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change torch.cuda.amp.GradScaler to torch.GradScaler("cuda") #3257
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@@ -150,7 +150,7 @@ def make_model(in_size, out_size, num_layers): | |
| # The same ``GradScaler`` instance should be used for the entire convergence run. | ||
| # If you perform multiple convergence runs in the same script, each run should use | ||
| # a dedicated fresh ``GradScaler`` instance. ``GradScaler`` instances are lightweight. | ||
| scaler = torch.cuda.amp.GradScaler() | ||
| scaler = torch.GradScaler("cuda") | ||
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| for epoch in range(0): # 0 epochs, this section is for illustration only | ||
| for input, target in zip(data, targets): | ||
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@@ -182,7 +182,7 @@ def make_model(in_size, out_size, num_layers): | |
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| net = make_model(in_size, out_size, num_layers) | ||
| opt = torch.optim.SGD(net.parameters(), lr=0.001) | ||
| scaler = torch.cuda.amp.GradScaler(enabled=use_amp) | ||
| scaler = torch.GradScaler("cuda" ,enabled=use_amp) | ||
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| start_timer() | ||
| for epoch in range(epochs): | ||
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