Fix the API of bce loss and add functional API binary_cross_entropy #26012
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wawltor
reviewed
Aug 13, 2020
wawltor
reviewed
Aug 13, 2020
joey12300
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Aug 13, 2020
joey12300
reviewed
Aug 13, 2020
python/paddle/nn/layer/loss.py
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| print(output.numpy()) # [0.65537095] | ||
| paddle.enable_static() | ||
| # static mode |
Contributor
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No need to show static graph demo code.
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there exist static mode demo before. I think keep it will be batter
joey12300
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Aug 13, 2020
joey12300
reviewed
Aug 13, 2020
Contributor
describe记得修改 |
LutaoChu
reviewed
Aug 14, 2020
| Out = -1 * (label * log(input) + (1 - label) * log(1 - input)) | ||
| If :attr:`reduction` set to ``'none'``, the unreduced loss is: | ||
| If :attr:`reduction` set to ``'none'``, the interface will return the original loss `Out`. |
Contributor
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interface用法会不会有点奇怪，改为operation？
wawltor
reviewed
Aug 18, 2020
| batch element. If given, has to be a Tensor of size nbatch and the data type | ||
| is float32, float64. Default is ``'None'``. | ||
| reduction (str, optional): Indicate how to average the loss by batch_size, | ||
| the candicates are ``'none'`` | ``'mean'`` | ``'sum'``. |
ZHUI
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ZHUI
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TCChenlong
reviewed
Aug 21, 2020
| output = paddle.nn.functional.binary_cross_entropy(input, label) | ||
| print(output.numpy()) # [0.65537095] | ||
| paddle.enable_static() | ||
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fix the API of bce loss and add functional API binary_cross_entropy.