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Modified describtion about reduction of SoftmaxCrossEntropyWithLogits.

This commit is contained in:
liuxiao93 2020-08-19 14:46:07 +08:00
parent 02256e0d9f
commit 0aa3dd4ef6
1 changed files with 3 additions and 3 deletions
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6
mindspore/nn/loss/loss.py
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@ -215,8 +215,8 @@ class SoftmaxCrossEntropyWithLogits(_Loss):
Args:
is_grad (bool): Specifies whether calculate grad only. Default: True.
sparse (bool): Specifies whether labels use sparse format or not. Default: False.
reduction (Union[str, None]): Type of reduction to be applied to loss. Support 'sum' and 'mean'. If None,
do not perform reduction. Default: None.
reduction (str): Type of reduction to be applied to loss. The optional values are "mean", "sum", and "none".
If "none", do not perform reduction. Default: "none".
smooth_factor (float): Label smoothing factor. It is a optional input which should be in range [0, 1].
Default: 0.
num_classes (int): The number of classes in the task. It is a optional input Default: 2.
@ -240,7 +240,7 @@ class SoftmaxCrossEntropyWithLogits(_Loss):
def __init__(self,
is_grad=True,
sparse=False,
reduction=None,
reduction='none',
smooth_factor=0,
num_classes=2):
super(SoftmaxCrossEntropyWithLogits, self).__init__(reduction)