mirror of
https://git.datalinker.icu/comfyanonymous/ComfyUI
synced 2026-09-02 19:47:07 +08:00
Merge branch 'master' of github.com:comfyanonymous/ComfyUI into feat/linux-amd-setup
This commit is contained in:
commit
2530ec5ad1
40
.github/workflows/check-line-endings.yml
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40
.github/workflows/check-line-endings.yml
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@ -0,0 +1,40 @@
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name: Check for Windows Line Endings
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on:
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pull_request:
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branches: ['*'] # Trigger on all pull requests to any branch
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jobs:
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check-line-endings:
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runs-on: ubuntu-latest
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steps:
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- name: Checkout code
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uses: actions/checkout@v4
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with:
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fetch-depth: 0 # Fetch all history to compare changes
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- name: Check for Windows line endings (CRLF)
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run: |
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# Get the list of changed files in the PR
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CHANGED_FILES=$(git diff --name-only origin/${{ github.base_ref }}..HEAD)
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# Flag to track if CRLF is found
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CRLF_FOUND=false
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# Loop through each changed file
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for FILE in $CHANGED_FILES; do
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# Check if the file exists and is a text file
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if [ -f "$FILE" ] && file "$FILE" | grep -q "text"; then
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# Check for CRLF line endings
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if grep -UP '\r$' "$FILE"; then
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echo "Error: Windows line endings (CRLF) detected in $FILE"
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CRLF_FOUND=true
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fi
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fi
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done
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# Exit with error if CRLF was found
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if [ "$CRLF_FOUND" = true ]; then
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exit 1
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fi
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@ -144,6 +144,7 @@ class PerformanceFeature(enum.Enum):
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parser.add_argument("--fast", nargs="*", type=PerformanceFeature, help="Enable some untested and potentially quality deteriorating optimizations. --fast with no arguments enables everything. You can pass a list specific optimizations if you only want to enable specific ones. Current valid optimizations: fp16_accumulation fp8_matrix_mult cublas_ops")
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parser.add_argument("--mmap-torch-files", action="store_true", help="Use mmap when loading ckpt/pt files.")
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parser.add_argument("--disable-mmap", action="store_true", help="Don't use mmap when loading safetensors.")
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parser.add_argument("--dont-print-server", action="store_true", help="Don't print server output.")
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parser.add_argument("--quick-test-for-ci", action="store_true", help="Quick test for CI.")
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@ -1214,7 +1214,7 @@ class Omnigen2(supported_models_base.BASE):
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def clip_target(self, state_dict={}):
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pref = self.text_encoder_key_prefix[0]
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hunyuan_detect = comfy.text_encoders.hunyuan_video.llama_detect(state_dict, "{}qwen25_3b.transformer.".format(pref))
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return supported_models_base.ClipTarget(comfy.text_encoders.omnigen2.LuminaTokenizer, comfy.text_encoders.omnigen2.te(**hunyuan_detect))
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return supported_models_base.ClipTarget(comfy.text_encoders.omnigen2.Omnigen2Tokenizer, comfy.text_encoders.omnigen2.te(**hunyuan_detect))
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models = [LotusD, 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, PixArtAlpha, PixArtSigma, HunyuanDiT, HunyuanDiT1, FluxInpaint, Flux, FluxSchnell, GenmoMochi, LTXV, HunyuanVideoSkyreelsI2V, HunyuanVideoI2V, HunyuanVideo, CosmosT2V, CosmosI2V, CosmosT2IPredict2, CosmosI2VPredict2, Lumina2, WAN21_T2V, WAN21_I2V, WAN21_FunControl2V, WAN21_Vace, WAN21_Camera, Hunyuan3Dv2mini, Hunyuan3Dv2, HiDream, Chroma, ACEStep, Omnigen2]
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@ -31,6 +31,7 @@ from einops import rearrange
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from comfy.cli_args import args
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MMAP_TORCH_FILES = args.mmap_torch_files
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DISABLE_MMAP = args.disable_mmap
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ALWAYS_SAFE_LOAD = False
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if hasattr(torch.serialization, "add_safe_globals"): # TODO: this was added in pytorch 2.4, the unsafe path should be removed once earlier versions are deprecated
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@ -58,7 +59,10 @@ def load_torch_file(ckpt, safe_load=False, device=None, return_metadata=False):
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with safetensors.safe_open(ckpt, framework="pt", device=device.type) as f:
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sd = {}
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for k in f.keys():
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sd[k] = f.get_tensor(k)
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tensor = f.get_tensor(k)
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if DISABLE_MMAP: # TODO: Not sure if this is the best way to bypass the mmap issues
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tensor = tensor.to(device=device, copy=True)
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sd[k] = tensor
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if return_metadata:
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metadata = f.metadata()
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except Exception as e:
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@ -406,7 +406,7 @@ class GeminiInputFiles(ComfyNodeABC):
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def create_file_part(self, file_path: str) -> GeminiPart:
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mime_type = (
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GeminiMimeType.pdf
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GeminiMimeType.application_pdf
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if file_path.endswith(".pdf")
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else GeminiMimeType.text_plain
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)
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@ -247,7 +247,7 @@ class MaskComposite:
