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43def6b6
编写于
4月 27, 2020
作者:
G
Guanghua Yu
提交者:
GitHub
4月 27, 2020
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fix CrossEntropyLoss op en doc, test=develop (#24104)
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python/paddle/nn/layer/loss.py
python/paddle/nn/layer/loss.py
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python/paddle/nn/layer/loss.py
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43def6b6
...
...
@@ -27,20 +27,22 @@ __all__ = [
class
CrossEntropyLoss
(
fluid
.
dygraph
.
Layer
):
"""
This operator implements the cross entropy loss function. This OP combines `
softmax
`,
`
cross_entropy`, and `reduce_sum`/`reduce_mean
` together.
This operator implements the cross entropy loss function. This OP combines `
`softmax`
`,
`
`cross_entropy``, and ``reduce_sum``/``reduce_mean`
` together.
It is useful when training a classification problem with `
C
` classes.
If provided, the optional argument `
weight
` should be a 1D Variable assigning
It is useful when training a classification problem with `
`C`
` classes.
If provided, the optional argument `
`weight`
` should be a 1D Variable assigning
weight to each of the classes.
For predictions label, and target label, the loss is calculated as follows.
.. math::
loss_j = -
\\
text{input[class]} +
\\
log
\\
left(
\\
sum_{i=0}^{K}
\\
exp(
\\
text{input}_i)
\\
right), j = 1,..., K
If weight is not `None`:
If weight is not ``None``:
.. math::
loss_j =
\\
text{weight[class]}(-
\\
text{input[class]} +
...
...
@@ -60,9 +62,12 @@ class CrossEntropyLoss(fluid.dygraph.Layer):
If :attr:`size_average` is ``'sum'``, the reduced sum loss is returned.
If :attr:`reduction` is ``'none'``, the unreduced loss is returned.
Default is ``'mean'``.
Returns:
The tensor variable storing the cross_entropy_loss of input and label.
Return type: Variable.
Examples:
.. code-block:: python
...
...
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