Merge branch 'master' into pysssss-model-db

This commit is contained in:
Jedrzej Kosinski
2025-08-11 14:09:21 -07:00
6 changed files with 10 additions and 11 deletions

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@@ -203,7 +203,7 @@ Put your VAE in: models/vae
### AMD GPUs (Linux only) ### AMD GPUs (Linux only)
AMD users can install rocm and pytorch with pip if you don't have it already installed, this is the command to install the stable version: AMD users can install rocm and pytorch with pip if you don't have it already installed, this is the command to install the stable version:
```pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.3``` ```pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.4```
This is the command to install the nightly with ROCm 6.4 which might have some performance improvements: This is the command to install the nightly with ROCm 6.4 which might have some performance improvements:
@@ -237,7 +237,7 @@ Additional discussion and help can be found [here](https://github.com/comfyanony
Nvidia users should install stable pytorch using this command: Nvidia users should install stable pytorch using this command:
```pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu128``` ```pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu129```
This is the command to install pytorch nightly instead which might have performance improvements. This is the command to install pytorch nightly instead which might have performance improvements.

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@@ -301,6 +301,7 @@ def model_lora_keys_unet(model, key_map={}):
key_map["{}".format(key_lora)] = k key_map["{}".format(key_lora)] = k
# Support transformer prefix format # Support transformer prefix format
key_map["transformer.{}".format(key_lora)] = k key_map["transformer.{}".format(key_lora)] = k
key_map["lycoris_{}".format(key_lora.replace(".", "_"))] = k #SimpleTuner lycoris format
return key_map return key_map

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@@ -321,9 +321,9 @@ try:
if torch_version_numeric >= (2, 7): # works on 2.6 but doesn't actually seem to improve much if torch_version_numeric >= (2, 7): # works on 2.6 but doesn't actually seem to improve much
if any((a in arch) for a in ["gfx90a", "gfx942", "gfx1100", "gfx1101", "gfx1151"]): # TODO: more arches, TODO: gfx950 if any((a in arch) for a in ["gfx90a", "gfx942", "gfx1100", "gfx1101", "gfx1151"]): # TODO: more arches, TODO: gfx950
ENABLE_PYTORCH_ATTENTION = True ENABLE_PYTORCH_ATTENTION = True
if torch_version_numeric >= (2, 8): # if torch_version_numeric >= (2, 8):
if any((a in arch) for a in ["gfx1201"]): # if any((a in arch) for a in ["gfx1201"]):
ENABLE_PYTORCH_ATTENTION = True # ENABLE_PYTORCH_ATTENTION = True
if torch_version_numeric >= (2, 7) and rocm_version >= (6, 4): if torch_version_numeric >= (2, 7) and rocm_version >= (6, 4):
if any((a in arch) for a in ["gfx1201", "gfx942", "gfx950"]): # TODO: more arches if any((a in arch) for a in ["gfx1201", "gfx942", "gfx950"]): # TODO: more arches
SUPPORT_FP8_OPS = True SUPPORT_FP8_OPS = True
@@ -340,7 +340,7 @@ if ENABLE_PYTORCH_ATTENTION:
PRIORITIZE_FP16 = False # TODO: remove and replace with something that shows exactly which dtype is faster than the other PRIORITIZE_FP16 = False # TODO: remove and replace with something that shows exactly which dtype is faster than the other
try: try:
if is_nvidia() and PerformanceFeature.Fp16Accumulation in args.fast: if (is_nvidia() or is_amd()) and PerformanceFeature.Fp16Accumulation in args.fast:
torch.backends.cuda.matmul.allow_fp16_accumulation = True torch.backends.cuda.matmul.allow_fp16_accumulation = True
PRIORITIZE_FP16 = True # TODO: limit to cards where it actually boosts performance PRIORITIZE_FP16 = True # TODO: limit to cards where it actually boosts performance
logging.info("Enabled fp16 accumulation.") logging.info("Enabled fp16 accumulation.")

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@@ -646,8 +646,6 @@ class PromptExecutor:
self.add_message("execution_error", mes, broadcast=False) self.add_message("execution_error", mes, broadcast=False)
def execute(self, prompt, prompt_id, extra_data={}, execute_outputs=[]): def execute(self, prompt, prompt_id, extra_data={}, execute_outputs=[]):
asyncio_loop = asyncio.new_event_loop()
asyncio.set_event_loop(asyncio_loop)
asyncio.run(self.execute_async(prompt, prompt_id, extra_data, execute_outputs)) asyncio.run(self.execute_async(prompt, prompt_id, extra_data, execute_outputs))
async def execute_async(self, prompt, prompt_id, extra_data={}, execute_outputs=[]): async def execute_async(self, prompt, prompt_id, extra_data={}, execute_outputs=[]):

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@@ -1,6 +1,6 @@
comfyui-frontend-package==1.24.4 comfyui-frontend-package==1.24.4
comfyui-workflow-templates==0.1.52 comfyui-workflow-templates==0.1.53
comfyui-embedded-docs==0.2.4 comfyui-embedded-docs==0.2.6
torch torch
torchsde torchsde
torchvision torchvision

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@@ -235,7 +235,7 @@ class PromptServer():
sid, sid,
) )
logging.info( logging.debug(
f"Feature flags negotiated for client {sid}: {client_flags}" f"Feature flags negotiated for client {sid}: {client_flags}"
) )
first_message = False first_message = False