diff --git a/.github/PULL_REQUEST_TEMPLATE/api-node.md b/.github/PULL_REQUEST_TEMPLATE/api-node.md index f62744878..c1f1bafb1 100644 --- a/.github/PULL_REQUEST_TEMPLATE/api-node.md +++ b/.github/PULL_REQUEST_TEMPLATE/api-node.md @@ -18,4 +18,4 @@ If **Need pricing update**: - [ ] **QA not required** ### Comms -- [ ] Informed **@Kosinkadink** +- [ ] Informed **Kosinkadink** diff --git a/.github/workflows/api-node-template.yml b/.github/workflows/api-node-template.yml index 0775f9979..fdb81c0c5 100644 --- a/.github/workflows/api-node-template.yml +++ b/.github/workflows/api-node-template.yml @@ -2,7 +2,7 @@ name: Append API Node PR template on: pull_request_target: - types: [opened, reopened, synchronize, edited, ready_for_review] + types: [opened, reopened, synchronize, ready_for_review] paths: - 'comfy_api_nodes/**' # only run if these files changed diff --git a/.github/workflows/release-stable-all.yml b/.github/workflows/release-stable-all.yml index 7dca7277b..f7de3a7c3 100644 --- a/.github/workflows/release-stable-all.yml +++ b/.github/workflows/release-stable-all.yml @@ -43,6 +43,23 @@ jobs: test_release: true secrets: inherit + release_nvidia_cu126: + permissions: + contents: "write" + packages: "write" + pull-requests: "read" + name: "Release NVIDIA cu126" + uses: ./.github/workflows/stable-release.yml + with: + git_tag: ${{ inputs.git_tag }} + cache_tag: "cu126" + python_minor: "12" + python_patch: "10" + rel_name: "nvidia" + rel_extra_name: "_cu126" + test_release: true + secrets: inherit + release_amd_rocm: permissions: contents: "write" diff --git a/comfy_extras/nodes_easycache.py b/comfy_extras/nodes_easycache.py index 1359e2f99..11b23ffdb 100644 --- a/comfy_extras/nodes_easycache.py +++ b/comfy_extras/nodes_easycache.py @@ -11,13 +11,13 @@ if TYPE_CHECKING: def easycache_forward_wrapper(executor, *args, **kwargs): # get values from args - x: torch.Tensor = args[0] transformer_options: dict[str] = args[-1] if not isinstance(transformer_options, dict): transformer_options = kwargs.get("transformer_options") if not transformer_options: transformer_options = args[-2] easycache: EasyCacheHolder = transformer_options["easycache"] + x: torch.Tensor = args[0][:, :easycache.output_channels] sigmas = transformer_options["sigmas"] uuids = transformer_options["uuids"] if sigmas is not None and easycache.is_past_end_timestep(sigmas): @@ -82,13 +82,13 @@ def easycache_forward_wrapper(executor, *args, **kwargs): def lazycache_predict_noise_wrapper(executor, *args, **kwargs): # get values from args - x: torch.Tensor = args[0] timestep: float = args[1] model_options: dict[str] = args[2] easycache: LazyCacheHolder = model_options["transformer_options"]["easycache"] if easycache.is_past_end_timestep(timestep): return executor(*args, **kwargs) # prepare next x_prev + x: torch.Tensor = args[0][:, :easycache.output_channels] next_x_prev = x input_change = None do_easycache = easycache.should_do_easycache(timestep) @@ -173,7 +173,7 @@ def easycache_sample_wrapper(executor, *args, **kwargs): class EasyCacheHolder: - def __init__(self, reuse_threshold: float, start_percent: float, end_percent: float, subsample_factor: int, offload_cache_diff: bool, verbose: bool=False): + def __init__(self, reuse_threshold: float, start_percent: float, end_percent: float, subsample_factor: int, offload_cache_diff: bool, verbose: bool=False, output_channels: int=None): self.name = "EasyCache" self.reuse_threshold = reuse_threshold self.start_percent = start_percent @@ -202,6 +202,7 @@ class EasyCacheHolder: self.allow_mismatch = True self.cut_from_start = True self.state_metadata = None + self.output_channels = output_channels def is_past_end_timestep(self, timestep: float) -> bool: return not (timestep[0] > self.end_t).item() @@ -264,7 +265,7 @@ class EasyCacheHolder: else: slicing.append(slice(None)) batch_slice = batch_slice + slicing - x[batch_slice] += self.uuid_cache_diffs[uuid].to(x.device) + x[tuple(batch_slice)] += self.uuid_cache_diffs[uuid].to(x.device) return x def update_cache_diff(self, output: torch.Tensor, x: torch.Tensor, uuids: list[UUID]): @@ -283,7 +284,7 @@ class EasyCacheHolder: else: slicing.append(slice(None)) skip_dim = False - x = x[slicing] + x = x[tuple(slicing)] diff = output - x batch_offset = diff.shape[0] // len(uuids) for i, uuid in enumerate(uuids): @@ -323,7 +324,7 @@ class EasyCacheHolder: return self def clone(self): - return EasyCacheHolder(self.reuse_threshold, self.start_percent, self.end_percent, self.subsample_factor, self.offload_cache_diff, self.verbose) + return EasyCacheHolder(self.reuse_threshold, self.start_percent, self.end_percent, self.subsample_factor, self.offload_cache_diff, self.verbose, output_channels=self.output_channels) class EasyCacheNode(io.ComfyNode): @@ -350,7 +351,7 @@ class EasyCacheNode(io.ComfyNode): @classmethod def execute(cls, model: io.Model.Type, reuse_threshold: float, start_percent: float, end_percent: