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Support third-party backend for Timm #2102

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Support third-party backend for Timm #2102

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7333040
Support third-party backend for timm
Tyx-main Feb 27, 2024
8df1610
add variable 'is_npu' for third-party branch
Tyx-main Feb 27, 2024
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9 changes: 8 additions & 1 deletion timm/data/loader.py
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Original file line number Diff line number Diff line change
Expand Up @@ -114,12 +114,16 @@ def __init__(
else:
self.random_erasing = None
self.is_cuda = torch.cuda.is_available() and device.type == 'cuda'
self.is_npu = torch.npu.is_available() and device.type == 'npu'

def __iter__(self):
first = True
if self.is_cuda:
stream = torch.cuda.Stream()
stream_context = partial(torch.cuda.stream, stream=stream)
elif self.is_npu:
stream = torch.npu.Stream()
stream_context = partial(torch.npu.stream, stream=stream)
else:
stream = None
stream_context = suppress
Expand All @@ -139,7 +143,10 @@ def __iter__(self):
first = False

if stream is not None:
torch.cuda.current_stream().wait_stream(stream)
if self.is_cuda:
torch.cuda.current_stream().wait_stream(stream)
elif self.is_npu:
torch.npu.current_stream().wait_stream(stream)

input = next_input
target = next_target
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4 changes: 4 additions & 0 deletions timm/utils/distributed.py
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Expand Up @@ -152,6 +152,8 @@ def init_distributed_device_so(

if 'cuda' in device:
assert torch.cuda.is_available(), f'CUDA is not available but {device} was specified.'
elif 'npu' in device:
assert torch.npu.is_available(), f'NPU is not available but {device} was specified.'

if distributed and device != 'cpu':
device, *device_idx = device.split(':', maxsplit=1)
Expand All @@ -165,6 +167,8 @@ def init_distributed_device_so(

if device.startswith('cuda:'):
torch.cuda.set_device(device)
elif device.startswith('npu:'):
torch.npu.set_device(device)

return dict(
device=device,
Expand Down
4 changes: 4 additions & 0 deletions train.py
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Expand Up @@ -1054,6 +1054,8 @@ def _backward(_loss):

if args.synchronize_step and device.type == 'cuda':
torch.cuda.synchronize()
elif args.synchronize_step and device.type == 'npu':
torch.npu.synchronize()
time_now = time.time()
update_time_m.update(time.time() - update_start_time)
update_start_time = time_now
Expand Down Expand Up @@ -1153,6 +1155,8 @@ def validate(

if device.type == 'cuda':
torch.cuda.synchronize()
elif device.type == 'npu':
torch.npu.synchronize()

losses_m.update(reduced_loss.item(), input.size(0))
top1_m.update(acc1.item(), output.size(0))
Expand Down