Fixing error accurate and error tensor to numpy
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@ -70,8 +70,8 @@ for epoch in range(EPOCH):
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# !!!!!!!! Change in here !!!!!!!!! #
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pred_y = torch.max(test_output, 1)[1].cuda().data.squeeze() # move the computation in GPU
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accuracy = torch.sum(pred_y == test_y) / test_y.size(0)
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print('Epoch: ', epoch, '| train loss: %.4f' % loss.data.numpy(), '| test accuracy: %.2f' % accuracy)
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accuracy = torch.sum(pred_y == test_y).type(torch.FloatTensor) / test_y.size(0)
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print('Epoch: ', epoch, '| train loss: %.4f' % loss.data.cpu().numpy(), '| test accuracy: %.2f' % accuracy)
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test_output = cnn(test_x[:10])
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