float, verbose: bool) -> io.NodeOutput: model = model.clone() - model.model_options["transformer_options"]["easycache"] = EasyCacheHolder(reuse_threshold, start_percent, end_percent, subsample_factor=8, offload_cache_diff=False, verbose=verbose) + model.model_options["transformer_options"]["easycache"] = EasyCacheHolder(reuse_threshold, start_percent, end_percent, subsample_factor=8, offload_cache_diff=False, verbose=verbose, output_channels=model.model.latent_format.latent_channels) model.add_wrapper_with_key(comfy.patcher_extension.WrappersMP.OUTER_SAMPLE, "easycache", easycache_sample_wrapper) model.add_wrapper_with_key(comfy.patcher_extension.WrappersMP.CALC_COND_BATCH, "easycache", easycache_calc_cond_batch_wrapper) model.add_wrapper_with_key(comfy.patcher_extension.WrappersMP.DIFFUSION_MODEL, "easycache", easycache_forward_wrapper) @@ -358,7 +359,7 @@ class EasyCacheNode(io.ComfyNode): class LazyCacheHolder: - def __init__(self, reuse_threshold: float, start_percent: float, end_percent: float, subsample_factor: int, offload_cache_diff: bool, verbose: bool=False): + def __init__(self, reuse_threshold: float, start_percent: float, end_percent: float, subsample_factor: int, offload_cache_diff: bool, verbose: bool=False, output_channels: int=None): self.name = "LazyCache" self.reuse_threshold = reuse_threshold self.start_percent = start_percent @@ -382,6 +383,7 @@ class LazyCacheHolder: self.approx_output_change_rates = [] self.total_steps_skipped = 0 self.state_metadata = None + self.output_channels = output_channels def has_cache_diff(self) -> bool: return self.cache_diff is not None @@ -456,7 +458,7 @@ class LazyCacheHolder: return self def clone(self): - return LazyCacheHolder(self.reuse_threshold, self.start_percent, self.end_percent, self.subsample_factor, self.offload_cache_diff, self.verbose) + return LazyCacheHolder(self.reuse_threshold, self.start_percent, self.end_percent, self.subsample_factor, self.offload_cache_diff, self.verbose, output_channels=self.output_channels) class LazyCacheNode(io.ComfyNode): @classmethod @@ -482,7 +484,7 @@ class LazyCacheNode(io.ComfyNode): @classmethod def execute(cls, model: io.Model.Type, reuse_threshold: float, start_percent: float, end_percent: float, verbose: bool) -> io.NodeOutput: model = model.clone() - model.model_options["transformer_options"]["easycache"] = LazyCacheHolder(reuse_threshold, start_percent, end_percent, subsample_factor=8, offload_cache_diff=False, verbose=verbose) + model.model_options["transformer_options"]["easycache"] = LazyCacheHolder(reuse_threshold, start_percent, end_percent, subsample_factor=8, offload_cache_diff=False, verbose=verbose, output_channels=model.model.latent_format.latent_channels) model.add_wrapper_with_key(comfy.patcher_extension.WrappersMP.OUTER_SAMPLE, "lazycache", easycache_sample_wrapper) model.add_wrapper_with_key(comfy.patcher_extension.WrappersMP.PREDICT_NOISE, "lazycache", lazycache_predict_noise_wrapper) return io.NodeOutput(model) diff --git a/comfy_extras/nodes_nop.py b/comfy_extras/nodes_nop.py new file mode 100644 index 000000000..953061bcb --- /dev/null +++ b/comfy_extras/nodes_nop.py @@ -0,0 +1,39 @@ +from comfy_api.latest import ComfyExtension, io +from typing_extensions import override +# If you write a node that is so useless that it breaks ComfyUI it will be featured in this exclusive list + +# "native" block swap nodes are placebo at best and break the ComfyUI memory management system. +# They are also considered harmful because instead of users reporting issues with the built in +# memory management they install these stupid nodes and complain even harder. Now it completely +# breaks with some of the new ComfyUI memory optimizations so I have made the decision to NOP it +# out of all workflows. +class wanBlockSwap(io.ComfyNode): + @classmethod + def define_schema(cls): + return io.Schema( + node_id="wanBlockSwap", + category="", + description="NOP", + inputs=[ + io.Model.Input("model"), + ], + outputs=[ + io.Model.Output(), + ], + is_deprecated=True, + ) + + @classmethod + def execute(cls, model) -> io.NodeOutput: + return io.NodeOutput(model) + + +class NopExtension(ComfyExtension): + @override + async def get_node_list(self) -> list[type[io.ComfyNode]]: + return [ + wanBlockSwap + ] + +async def comfy_entrypoint() -> NopExtension: + return NopExtension() diff --git a/nodes.py b/nodes.py index 5689f6fe1..f6aeedc78 100644 --- a/nodes.py +++ b/nodes.py @@ -2330,6 +2330,7 @@ async def init_builtin_extra_nodes(): "nodes_easycache.py", "nodes_audio_encoder.py", "nodes_rope.py", + "nodes_nop.py", ] import_failed = [] diff --git a/pyproject.toml b/pyproject.toml index 63778286f..a14b383b3 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -24,7 +24,7 @@ lint.select = [ exclude = ["*.ipynb", "**/generated/*.pyi"] [tool.pylint] -master.py-version = "3.9" +master.py-version = "3.10" master.extension-pkg-allow-list = [ "pydantic", ]