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Allow TF32 in CUDA for increased performance #279
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@ -1,6 +1,8 @@
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import torch
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import torch
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# has_mps is only available in nightly pytorch (for now), `getattr` for compatibility
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# has_mps is only available in nightly pytorch (for now), `getattr` for compatibility
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from modules import errors
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has_mps = getattr(torch, 'has_mps', False)
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has_mps = getattr(torch, 'has_mps', False)
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cpu = torch.device("cpu")
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cpu = torch.device("cpu")
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@ -20,3 +22,12 @@ def torch_gc():
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if torch.cuda.is_available():
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if torch.cuda.is_available():
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torch.cuda.empty_cache()
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torch.cuda.empty_cache()
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torch.cuda.ipc_collect()
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torch.cuda.ipc_collect()
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def enable_tf32():
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if torch.cuda.is_available():
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torch.backends.cuda.matmul.allow_tf32 = True
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torch.backends.cudnn.allow_tf32 = True
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errors.run(enable_tf32, "Enabling TF32")
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10
modules/errors.py
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10
modules/errors.py
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@ -0,0 +1,10 @@
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import sys
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import traceback
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def run(code, task):
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try:
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code()
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except Exception as e:
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print(f"{task}: {type(e).__name__}", file=sys.stderr)
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print(traceback.format_exc(), file=sys.stderr)
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