Merge 6cdd246966 into 09725967cf

* Update amd portable for rocm 7.2

* Update Python patch version in release workflow

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

@@ -20,7 +20,7 @@ jobs:
       git_tag: ${{ inputs.git_tag }}
       cache_tag: "cu130"
       python_minor: "13"
-      python_patch: "9"
+      python_patch: "11"
       rel_name: "nvidia"
       rel_extra_name: ""
       test_release: true
@@ -65,11 +65,11 @@ jobs:
       contents: "write"
       packages: "write"
       pull-requests: "read"
-    name: "Release AMD ROCm 7.1.1"
+    name: "Release AMD ROCm 7.2"
     uses: ./.github/workflows/stable-release.yml
     with:
       git_tag: ${{ inputs.git_tag }}
-      cache_tag: "rocm711"
+      cache_tag: "rocm72"
       python_minor: "12"
       python_patch: "10"
       rel_name: "amd"

comfy/ldm/wan/vae.py

@@ -479,10 +479,12 @@ class WanVAE(nn.Module):
 
     def encode(self, x):
         conv_idx = [0]
-        feat_map = [None] * count_conv3d(self.decoder)
         ## cache
         t = x.shape[2]
         iter_ = 1 + (t - 1) // 4
+        feat_map = None
+        if iter_ > 1:
+            feat_map = [None] * count_conv3d(self.decoder)
         ## 对encode输入的x，按时间拆分为1、4、4、4....
         for i in range(iter_):
             conv_idx = [0]
@@ -502,10 +504,11 @@ class WanVAE(nn.Module):
 
     def decode(self, z):
         conv_idx = [0]
-        feat_map = [None] * count_conv3d(self.decoder)
         # z: [b,c,t,h,w]
-
         iter_ = z.shape[2]
+        feat_map = None
+        if iter_ > 1:
+            feat_map = [None] * count_conv3d(self.decoder)
         x = self.conv2(z)
         for i in range(iter_):
             conv_idx = [0]

comfy_api/latest/_io.py

@@ -1146,6 +1146,25 @@ class ImageCompare(ComfyTypeI):
       def as_dict(self):
           return super().as_dict()
 
+@comfytype(io_type="BOUNDING_BOX")
+class BoundingBox(ComfyTypeIO):
+    Type = dict
+
+    class Input(WidgetInput):
+        def __init__(self, id: str, display_name: str=None, optional=False, tooltip: str=None,
+                     socketless: bool=True, default: dict=None, component: str=None):
+            super().__init__(id, display_name, optional, tooltip, None, default, socketless)
+            self.component = component
+            if default is None:
+                self.default = {"x": 0, "y": 0, "width": 512, "height": 512}
+
+        def as_dict(self):
+            d = super().as_dict()
+            if self.component:
+                d["component"] = self.component
+            return d
+
+
 DYNAMIC_INPUT_LOOKUP: dict[str, Callable[[dict[str, Any], dict[str, Any], tuple[str, dict[str, Any]], str, list[str] | None], None]] = {}
 def register_dynamic_input_func(io_type: str, func: Callable[[dict[str, Any], dict[str, Any], tuple[str, dict[str, Any]], str, list[str] | None], None]):
     DYNAMIC_INPUT_LOOKUP[io_type] = func
@@ -2101,4 +2120,5 @@ __all__ = [
     "ImageCompare",
     "PriceBadgeDepends",
     "PriceBadge",
+    "BoundingBox",
 ]

comfy_extras/nodes_custom_sampler.py

@@ -701,7 +701,14 @@ class Noise_EmptyNoise:
 
     def generate_noise(self, input_latent):
         latent_image = input_latent["samples"]
-        return torch.zeros(latent_image.shape, dtype=latent_image.dtype, layout=latent_image.layout, device="cpu")
+        if latent_image.is_nested:
+            tensors = latent_image.unbind()
+            zeros = []
+            for t in tensors:
+                zeros.append(torch.zeros(t.shape, dtype=t.dtype, layout=t.layout, device="cpu"))
+            return comfy.nested_tensor.NestedTensor(zeros)
+        else:
+            return torch.zeros(latent_image.shape, dtype=latent_image.dtype, layout=latent_image.layout, device="cpu")
 
 
 class Noise_RandomNoise:

comfy_extras/nodes_images.py

@@ -27,16 +27,18 @@ class ImageCrop(IO.ComfyNode):
             category="image/transform",
             inputs=[
                 IO.Image.Input("image"),
-                IO.Int.Input("width", default=512, min=1, max=nodes.MAX_RESOLUTION, step=1),
-                IO.Int.Input("height", default=512, min=1, max=nodes.MAX_RESOLUTION, step=1),
-                IO.Int.Input("x", default=0, min=0, max=nodes.MAX_RESOLUTION, step=1),
-                IO.Int.Input("y", default=0, min=0, max=nodes.MAX_RESOLUTION, step=1),
+                IO.BoundingBox.Input("crop_region", component="ImageCrop"),
             ],
             outputs=[IO.Image.Output()],
         )
 
     @classmethod
-    def execute(cls, image, width, height, x, y) -> IO.NodeOutput:
+    def execute(cls, image, crop_region) -> IO.NodeOutput:
+        x = crop_region.get("x", 0)
+        y = crop_region.get("y", 0)
+        width = crop_region.get("width", 512)
+        height = crop_region.get("height", 512)
+
         x = min(x, image.shape[2] - 1)
         y = min(y, image.shape[1] - 1)
         to_x = width + x
@@ -47,6 +49,27 @@ class ImageCrop(IO.ComfyNode):
     crop = execute  # TODO: remove
 
 
+class BoundingBox(IO.ComfyNode):
+    @classmethod
+    def define_schema(cls):
+        return IO.Schema(
+            node_id="PrimitiveBoundingBox",
+            display_name="Bounding Box",
+            category="utils/primitive",
+            inputs=[
+                IO.Int.Input("x", default=0, min=0, max=MAX_RESOLUTION),
+                IO.Int.Input("y", default=0, min=0, max=MAX_RESOLUTION),
+                IO.Int.Input("width", default=512, min=1, max=MAX_RESOLUTION),
+                IO.Int.Input("height", default=512, min=1, max=MAX_RESOLUTION),
+            ],
+            outputs=[IO.BoundingBox.Output()],
+        )
+
+    @classmethod
+    def execute(cls, x, y, width, height) -> IO.NodeOutput:
+        return IO.NodeOutput({"x": x, "y": y, "width": width, "height": height})
+
+
 class RepeatImageBatch(IO.ComfyNode):
     @classmethod
     def define_schema(cls):
@@ -632,6 +655,7 @@ class ImagesExtension(ComfyExtension):
     async def get_node_list(self) -> list[type[IO.ComfyNode]]:
         return [
             ImageCrop,
+            BoundingBox,
             RepeatImageBatch,
             ImageFromBatch,
             ImageAddNoise,

comfyui_version.py

@@ -1,3 +1,3 @@
 # This file is automatically generated by the build process when version is
 # updated in pyproject.toml.
-__version__ = "0.10.0"
+__version__ = "0.11.0"

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "ComfyUI"
-version = "0.10.0"
+version = "0.11.0"
 readme = "README.md"
 license = { file = "LICENSE" }
 requires-python = ">=3.10"

requirements.txt

@@ -1,5 +1,5 @@
 comfyui-frontend-package==1.37.11
-comfyui-workflow-templates==0.8.15
+comfyui-workflow-templates==0.8.24
 comfyui-embedded-docs==0.4.0
 torch
 torchsde