INNER CODE UNIT · Python

softmax_scores_batch

haitongli/knowledge-distillation-pytorch · distillation_analysis.py:47

            softmax_scores_batch = F.softmax(output_batch/temperature, dim=1)
            softmax_scores_batch = softmax_scores_batch.data.cpu().numpy()
            softmax_scores.append(softmax_scores_batch)

            # extract data from torch Variable, move to cpu, convert to numpy arrays
            output_batch = output_batch.data.cpu().numpy()
            labels_batch = labels_batch.data.cpu().numpy()

            predict_correct_batch = (np.argmax(output_batch, axis=1) == labels_batch).astype(int)
            predict_correct.append(np.reshape(predict_correct_batch, (labels_batch.size, 1)))

            t.update()

    softmax_scores = np.vstack(softmax_scores)
    predict_correct = np.vstack(predict_correct)

    return softmax_scores, predict_correct, confusion_matrix.value().astype(int)

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