Improve docs of softmax_cross_entropy #3105
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Jenkins, test this please |
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@keisuke-umezawa Jenkins tests failed. Could you rebase it to the current master? |
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@mitmul I rebased this branch. |
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Sep 4, 2017
| @@ -223,17 +223,21 @@ def backward_gpu(self, inputs, grad_outputs): | |||
| def softmax_cross_entropy( | |||
| x, t, normalize=True, cache_score=True, class_weight=None, | |||
| ignore_label=-1, reduce='mean'): | |||
| """Computes cross entropy loss for pre-softmax activations. | |||
| """Computes cross entropy loss after softmax activations. | |||
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It seems that the previous sentence is better; in your sentence, it is a bit confusing that we should apply "softmax" functions before calling softmax_cross_entropy.
| >>> log_softmax = -F.log_softmax(x) | ||
| >>> expected_loss = np.mean([log_softmax[row, column].data \ | ||
| for row, column in enumerate(t)]) | ||
| >>> y.data == expected_loss |
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How about using y.array instead of y.data?
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ok. I used y.array
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@rezoo I fixed them! |
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Thank you. LGTM. |
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This is PR for improving docs of functions/links. Related issue: #2182
Modified functions/links: