Fix some fp8 scaled checkpoints no longer working.

.github/workflows/release-stable-all.yml

@@ -20,12 +20,29 @@ jobs:
       git_tag: ${{ inputs.git_tag }}
       cache_tag: "cu130"
       python_minor: "13"
-      python_patch: "12"
+      python_patch: "11"
       rel_name: "nvidia"
       rel_extra_name: ""
       test_release: true
     secrets: inherit
 
+  release_nvidia_cu128:
+    permissions:
+      contents: "write"
+      packages: "write"
+      pull-requests: "read"
+    name: "Release NVIDIA cu128"
+    uses: ./.github/workflows/stable-release.yml
+    with:
+      git_tag: ${{ inputs.git_tag }}
+      cache_tag: "cu128"
+      python_minor: "12"
+      python_patch: "10"
+      rel_name: "nvidia"
+      rel_extra_name: "_cu128"
+      test_release: true
+    secrets: inherit
+
   release_nvidia_cu126:
     permissions:
       contents: "write"
@@ -59,20 +76,3 @@ jobs:
       rel_extra_name: ""
       test_release: false
     secrets: inherit
-
-  release_xpu:
-    permissions:
-      contents: "write"
-      packages: "write"
-      pull-requests: "read"
-    name: "Release Intel XPU"
-    uses: ./.github/workflows/stable-release.yml
-    with:
-      git_tag: ${{ inputs.git_tag }}
-      cache_tag: "xpu"
-      python_minor: "13"
-      python_patch: "12"
-      rel_name: "intel"
-      rel_extra_name: ""
-      test_release: true
-    secrets: inherit

README.md

@@ -137,7 +137,7 @@ ComfyUI follows a weekly release cycle targeting Monday but this regularly chang
    - Builds a new release using the latest stable core version
 
 3. **[ComfyUI Frontend](https://github.com/Comfy-Org/ComfyUI_frontend)**
-   - Every 2+ weeks frontend updates are merged into the core repository
+   - Weekly frontend updates are merged into the core repository
    - Features are frozen for the upcoming core release
    - Development continues for the next release cycle
 
@@ -276,7 +276,7 @@ Nvidia users should install stable pytorch using this command:
 
 This is the command to install pytorch nightly instead which might have performance improvements.
 
-```pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu132```
+```pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu130```
 
 #### Troubleshooting
 

comfy/ldm/modules/encoders/noise_aug_modules.py

@@ -3,9 +3,12 @@ from ..diffusionmodules.openaimodel import Timestep
 import torch
 
 class CLIPEmbeddingNoiseAugmentation(ImageConcatWithNoiseAugmentation):
-    def __init__(self, *args, timestep_dim=256, **kwargs):
+    def __init__(self, *args, clip_stats_path=None, timestep_dim=256, **kwargs):
         super().__init__(*args, **kwargs)
-        clip_mean, clip_std = torch.zeros(timestep_dim), torch.ones(timestep_dim)
+        if clip_stats_path is None:
+            clip_mean, clip_std = torch.zeros(timestep_dim), torch.ones(timestep_dim)
+        else:
+            clip_mean, clip_std = torch.load(clip_stats_path, map_location="cpu")
         self.register_buffer("data_mean", clip_mean[None, :], persistent=False)
         self.register_buffer("data_std", clip_std[None, :], persistent=False)
         self.time_embed = Timestep(timestep_dim)

