Hackathon No.21 #4723
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Hackathon No.21 #4723
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Thanks for your contribution! |
TCChenlong
reviewed
May 30, 2022
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| .. _cn_api_paddle_nn_functional_soft_margin_losss: | |||
| soft_margin_loss | ||
| ------------------------------- | ||
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| .. py:function:: paddle.nn.functional.soft_margin_loss(input, label, weight:Optional=None, reduction: str = 'mean') |
| ::::::::: | ||
| - **input** (Tensor) - :math:`[N, *]` ，其中N是batch_size， `*` 是任意其他维度。数据类型是float32、float64。 | ||
| - **label** (Tensor) - :math:`[N, *]` ，标签 ``label`` 的维度、数据类型与输入 ``input`` 相同。 | ||
| - **weight** (Tensor，可选) - 手动指定每个batch二值交叉熵的权重，如果指定的话，维度必须是一个batch的数据的维度。数据类型是float32, float64。默认值是：None。 |
| \text{loss}(x, y) = \sum_i \frac{\log(1 + \exp(-y[i]*x[i]))}{\text{x.nelement}()} | ||
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| 最后，添加 `reduce` 操作到前面的输出Out上。当 `reduction` 为 `none` 时，直接返回最原始的 `Out` 结果。当 `reduction` 为 `mean` 时，返回输出的均值 :math:`Out = MEAN(Out)` 。当 `reduction` 为 `sum` 时，返回输出的求和 :math:`Out = SUM(Out)` 。 |
Ligoml
approved these changes
Jul 26, 2022
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SoftMarginLoss API 中文文档
PADDLEPADDLE_PR=42364
【Hackathon No.21】