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visible_width, visible_height = (right - left, bottom - top,)
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source_portion = source[:, :visible_height, :visible_width]
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destination_portion = destination[:, top:bottom, left:right]
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destination_portion = output[:, top:bottom, left:right]
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if operation == "multiply":
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output[:, top:bottom, left:right] = destination_portion * source_portion
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@ -1,24 +1,24 @@
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from nodes import MAX_RESOLUTION
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class CLIPTextEncodePixArtAlpha:
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@classmethod
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def INPUT_TYPES(s):
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return {"required": {
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"width": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
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"height": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
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# "aspect_ratio": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}),
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"text": ("STRING", {"multiline": True, "dynamicPrompts": True}), "clip": ("CLIP", ),
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}}
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RETURN_TYPES = ("CONDITIONING",)
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FUNCTION = "encode"
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CATEGORY = "advanced/conditioning"
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DESCRIPTION = "Encodes text and sets the resolution conditioning for PixArt Alpha. Does not apply to PixArt Sigma."
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def encode(self, clip, width, height, text):
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tokens = clip.tokenize(text)
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return (clip.encode_from_tokens_scheduled(tokens, add_dict={"width": width, "height": height}),)
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NODE_CLASS_MAPPINGS = {
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"CLIPTextEncodePixArtAlpha": CLIPTextEncodePixArtAlpha,
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}
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from nodes import MAX_RESOLUTION
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class CLIPTextEncodePixArtAlpha:
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@classmethod
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def INPUT_TYPES(s):
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return {"required": {
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"width": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
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"height": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
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# "aspect_ratio": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}),
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"text": ("STRING", {"multiline": True, "dynamicPrompts": True}), "clip": ("CLIP", ),
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}}
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RETURN_TYPES = ("CONDITIONING",)
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FUNCTION = "encode"
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CATEGORY = "advanced/conditioning"
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DESCRIPTION = "Encodes text and sets the resolution conditioning for PixArt Alpha. Does not apply to PixArt Sigma."
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def encode(self, clip, width, height, text):
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tokens = clip.tokenize(text)
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return (clip.encode_from_tokens_scheduled(tokens, add_dict={"width": width, "height": height}),)
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NODE_CLASS_MAPPINGS = {
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"CLIPTextEncodePixArtAlpha": CLIPTextEncodePixArtAlpha,
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}
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@ -1,5 +1,5 @@
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comfyui-frontend-package==1.23.4
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comfyui-workflow-templates==0.1.35
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comfyui-workflow-templates==0.1.36
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comfyui-embedded-docs==0.2.4
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torch
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torchsde
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@ -10,11 +10,11 @@ import urllib.parse
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server_address = "127.0.0.1:8188"
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client_id = str(uuid.uuid4())
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def queue_prompt(prompt):
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p = {"prompt": prompt, "client_id": client_id}
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def queue_prompt(prompt, prompt_id):
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p = {"prompt": prompt, "client_id": client_id, "prompt_id": prompt_id}
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data = json.dumps(p).encode('utf-8')
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req = urllib.request.Request("http://{}/prompt".format(server_address), data=data)
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return json.loads(urllib.request.urlopen(req).read())
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req = urllib.request.Request("http://{}/prompt".format(server_address), data=data)
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urllib.request.urlopen(req).read()
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def get_image(filename, subfolder, folder_type):
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data = {"filename": filename, "subfolder": subfolder, "type": folder_type}
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@ -27,7 +27,8 @@ def get_history(prompt_id):
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return json.loads(response.read())
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def get_images(ws, prompt):
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prompt_id = queue_prompt(prompt)['prompt_id']
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prompt_id = str(uuid.uuid4())
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queue_prompt(prompt, prompt_id)
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output_images = {}
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while True:
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out = ws.recv()
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@ -678,7 +678,7 @@ class PromptServer():
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if "prompt" in json_data:
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prompt = json_data["prompt"]
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prompt_id = str(uuid.uuid4())
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prompt_id = str(json_data.get("prompt_id", uuid.uuid4()))
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valid = await execution.validate_prompt(prompt_id, prompt)
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extra_data = {}
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if "extra_data" in json_data:
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