(config_dict, dtype, device, operations) + self.num_layers = config_dict["num_hidden_layers"] + + def get_input_embeddings(self): + return self.bert.embeddings.word_embeddings + + def set_input_embeddings(self, embeddings): + self.bert.embeddings.word_embeddings = embeddings + + def forward(self, *args, **kwargs): + return self.bert(*args, **kwargs) diff --git a/comfy/text_encoders/hydit.py b/comfy/text_encoders/hydit.py index e47c8cb20..fc1d3c75d 100644 --- a/comfy/text_encoders/hydit.py +++ b/comfy/text_encoders/hydit.py @@ -1,56 +1,15 @@ from comfy import sd1_clip -from transformers import T5TokenizerFast, BertTokenizer, BertModel, modeling_utils, BertConfig +from transformers import BertTokenizer from .spiece_tokenizer import SPieceTokenizer +from .bert import BertModel import comfy.text_encoders.t5 import os - import torch -import contextlib - -@contextlib.contextmanager -def use_comfy_ops(ops, device=None, dtype=None): - old_torch_nn_linear = torch.nn.Linear - force_device = device - force_dtype = dtype - def linear_with_dtype(in_features: int, out_features: int, bias: bool = True, device=None, dtype=None): - if force_device is not None: - device = force_device - if force_dtype is not None: - dtype = force_dtype - return ops.Linear(in_features, out_features, bias=bias, device=device, dtype=dtype) - - torch.nn.Linear = linear_with_dtype - try: - yield - finally: - torch.nn.Linear = old_torch_nn_linear - - -class RobertaWrapper(torch.nn.Module): - def __init__(self, config_dict, dtype, device, operations): - super().__init__() - config = BertConfig(**config_dict) - with use_comfy_ops(operations, device, dtype): - with modeling_utils.no_init_weights(): - self.bert = BertModel(config, add_pooling_layer=False) - - self.num_layers = config.num_hidden_layers - - def get_input_embeddings(self): - return self.bert.get_input_embeddings() - - def set_input_embeddings(self, value): - return self.bert.set_input_embeddings(value) - - def forward(self, input_tokens, attention_mask=None, intermediate_output=None, final_layer_norm_intermediate=True): - intermediate = None - out = self.bert(input_ids=input_tokens, output_hidden_states=intermediate_output is not None, attention_mask=attention_mask) - return out.last_hidden_state, intermediate, out.pooler_output class HyditBertModel(sd1_clip.SDClipModel): def __init__(self, device="cpu", layer="last", layer_idx=None, dtype=None): textmodel_json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "hydit_clip.json") - super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, dtype=dtype, special_tokens={"start": 101, "end": 102, "pad": 0}, model_class=RobertaWrapper, enable_attention_masks=True, return_attention_masks=True) + super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, dtype=dtype, special_tokens={"start": 101, "end": 102, "pad": 0}, model_class=BertModel, enable_attention_masks=True, return_attention_masks=True) class HyditBertTokenizer(sd1_clip.SDTokenizer): def __init__(self, embedding_directory=None, tokenizer_data={}): From afe732bef960d753661acb5b886ba42573dd3720 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Fri, 26 Jul 2024 11:52:58 -0400 Subject: [PATCH 123/133] Hunyuan dit can now accept longer prompts. --- comfy/ldm/hydit/models.py | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/comfy/ldm/hydit/models.py b/comfy/ldm/hydit/models.py index 4bd7abab6..bde9687e2 100644 --- a/comfy/ldm/hydit/models.py +++ b/comfy/ldm/hydit/models.py @@ -319,13 +319,15 @@ class HunYuanDiT(nn.Module): text_states_mask = text_embedding_mask.bool() # 2,77 text_states_t5_mask = text_embedding_mask_t5.bool() # 2,256 b_t5, l_t5, c_t5 = text_states_t5.shape - text_states_t5 = self.mlp_t5(text_states_t5.view(-1, c_t5)) - text_states = torch.cat([text_states, text_states_t5.view(b_t5, l_t5, -1)], dim=1) # 2,205，1024 + text_states_t5 = self.mlp_t5(text_states_t5.view(-1, c_t5)).view(b_t5, l_t5, -1) - clip_t5_mask = torch.cat([text_states_mask, text_states_t5_mask], dim=-1) + padding = self.text_embedding_padding.to(text_states) - clip_t5_mask = clip_t5_mask - text_states = torch.where(clip_t5_mask.unsqueeze(2), text_states, self.text_embedding_padding.to(text_states)) + text_states[:,-self.text_len:] = torch.where(text_states_mask[:,-self.text_len:].unsqueeze(2), text_states[:,-self.text_len:], padding[:self.text_len]) + text_states_t5[:,-self.text_len_t5:] = torch.where(text_states_t5_mask[:,-self.text_len_t5:].unsqueeze(2), text_states_t5[:,-self.text_len_t5:], padding[self.text_len:]) + + text_states = torch.cat([text_states, text_states_t5], dim=1) # 2,205，1024 + # clip_t5_mask = torch.cat([text_states_mask, text_states_t5_mask], dim=-1) _, _, oh, ow = x.shape th, tw = (oh + (self.patch_size // 2)) // self.patch_size, (ow + (self.patch_size // 2)) // self.patch_size From 8328a2d8cdabd0e42b856dd0193ebc24ea41c359 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Fri, 26 Jul 2024 12:11:32 -0400 Subject: [PATCH 124/133] Let hunyuan dit work with all prompt lengths. --- comfy/ldm/hydit/poolers.py | 1 + 1 file changed, 1 insertion(+) diff --git a/comfy/ldm/hydit/poolers.py b/comfy/ldm/hydit/poolers.py index 3470041b5..2c6e46e67 100644 --- a/comfy/ldm/hydit/poolers.py +++ b/comfy/ldm/hydit/poolers.py @@ -16,6 +16,7 @@ class AttentionPool(nn.Module): self.embed_dim = embed_dim def forward(self, x): + x = x[:,:self.positional_embedding.shape[0] - 1] x = x.permute(1, 0, 2) # NLC -> LNC x = torch.cat([x.mean(dim=0, keepdim=True), x], dim=0) # (L+1)NC x = x + self.positional_embedding[:, None, :].to(dtype=x.dtype, device=x.device) # (L+1)NC From b6779d8df310bcac115d9949fcc6c7502b4c9551 Mon Sep 17 00:00:00 2001 From: filtered <176114999+webfiltered@users.noreply.github.com> Date: Sat, 27 Jul 2024 02:25:42 +1000 Subject: [PATCH 125/133] Fix undo incorrectly undoing text input (#4114) Fixes an issue where under certain conditions, the ComfyUI custom undo / redo functions would not run when intended to. When trying to undo an action like deleting several nodes, instead the native browser undo runs - e.g. a textarea gets focus and the last typed text is undone. Clicking outside the text area and typing again just keeps doing the same thing. --- web/scripts/changeTracker.js | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/web/scripts/changeTracker.js b/web/scripts/changeTracker.js index 39bc4a810..d7798dbe9 100644 --- a/web/scripts/changeTracker.js +++ b/web/scripts/changeTracker.js @@ -105,15 +105,16 @@ export class ChangeTracker { window.addEventListener( "keydown", (e) => { + const activeEl = document.activeElement; requestAnimationFrame(async () => { - let activeEl; + let bindInputEl; // If we are auto queue in change mode then we do want to trigger on inputs if (!app.ui.autoQueueEnabled || app.ui.autoQueueMode === "instant") { - activeEl = document.activeElement; if (activeEl?.tagName === "INPUT" || activeEl?.["type"] === "textarea") { // Ignore events on inputs, they have their native history return; } + bindInputEl = activeEl; } keyIgnored = e.key === "Control" || e.key === "Shift" || e.key === "Alt" || e.key === "Meta"; @@ -123,7 +124,7 @@ export class ChangeTracker { if (await changeTracker().undoRedo(e)) return; // If our active element is some type of input then handle changes after they're done - if (ChangeTracker.bindInput(activeEl)) return; + if (ChangeTracker.bindInput(bindInputEl)) return; changeTracker().checkState(); }); }, From 6225a7827c17bc237167f8500029d282f4c91950 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Fri, 26 Jul 2024 13:04:48 -0400 Subject: [PATCH 126/133] Add CLIPTextEncodeHunyuanDiT. Useful for testing what each text encoder does. --- comfy_extras/nodes_hunyuan.py | 24 ++++++++++++++++++++++++ nodes.py | 1 + 2 files changed, 25 insertions(+) create mode 100644 comfy_extras/nodes_hunyuan.py diff --git a/comfy_extras/nodes_hunyuan.py b/comfy_extras/nodes_hunyuan.py new file mode 100644 index 000000000..a3ac8cb06 --- /dev/null +++ b/comfy_extras/nodes_hunyuan.py @@ -0,0 +1,24 @@ +class CLIPTextEncodeHunyuanDiT: + @classmethod + def INPUT_TYPES(s): + return {"required": { + "clip": ("CLIP", ), + "bert": ("STRING", {"multiline": True, "dynamicPrompts": True}), + "mt5xl": ("STRING", {"multiline": True, "dynamicPrompts": True}), + }} + RETURN_TYPES = ("CONDITIONING",) + FUNCTION = "encode" + + CATEGORY = "advanced/conditioning" + + def encode(self, clip, bert, mt5xl): + tokens = clip.tokenize(bert) + tokens["mt5xl"] = clip.tokenize(mt5xl)["mt5xl"] + + output = clip.encode_from_tokens(tokens, return_pooled=True, return_dict=True) + cond = output.pop("cond") + return ([[cond, output]], ) + +NODE_CLASS_MAPPINGS = { + "CLIPTextEncodeHunyuanDiT": CLIPTextEncodeHunyuanDiT, +} diff --git a/nodes.py b/nodes.py index fbdcb6c91..dc66dd3ef 100644 --- a/nodes.py +++ b/nodes.py @@ -2037,6 +2037,7 @@ def init_builtin_extra_nodes(): "nodes_sd3.py", "nodes_gits.py", "nodes_controlnet.py", + "nodes_hunyuan.py", ] import_failed = [] From cf4418b806af5f7f67e3ce5b6ee386360b410bbb Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Fri, 26 Jul 2024 13:07:39 -0400 Subject: [PATCH 127/133] Don't treat Bert model like CLIP. Bert can accept up to 512 tokens so any prompt with more than 77 should just be passed to it as is instead of splitting it up like CLIP. --- comfy/text_encoders/hydit.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/comfy/text_encoders/hydit.py b/comfy/text_encoders/hydit.py index fc1d3c75d..ac0c893bc 100644 --- a/comfy/text_encoders/hydit.py +++ b/comfy/text_encoders/hydit.py @@ -14,7 +14,7 @@ class HyditBertModel(sd1_clip.SDClipModel): class HyditBertTokenizer(sd1_clip.SDTokenizer): def __init__(self, embedding_directory=None, tokenizer_data={}): tokenizer_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "hydit_clip_tokenizer") - super().__init__(tokenizer_path, pad_with_end=False, embedding_size=1024, embedding_key='chinese_roberta', tokenizer_class=BertTokenizer) + super().__init__(tokenizer_path, pad_with_end=False, embedding_size=1024, embedding_key='chinese_roberta', tokenizer_class=BertTokenizer, pad_to_max_length=False, max_length=512, min_length=77) class MT5XLModel(sd1_clip.SDClipModel): From 17b41f622ef64ba9a9ce38da0f1038e718508dc6 Mon Sep 17 00:00:00 2001 From: Robin Huang Date: Fri, 26 Jul 2024 11:37:40 -0700 Subject: [PATCH 128/133] Change windows standalone URL to stable release. (#4065) --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index c2100cab2..6a68f268a 100644 --- a/README.md +++ b/README.md @@ -78,7 +78,7 @@ Ctrl can also be replaced with Cmd instead for macOS users There is a portable standalone build for Windows that should work for running on Nvidia GPUs or for running on your CPU only on the [releases page](https://github.com/comfyanonymous/ComfyUI/releases). -### [Direct link to download](https://github.com/comfyanonymous/ComfyUI/releases/download/latest/ComfyUI_windows_portable_nvidia_cu121_or_cpu.7z) +### [Direct link to download](https://github.com/comfyanonymous/ComfyUI/releases/latest/download/ComfyUI_windows_portable_nvidia.7z) Simply download, extract with [7-Zip](https://7-zip.org) and run. Make sure you put your Stable Diffusion checkpoints/models (the huge ckpt/safetensors files) in: ComfyUI\models\checkpoints From 45a2842d7fe2ed92c3402c0a17b55bd46366b407 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Fri, 26 Jul 2024 14:52:00 -0400 Subject: [PATCH 129/133] Set stable releases as a prerelease initially. This should give time to test the standalone package before making it live. --- .github/workflows/stable-release.yml | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/.github/workflows/stable-release.yml b/.github/workflows/stable-release.yml index 1fd76b530..19035c02c 100644 --- a/.github/workflows/stable-release.yml +++ b/.github/workflows/stable-release.yml @@ -106,4 +106,5 @@ jobs: file: ComfyUI_windows_portable_nvidia.7z tag: ${{ github.ref }} overwrite: true - + prerelease: true + make_latest: false From e746965c5051660ffa10330c00461094270f0207 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Sat, 27 Jul 2024 01:20:18 -0400 Subject: [PATCH 130/133] Update nightly package workflow. --- .github/workflows/windows_release_nightly_pytorch.