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import torch | |
def configure_compute_backend(): | |
"""Configure PyTorch compute backend settings for CUDA.""" | |
if torch.cuda.is_available(): | |
torch.backends.cuda.matmul.allow_tf32 = True | |
torch.backends.cudnn.allow_tf32 = True | |
torch.backends.cudnn.benchmark = True | |
torch.backends.cudnn.deterministic = False | |
else: | |
raise ValueError("No CUDA available") | |
def get_device(): | |
"""Get the device to use for training.""" | |
if torch.cuda.is_available(): | |
return torch.device("cuda") | |
else: | |
raise ValueError("No CUDA available") |