Merge 7d493629a4 into b8f848bfe3

Separate integer primitive that does not contain randomizing function which will act as primary integer primitive and for integers with randomizing, a new primitive named RandInt instead. 

This will greatly reduce canvas clutter when using primitive integer for purposes like steps, resolution and other use cases that does not need randomization nor are related to seed.

Having the randomizing element always present also runs the risk of the user accidentally leaving node at random on a primitive that then passes that value to a node that causes server to hang because of it. Possibly even worse.

.github/workflows/windows_release_dependencies.yml

@@ -29,7 +29,7 @@ on:
         description: 'python patch version'
         required: true
         type: string
-        default: "9"
+        default: "11"
 #  push:
 #    branches:
 #      - master

comfy/ldm/cosmos/predict2.py

@@ -13,6 +13,7 @@ from torchvision import transforms
 
 import comfy.patcher_extension
 from comfy.ldm.modules.attention import optimized_attention
+import comfy.ldm.common_dit
 
 def apply_rotary_pos_emb(
     t: torch.Tensor,
@@ -835,6 +836,8 @@ class MiniTrainDIT(nn.Module):
         padding_mask: Optional[torch.Tensor] = None,
         **kwargs,
     ):
+        orig_shape = list(x.shape)
+        x = comfy.ldm.common_dit.pad_to_patch_size(x, (self.patch_temporal, self.patch_spatial, self.patch_spatial))
         x_B_C_T_H_W = x
         timesteps_B_T = timesteps
         crossattn_emb = context
@@ -882,5 +885,5 @@ class MiniTrainDIT(nn.Module):
             )
 
         x_B_T_H_W_O = self.final_layer(x_B_T_H_W_D, t_embedding_B_T_D, adaln_lora_B_T_3D=adaln_lora_B_T_3D)
-        x_B_C_Tt_Hp_Wp = self.unpatchify(x_B_T_H_W_O)
+        x_B_C_Tt_Hp_Wp = self.unpatchify(x_B_T_H_W_O)[:, :, :orig_shape[-3], :orig_shape[-2], :orig_shape[-1]]
         return x_B_C_Tt_Hp_Wp

comfy_extras/nodes_primitive.py

@@ -40,6 +40,24 @@ class StringMultiline(io.ComfyNode):
         return io.NodeOutput(value)
 
 
+class RandInt(io.ComfyNode):
+    @classmethod
+    def define_schema(cls):
+        return io.Schema(
+            node_id="PrimitiveRandomInt",
+            display_name="RandomInt",
+            category="utils/primitive",
+            inputs=[
+                io.Int.Input("value", min=-sys.maxsize, max=sys.maxsize, control_after_generate=True),
+            ],
+            outputs=[io.Int.Output()],
+        )
+
+    @classmethod
+    def execute(cls, value: int) -> io.NodeOutput:
+        return io.NodeOutput(value)
+
+
 class Int(io.ComfyNode):
     @classmethod
     def define_schema(cls):
@@ -48,7 +66,7 @@ class Int(io.ComfyNode):
             display_name="Int",
             category="utils/primitive",
             inputs=[
-                io.Int.Input("value", min=-sys.maxsize, max=sys.maxsize, control_after_generate=True),
+                io.Int.Input("value", min=-sys.maxsize, max=sys.maxsize),
             ],
             outputs=[io.Int.Output()],
         )
@@ -100,6 +118,7 @@ class PrimitivesExtension(ComfyExtension):
         return [
             String,
             StringMultiline,
+            RandInt,
             Int,
             Float,
             Boolean,