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/windows_release_nightly_pytorch.yml b/.github/workflows/windows_release_nightly_pytorch.yml index e68011b64..ba388cd44 100644 --- a/.github/workflows/windows_release_nightly_pytorch.yml +++ b/.github/workflows/windows_release_nightly_pytorch.yml @@ -19,7 +19,7 @@ on: description: 'python patch version' required: true type: string - default: "3" + default: "4" # push: # branches: # - master @@ -49,7 +49,7 @@ jobs: echo 'import site' >> ./python3${{ inputs.python_minor }}._pth curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py ./python.exe get-pip.py - python -m pip wheel torch torchvision torchaudio mpmath==1.3.0 numpy==1.26.4 --pre --extra-index-url https://download.pytorch.org/whl/nightly/cu${{ inputs.cu }} -r ../ComfyUI/requirements.txt pygit2 -w ../temp_wheel_dir + python -m pip wheel torch torchvision torchaudio --pre --extra-index-url https://download.pytorch.org/whl/nightly/cu${{ inputs.cu }} -r ../ComfyUI/requirements.txt pygit2 -w ../temp_wheel_dir ls ../temp_wheel_dir ./python.exe -s -m pip install --pre ../temp_wheel_dir/* sed -i '1i../ComfyUI' ./python3${{ inputs.python_minor }}._pth From 07f6a1a685d16a1b7e2c4b05d94670d2543ec29e Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Sat, 27 Jul 2024 03:15:22 -0400 Subject: [PATCH 131/133] Handle case in the updater when master branch is not in local repo. --- .ci/update_windows/update.py | 11 +++++++++-- 1 file changed, 9 insertions(+), 2 deletions(-) diff --git a/.ci/update_windows/update.py b/.ci/update_windows/update.py index 127247b2f..cc79a914e 100755 --- a/.ci/update_windows/update.py +++ b/.ci/update_windows/update.py @@ -62,8 +62,15 @@ except: print("checking out master branch") branch = repo.lookup_branch('master') -ref = repo.lookup_reference(branch.name) -repo.checkout(ref) +if branch is None: + ref = repo.lookup_reference('refs/remotes/origin/master') + repo.checkout(ref) + branch = repo.lookup_branch('master') + if branch is None: + repo.create_branch('master', repo.get(ref.target)) +else: + ref = repo.lookup_reference(branch.name) + repo.checkout(ref) print("pulling latest changes") pull(repo) From e6829e7ac5bef5db8099005b5b038c49e173e87c Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Sat, 27 Jul 2024 04:41:46 -0400 Subject: [PATCH 132/133] Add a way to set custom dependencies in the release workflow. --- .github/workflows/windows_release_dependencies.yml | 11 ++++++++--- 1 file changed, 8 insertions(+), 3 deletions(-) diff --git a/.github/workflows/windows_release_dependencies.yml b/.github/workflows/windows_release_dependencies.yml index 5aa57e7d7..8d3a8665d 100644 --- a/.github/workflows/windows_release_dependencies.yml +++ b/.github/workflows/windows_release_dependencies.yml @@ -8,11 +8,16 @@ on: required: false type: string default: "" + extra_dependencies: + description: 'extra dependencies' + required: false + type: string + default: "\"numpy<2\"" cu: description: 'cuda version' required: true type: string - default: "121" + default: "124" python_minor: description: 'python minor version' @@ -24,7 +29,7 @@ on: description: 'python patch version' required: true type: string - default: "8" + default: "9" # push: # branches: # - master @@ -51,7 +56,7 @@ jobs: ..\python_embeded\python.exe -s -m pip install --upgrade torch torchvision torchaudio ${{ inputs.xformers }} --extra-index-url https://download.pytorch.org/whl/cu${{ inputs.cu }} -r ../ComfyUI/requirements.txt pygit2 pause" > update_comfyui_and_python_dependencies.bat - python -m pip wheel --no-cache-dir torch torchvision torchaudio ${{ inputs.xformers }} --extra-index-url https://download.pytorch.org/whl/cu${{ inputs.cu }} -r requirements.txt pygit2 -w ./temp_wheel_dir + python -m pip wheel --no-cache-dir torch torchvision torchaudio ${{ inputs.xformers }} ${{ inputs.extra_dependencies }} --extra-index-url https://download.pytorch.org/whl/cu${{ inputs.cu }} -r requirements.txt pygit2 -w ./temp_wheel_dir python -m pip install --no-cache-dir ./temp_wheel_dir/* echo installed basic ls -lah temp_wheel_dir From f82d09c9b40fd9ebbc080bc5662ddb39787b1ec9 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Sat, 27 Jul 2024 04:48:19 -0400 Subject: [PATCH 133/133] Update packaging workflow. --- .github/workflows/windows_release_package.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/windows_release_package.yml b/.github/workflows/windows_release_package.yml index 020741c41..5aed73e55 100644 --- a/.github/workflows/windows_release_package.yml +++ b/.github/workflows/windows_release_package.yml @@ -7,7 +7,7 @@ on: description: 'cuda version' required: true type: string - default: "121" + default: "124" python_minor: description: 'python minor version' @@ -19,7 +19,7 @@ on: description: 'python patch version' required: true type: string - default: "8" + default: "9" # push: # branches: # - master