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fix doc bugs #58933

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Nov 14, 2023
Merged

fix doc bugs #58933

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24 changes: 12 additions & 12 deletions python/paddle/nn/functional/loss.py
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Original file line number Diff line number Diff line change
Expand Up @@ -238,12 +238,12 @@ def base_softmax_with_cross_entropy(
is the rank of input :attr:`logits`. Default: -1.

Returns:
``Tensor`` or Tuple of two ``Tensor`` : Return the cross entropy loss if \
`return_softmax` is False, otherwise the tuple \
(loss, softmax), softmax is in the same shape \
with input logits and cross entropy loss is in \
the same shape with input logits except shape \
in dimension :attr:`axis` as 1.
- If `return_softmax` is False, return the cross entropy loss as a ``Tensor``.
The dtype is the same as the input ``logits``. The shape is consistent with ``logits`` except in dimension :attr:`axis` as 1.
- If `return_softmax` is True, return a tuple of two ``Tensor``: the cross entropy loss and the softmax result.
The dtype of the cross entropy loss is the same as the input ``logits``, and the shape is consistent with ``logits``
except in dimension :attr:`axis` as 1. The dtype and shape of the softmax result are the same as the input ``logits``.


Examples:
.. code-block:: python
Expand Down Expand Up @@ -2458,12 +2458,12 @@ def softmax_with_cross_entropy(
is the rank of input :attr:`logits`. Default: -1.

Returns:
``Tensor`` or Tuple of two ``Tensor`` : Return the cross entropy loss if \
`return_softmax` is False, otherwise the tuple \
(loss, softmax), softmax is in the same shape \
with input logits and cross entropy loss is in \
the same shape with input logits except shape \
in dimension :attr:`axis` as 1.
- If `return_softmax` is False, return the cross entropy loss as a ``Tensor``.
The dtype is the same as the input ``logits``. The shape is consistent with ``logits`` except in dimension :attr:`axis` as 1.
- If `return_softmax` is True, return a tuple of two ``Tensor``: the cross entropy loss and the softmax result.
The dtype of the cross entropy loss is the same as the input ``logits``, and the shape is consistent with ``logits``
except in dimension :attr:`axis` as 1. The dtype and shape of the softmax result are the same as the input ``logits``.


Examples:
.. code-block:: python
Expand Down