p83571920
/
mindspore
forked from mindspore-Ecosystem/mindspore
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

!10307 add type check support to sampledsoftmaxloss 

From: @TFbunny
Reviewed-by: @liangchenghui,@wuxuejian
Signed-off-by: @liangchenghui
This commit is contained in:
mindspore-ci-bot 2020-12-22 09:26:16 +08:00 committed by Gitee
parent 2b64b7f295 b3b06169c6
commit 7a873d10a1
1 changed files with 8 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

8
mindspore/nn/loss/loss.py
View File

@ -281,6 +281,10 @@ class SoftmaxCrossEntropyWithLogits(_Loss):
x = self.softmax_cross_entropy(logits, labels)[0]
return self.get_loss(x)
@constexpr
def _check_label_dtype(labels_dtype, cls_name):
validator.check_type_name("labels", labels_dtype, [mstype.int32, mstype.int64], cls_name)
class SampledSoftmaxLoss(_Loss):
r"""
@ -373,8 +377,11 @@ class SampledSoftmaxLoss(_Loss):
self.zeros_like = P.ZerosLike()
self.mul = P.Mul()
self.expand_dims = P.ExpandDims()
self.dtype = P.DType()
def construct(self, weights, biases, labels, inputs):
_check_label_dtype(self.dtype(labels), self.cls_name)
logits, labels = self._compute_sampled_logits(
weights=weights,
biases=biases,
@ -424,6 +431,7 @@ class SampledSoftmaxLoss(_Loss):
`[batch_size, num_true + num_sampled]`
out_labels: A Tensor object with the same shape as `out_logits`.
"""
if not labels.dtype == mstype.int32:
labels = self.cast(labels, mstype.int32)
labels = self.reshape(labels, (-1, num_true))