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@@ -33,7 +33,7 @@ def train_one_epoch(model, optimizer, data_loader, device, epoch, print_freq, sc
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targets = [{k: v.to(device) if isinstance(v, torch.Tensor) else v for k, v in t.items()} for t in targets]
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targets = [{k: v.to(device) if isinstance(v, torch.Tensor) else v for k, v in t.items()} for t in targets]
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with torch.cuda.amp.autocast(enabled=scaler is not None):
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with torch.cuda.amp.autocast(enabled=scaler is not None):
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loss_dict = model(images, targets)
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loss_dict = model(images, targets)
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- print(f'loss_dict:{loss_dict}')
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+ # print(f'loss_dict:{loss_dict}')
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losses = sum(loss for loss in loss_dict.values())
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losses = sum(loss for loss in loss_dict.values())
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# reduce losses over all GPUs for logging purposes
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# reduce losses over all GPUs for logging purposes
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