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Merge branch 'master' into dr-support-pip-cm
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@ -203,7 +203,7 @@ Put your VAE in: models/vae
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### AMD GPUs (Linux only)
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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:
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```pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.3```
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```pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.4```
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This is the command to install the nightly with ROCm 6.4 which might have some performance improvements:
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@ -237,7 +237,7 @@ Additional discussion and help can be found [here](https://github.com/comfyanony
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Nvidia users should install stable pytorch using this command:
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```pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu128```
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```pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu129```
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This is the command to install pytorch nightly instead which might have performance improvements.
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@ -340,7 +340,7 @@ if ENABLE_PYTORCH_ATTENTION:
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PRIORITIZE_FP16 = False # TODO: remove and replace with something that shows exactly which dtype is faster than the other
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try:
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if is_nvidia() and PerformanceFeature.Fp16Accumulation in args.fast:
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if (is_nvidia() or is_amd()) and PerformanceFeature.Fp16Accumulation in args.fast:
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torch.backends.cuda.matmul.allow_fp16_accumulation = True
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PRIORITIZE_FP16 = True # TODO: limit to cards where it actually boosts performance
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logging.info("Enabled fp16 accumulation.")
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