comfy_api_nodes/apis/wan.py

@@ -1,226 +0,0 @@
-from pydantic import BaseModel, Field
-
-
-class Text2ImageInputField(BaseModel):
-    prompt: str = Field(...)
-    negative_prompt: str | None = Field(None)
-
-
-class Image2ImageInputField(BaseModel):
-    prompt: str = Field(...)
-    negative_prompt: str | None = Field(None)
-    images: list[str] = Field(..., min_length=1, max_length=2)
-
-
-class Text2VideoInputField(BaseModel):
-    prompt: str = Field(...)
-    negative_prompt: str | None = Field(None)
-    audio_url: str | None = Field(None)
-
-
-class Image2VideoInputField(BaseModel):
-    prompt: str = Field(...)
-    negative_prompt: str | None = Field(None)
-    img_url: str = Field(...)
-    audio_url: str | None = Field(None)
-
-
-class Reference2VideoInputField(BaseModel):
-    prompt: str = Field(...)
-    negative_prompt: str | None = Field(None)
-    reference_video_urls: list[str] = Field(...)
-
-
-class Txt2ImageParametersField(BaseModel):
-    size: str = Field(...)
-    n: int = Field(1, description="Number of images to generate.")  # we support only value=1
-    seed: int = Field(..., ge=0, le=2147483647)
-    prompt_extend: bool = Field(True)
-    watermark: bool = Field(False)
-
-
-class Image2ImageParametersField(BaseModel):
-    size: str | None = Field(None)
-    n: int = Field(1, description="Number of images to generate.")  # we support only value=1
-    seed: int = Field(..., ge=0, le=2147483647)
-    watermark: bool = Field(False)
-
-
-class Text2VideoParametersField(BaseModel):
-    size: str = Field(...)
-    seed: int = Field(..., ge=0, le=2147483647)
-    duration: int = Field(5, ge=5, le=15)
-    prompt_extend: bool = Field(True)
-    watermark: bool = Field(False)
-    audio: bool = Field(False, description="Whether to generate audio automatically.")
-    shot_type: str = Field("single")
-
-
-class Image2VideoParametersField(BaseModel):
-    resolution: str = Field(...)
-    seed: int = Field(..., ge=0, le=2147483647)
-    duration: int = Field(5, ge=5, le=15)
-    prompt_extend: bool = Field(True)
-    watermark: bool = Field(False)
-    audio: bool = Field(False, description="Whether to generate audio automatically.")
-    shot_type: str = Field("single")
-
-
-class Reference2VideoParametersField(BaseModel):
-    size: str = Field(...)
-    duration: int = Field(5, ge=5, le=15)
-    shot_type: str = Field("single")
-    seed: int = Field(..., ge=0, le=2147483647)
-    watermark: bool = Field(False)
-
-
-class Text2ImageTaskCreationRequest(BaseModel):
-    model: str = Field(...)
-    input: Text2ImageInputField = Field(...)
-    parameters: Txt2ImageParametersField = Field(...)
-
-
-class Image2ImageTaskCreationRequest(BaseModel):
-    model: str = Field(...)
-    input: Image2ImageInputField = Field(...)
-    parameters: Image2ImageParametersField = Field(...)
-
-
-class Text2VideoTaskCreationRequest(BaseModel):
-    model: str = Field(...)
-    input: Text2VideoInputField = Field(...)
-    parameters: Text2VideoParametersField = Field(...)
-
-
-class Image2VideoTaskCreationRequest(BaseModel):
-    model: str = Field(...)
-    input: Image2VideoInputField = Field(...)
-    parameters: Image2VideoParametersField = Field(...)
-
-
-class Reference2VideoTaskCreationRequest(BaseModel):
-    model: str = Field(...)
-    input: Reference2VideoInputField = Field(...)
-    parameters: Reference2VideoParametersField = Field(...)
-
-
-class Wan27MediaItem(BaseModel):
-    type: str = Field(...)
-    url: str = Field(...)
-
-
-class Wan27ReferenceVideoInputField(BaseModel):
-    prompt: str = Field(...)
