[pull] master from comfyanonymous:master

.ci/update_windows/update.py

@@ -53,6 +53,16 @@ def pull(repo, remote_name='origin', branch='master'):
     repo.stash(ident)
 except KeyError:
     print("nothing to stash")  # noqa: T201
+except:
+    print("Could not stash, cleaning index and trying again.")  # noqa: T201
+    repo.state_cleanup()
+    repo.index.read_tree(repo.head.peel().tree)
+    repo.index.write()
+    try:
+        repo.stash(ident)
+    except KeyError:
+        print("nothing to stash.")  # noqa: T201
+
 backup_branch_name = 'backup_branch_{}'.format(datetime.today().strftime('%Y-%m-%d_%H_%M_%S'))
 print("creating backup branch: {}".format(backup_branch_name))  # noqa: T201
 try:

comfy/supported_models.py

@@ -965,7 +965,7 @@ class CosmosT2IPredict2(supported_models_base.BASE):
 
     def __init__(self, unet_config):
         super().__init__(unet_config)
-        self.memory_usage_factor = (unet_config.get("model_channels", 2048) / 2048) * 0.9
+        self.memory_usage_factor = (unet_config.get("model_channels", 2048) / 2048) * 0.95
 
     def get_model(self, state_dict, prefix="", device=None):
         out = model_base.CosmosPredict2(self, device=device)
@@ -1289,7 +1289,7 @@ class ChromaRadiance(Chroma):
     latent_format = comfy.latent_formats.ChromaRadiance
 
     # Pixel-space model, no spatial compression for model input.
-    memory_usage_factor = 0.038
+    memory_usage_factor = 0.044
 
     def get_model(self, state_dict, prefix="", device=None):
         return model_base.ChromaRadiance(self, device=device)
@@ -1332,7 +1332,7 @@ class Omnigen2(supported_models_base.BASE):
         "shift": 2.6,
     }
 
-    memory_usage_factor = 1.65 #TODO
+    memory_usage_factor = 1.95 #TODO
 
     unet_extra_config = {}
     latent_format = latent_formats.Flux
@@ -1397,7 +1397,7 @@ class HunyuanImage21(HunyuanVideo):
 
     latent_format = latent_formats.HunyuanImage21
 
-    memory_usage_factor = 7.7
+    memory_usage_factor = 8.7
 
     supported_inference_dtypes = [torch.bfloat16, torch.float32]
 
@@ -1488,7 +1488,7 @@ class Kandinsky5(supported_models_base.BASE):
     unet_extra_config = {}
     latent_format = latent_formats.HunyuanVideo
 
-    memory_usage_factor = 1.1 #TODO
+    memory_usage_factor = 1.25 #TODO
 
     supported_inference_dtypes = [torch.bfloat16, torch.float32]
 
@@ -1517,7 +1517,7 @@ class Kandinsky5Image(Kandinsky5):
     }
 
     latent_format = latent_formats.Flux
-    memory_usage_factor = 1.1 #TODO
+    memory_usage_factor = 1.25 #TODO
 
     def get_model(self, state_dict, prefix="", device=None):
         out = model_base.Kandinsky5Image(self, device=device)

comfy_api/latest/_io.py

@@ -774,6 +774,13 @@ class AudioEncoder(ComfyTypeIO):
 class AudioEncoderOutput(ComfyTypeIO):
     Type = Any
 
+@comfytype(io_type="TRACKS")
+class Tracks(ComfyTypeIO):
+    class TrackDict(TypedDict):
+        track_path: torch.Tensor
+        track_visibility: torch.Tensor
+    Type = TrackDict
+
 @comfytype(io_type="COMFY_MULTITYPED_V3")
 class MultiType:
     Type = Any
@@ -1894,6 +1901,7 @@ def as_dict(self) -> dict:
     "SEGS",
     "AnyType",
     "MultiType",
+    "Tracks",
     # Dynamic Types
     "MatchType",
     # "DynamicCombo",