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import torch |
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def compute_batch_accuracy(pred, label): |
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correct = (pred == label).sum() |
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return correct,label.size(0) |
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def compute_set_accuracy(model, test_loader): |
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu") |
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correct = 0 |
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total = 0 |
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with torch.no_grad(): |
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for data in test_loader: |
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inputs, labels = data |
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inputs = inputs.to(device) |
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labels = labels.to(device) |
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outputs = model(inputs) |
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correct_batch, total_batch = compute_batch_accuracy(torch.argmax(outputs, dim=1), labels) |
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correct += correct_batch |
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total += total_batch |
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return correct/total |
