bump comfyui-frontend-package to 1.34.7

comfy/ldm/hunyuan_video/model.py

@@ -43,7 +43,6 @@ class HunyuanVideoParams:
     meanflow: bool
     use_cond_type_embedding: bool
     vision_in_dim: int
-    meanflow_sum: bool
 
 
 class SelfAttentionRef(nn.Module):
@@ -318,7 +317,7 @@ class HunyuanVideo(nn.Module):
                 timesteps_r = transformer_options['sample_sigmas'][w[0] + 1]
                 timesteps_r = timesteps_r.unsqueeze(0).to(device=timesteps.device, dtype=timesteps.dtype)
                 vec_r = self.time_r_in(timestep_embedding(timesteps_r, 256, time_factor=1000.0).to(img.dtype))
-                vec = (vec + vec_r) if self.params.meanflow_sum else (vec + vec_r) / 2
+                vec = (vec + vec_r) / 2
 
         if ref_latent is not None:
             ref_latent_ids = self.img_ids(ref_latent)

comfy/model_detection.py

@@ -180,10 +180,8 @@ def detect_unet_config(state_dict, key_prefix, metadata=None):
             dit_config["use_cond_type_embedding"] = False
         if '{}vision_in.proj.0.weight'.format(key_prefix) in state_dict_keys:
             dit_config["vision_in_dim"] = state_dict['{}vision_in.proj.0.weight'.format(key_prefix)].shape[0]
-            dit_config["meanflow_sum"] = True
         else:
             dit_config["vision_in_dim"] = None
-            dit_config["meanflow_sum"] = False
         return dit_config
 
     if '{}double_blocks.0.img_attn.norm.key_norm.scale'.format(key_prefix) in state_dict_keys and ('{}img_in.weight'.format(key_prefix) in state_dict_keys or f"{key_prefix}distilled_guidance_layer.norms.0.scale" in state_dict_keys): #Flux, Chroma or Chroma Radiance (has no img_in.weight)

comfy/ops.py

@@ -22,6 +22,7 @@ import comfy.model_management
 from comfy.cli_args import args, PerformanceFeature
 import comfy.float
 import comfy.rmsnorm
+import contextlib
 import json
 
 def run_every_op():
@@ -93,6 +94,13 @@ def cast_bias_weight(s, input=None, dtype=None, device=None, bias_dtype=None, of
     else:
         offload_stream = None
 
+    if offload_stream is not None:
+        wf_context = offload_stream
+        if hasattr(wf_context, "as_context"):
+            wf_context = wf_context.as_context(offload_stream)
+    else:
+        wf_context = contextlib.nullcontext()
+
     non_blocking = comfy.model_management.device_supports_non_blocking(device)
 
     weight_has_function = len(s.weight_function) > 0

comfy/quant_ops.py

@@ -399,10 +399,7 @@ class TensorCoreFP8Layout(QuantizedLayout):
         orig_dtype = tensor.dtype
 
         if isinstance(scale, str) and scale == "recalculate":
-            scale = torch.amax(tensor.abs()).to(dtype=torch.float32) / torch.finfo(dtype).max
-            if tensor.dtype not in [torch.float32, torch.bfloat16]:  # Prevent scale from being too small
-                tensor_info = torch.finfo(tensor.dtype)
-                scale = (1.0 / torch.clamp((1.0 / scale), min=tensor_info.min, max=tensor_info.max))
+            scale = torch.amax(tensor.abs()) / torch.finfo(dtype).max
 
         if scale is not None:
             if not isinstance(scale, torch.Tensor):

comfyui_version.py

@@ -1,3 +1,3 @@
 # This file is automatically generated by the build process when version is
 # updated in pyproject.toml.
-__version__ = "0.4.0"
+__version__ = "0.3.76"

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "ComfyUI"
-version = "0.4.0"
+version = "0.3.76"
 readme = "README.md"
 license = { file = "LICENSE" }
 requires-python = ">=3.9"

requirements.txt

@@ -1,4 +1,4 @@
-comfyui-frontend-package==1.33.13
+comfyui-frontend-package==1.34.7
 comfyui-workflow-templates==0.7.54
 comfyui-embedded-docs==0.3.1
 torch