-    negative_prompt: str | None = Field(None)
-    media: list[Wan27MediaItem] = Field(...)
-
-
-class Wan27ReferenceVideoParametersField(BaseModel):
-    resolution: str = Field(...)
-    ratio: str | None = Field(None)
-    duration: int = Field(5, ge=2, le=10)
-    watermark: bool = Field(False)
-    seed: int = Field(..., ge=0, le=2147483647)
-
-
-class Wan27ReferenceVideoTaskCreationRequest(BaseModel):
-    model: str = Field(...)
-    input: Wan27ReferenceVideoInputField = Field(...)
-    parameters: Wan27ReferenceVideoParametersField = Field(...)
-
-
-class Wan27ImageToVideoInputField(BaseModel):
-    prompt: str | None = Field(None)
-    negative_prompt: str | None = Field(None)
-    media: list[Wan27MediaItem] = Field(...)
-
-
-class Wan27ImageToVideoParametersField(BaseModel):
-    resolution: str = Field(...)
-    duration: int = Field(5, ge=2, le=15)
-    prompt_extend: bool = Field(True)
-    watermark: bool = Field(False)
-    seed: int = Field(..., ge=0, le=2147483647)
-
-
-class Wan27ImageToVideoTaskCreationRequest(BaseModel):
-    model: str = Field(...)
-    input: Wan27ImageToVideoInputField = Field(...)
-    parameters: Wan27ImageToVideoParametersField = Field(...)
-
-
-class Wan27VideoEditInputField(BaseModel):
-    prompt: str = Field(...)
-    media: list[Wan27MediaItem] = Field(...)
-
-
-class Wan27VideoEditParametersField(BaseModel):
-    resolution: str = Field(...)
-    ratio: str | None = Field(None)
-    duration: int = Field(0)
-    audio_setting: str = Field("auto")
-    watermark: bool = Field(False)
-    seed: int = Field(..., ge=0, le=2147483647)
-
-
-class Wan27VideoEditTaskCreationRequest(BaseModel):
-    model: str = Field(...)
-    input: Wan27VideoEditInputField = Field(...)
-    parameters: Wan27VideoEditParametersField = Field(...)
-
-
-class Wan27Text2VideoParametersField(BaseModel):
-    resolution: str = Field(...)
-    ratio: str | None = Field(None)
-    duration: int = Field(5, ge=2, le=15)
-    prompt_extend: bool = Field(True)
-    watermark: bool = Field(False)
-    seed: int = Field(..., ge=0, le=2147483647)
-
-
-class Wan27Text2VideoTaskCreationRequest(BaseModel):
-    model: str = Field(...)
-    input: Text2VideoInputField = Field(...)
-    parameters: Wan27Text2VideoParametersField = Field(...)
-
-
-class TaskCreationOutputField(BaseModel):
-    task_id: str = Field(...)
-    task_status: str = Field(...)
-
-
-class TaskCreationResponse(BaseModel):
-    output: TaskCreationOutputField | None = Field(None)
-    request_id: str = Field(...)
-    code: str | None = Field(None, description="Error code for the failed request.")
-    message: str | None = Field(None, description="Details about the failed request.")
-
-
-class TaskResult(BaseModel):
-    url: str | None = Field(None)
-    code: str | None = Field(None)
-    message: str | None = Field(None)
-
-
-class ImageTaskStatusOutputField(TaskCreationOutputField):
-    task_id: str = Field(...)
-    task_status: str = Field(...)
-    results: list[TaskResult] | None = Field(None)
-
-
-class VideoTaskStatusOutputField(TaskCreationOutputField):
-    task_id: str = Field(...)
-    task_status: str = Field(...)
-    video_url: str | None = Field(None)
-    code: str | None = Field(None)
-    message: str | None = Field(None)
-
-
-class ImageTaskStatusResponse(BaseModel):
-    output: ImageTaskStatusOutputField | None = Field(None)
-    request_id: str = Field(...)
-
-
-class VideoTaskStatusResponse(BaseModel):
-    output: VideoTaskStatusOutputField | None = Field(None)
-    request_id: str = Field(...)

