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train.py - add with torch.no_grad():
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train.py
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train.py
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@ -191,6 +191,7 @@ def evaluate(model, criterion, data_loader, current_step):
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print(" | > Validation")
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progbar = Progbar(len(data_loader.dataset) / c.batch_size)
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n_priority_freq = int(3000 / (c.sample_rate * 0.5) * c.num_freq)
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with torch.no_grad():
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for num_iter, data in enumerate(data_loader):
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start_time = time.time()
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