comfy_extras/nodes_ace.py

@@ -80,7 +80,7 @@ class EmptyAceStepLatentAudio(io.ComfyNode):
     @classmethod
     def execute(cls, seconds, batch_size) -> io.NodeOutput:
         length = int(seconds * 44100 / 512 / 8)
-        latent = torch.zeros([batch_size, 8, 16, length], device=comfy.model_management.intermediate_device(), dtype=comfy.model_management.intermediate_dtype())
+        latent = torch.zeros([batch_size, 8, 16, length], device=comfy.model_management.intermediate_device())
         return io.NodeOutput({"samples": latent, "type": "audio"})
 
 
@@ -103,7 +103,7 @@ class EmptyAceStep15LatentAudio(io.ComfyNode):
     @classmethod
     def execute(cls, seconds, batch_size) -> io.NodeOutput:
         length = round((seconds * 48000 / 1920))
-        latent = torch.zeros([batch_size, 64, length], device=comfy.model_management.intermediate_device(), dtype=comfy.model_management.intermediate_dtype())
+        latent = torch.zeros([batch_size, 64, length], device=comfy.model_management.intermediate_device())
         return io.NodeOutput({"samples": latent, "type": "audio"})
 
 class ReferenceAudio(io.ComfyNode):

comfy_extras/nodes_curve.py

@@ -1,7 +1,5 @@
 from __future__ import annotations
 
-import numpy as np
-
 from comfy_api.latest import ComfyExtension, io
 from comfy_api.input import CurveInput
 from typing_extensions import override
@@ -34,58 +32,10 @@ class CurveEditor(io.ComfyNode):
         return io.NodeOutput(result, ui=ui) if ui else io.NodeOutput(result)
 
 
-class ImageHistogram(io.ComfyNode):
-    @classmethod
-    def define_schema(cls):
-        return io.Schema(
-            node_id="ImageHistogram",
-            display_name="Image Histogram",
-            category="utils",
-            inputs=[
-                io.Image.Input("image"),
-            ],
-            outputs=[
-                io.Histogram.Output("rgb"),
-                io.Histogram.Output("luminance"),
-                io.Histogram.Output("red"),
-                io.Histogram.Output("green"),
-                io.Histogram.Output("blue"),
-            ],
-        )
-
-    @classmethod
-    def execute(cls, image) -> io.NodeOutput:
-        img = image[0].cpu().numpy()
-        img_uint8 = np.clip(img * 255, 0, 255).astype(np.uint8)
-
-        def bincount(data):
-            return np.bincount(data.ravel(), minlength=256)[:256]
-
-        hist_r = bincount(img_uint8[:, :, 0])
-        hist_g = bincount(img_uint8[:, :, 1])
-        hist_b = bincount(img_uint8[:, :, 2])
-
-        # Average of R, G, B histograms (same as Photoshop's RGB composite)
-        rgb = ((hist_r + hist_g + hist_b) // 3).tolist()
-
-        # ITU-R BT.709-6, Item 3.2 (p.6) — Derivation of luminance signal
-        # https://www.itu.int/rec/R-REC-BT.709-6-201506-I/en
-        lum = 0.2126 * img[:, :, 0] + 0.7152 * img[:, :, 1] + 0.0722 * img[:, :, 2]
-        luminance = bincount(np.clip(lum * 255, 0, 255).astype(np.uint8)).tolist()
-
-        return io.NodeOutput(
-            rgb,
-            luminance,
-            hist_r.tolist(),
-            hist_g.tolist(),
-            hist_b.tolist(),
-        )
-
-
 class CurveExtension(ComfyExtension):
     @override
     async def get_node_list(self):
-        return [CurveEditor, ImageHistogram]
+        return [CurveEditor]
 
 
 async def comfy_entrypoint():

requirements.txt

@@ -1,5 +1,5 @@
 comfyui-frontend-package==1.42.8
-comfyui-workflow-templates==0.9.44
+comfyui-workflow-templates==0.9.39
 comfyui-embedded-docs==0.4.3
 torch
 torchsde

server.py

@@ -146,10 +146,6 @@ def is_loopback(host):
 def create_origin_only_middleware():
     @web.middleware
     async def origin_only_middleware(request: web.Request, handler):
-        if 'Sec-Fetch-Site' in request.headers:
-            sec_fetch_site = request.headers['Sec-Fetch-Site']
-            if sec_fetch_site == 'cross-site':
-                return web.Response(status=403)
         #this code is used to prevent the case where a random website can queue comfy workflows by making a POST to 127.0.0.1 which browsers don't prevent for some dumb reason.
         #in that case the Host and Origin hostnames won't match
         #I know the proper fix would be to add a cookie but this should take care of the problem in the meantime