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!10639 BUG-Fixed: [CT][MS][Document] fix bug in the example of LARSUpdate and SequenceMask 

From: @david-he91
Reviewed-by: @liangchenghui,@wuxuejian
Signed-off-by: @liangchenghui
This commit is contained in:
mindspore-ci-bot 2020-12-27 17:02:35 +08:00 committed by Gitee
parent f1f6092bf6 d9833bdf61
commit 36cd9caa49
3 changed files with 13 additions and 13 deletions
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13
mindspore/ops/composite/array_ops.py
View File

@ -112,12 +112,12 @@ def sequence_mask(lengths, maxlen):
If lengths has shape [d_1, d_2, ..., d_n], then the resulting tensor mask has type dtype and shape
[d_1, d_2, ..., d_n, maxlen], with mask[i_1, i_2, ..., i_n, j] = (j < lengths[i_1, i_2, ..., i_n])
Args:
length (Tensor): Tensor to calculate the mask for. All values in this tensor must be
Inputs:
- **lengths** (Tensor) - Tensor to calculate the mask for. All values in this tensor must be
less than or equal to `maxlen`. Must be type int32 or int64.
maxlen (int): size of the last dimension of returned tensor. Must be positive and same
type as elements in `lengths`.
- **maxlen** (int) - size of the last dimension of returned tensor. Must be positive and same
type as elements in `lengths`. Default is the maximum value in lengths.
Outputs:
One mask tensor of shape lengths.shape + (maxlen,).
@ -126,9 +126,8 @@ def sequence_mask(lengths, maxlen):
``GPU``
Examples:
>>> x = Tensor(np.array([[1, 3], [2, 0]])
>>> sequence_mask = P.SequenceMask()
>>> output = sequence_mask(x, 3)
>>> x = Tensor(np.array([[1, 3], [2, 0]]))
>>> output = C.sequence_mask(x, 3)
>>> print(output)
[[[True, False, False],
[True, True, True]],

8
mindspore/ops/operations/_inner_ops.py
View File

@ -690,10 +690,10 @@ class SequenceMask(PrimitiveWithCheck):
Inputs:
- **lengths** (Tensor) - Tensor to calculate the mask for. All values in this tensor must be
less than `maxlen`. Must be type int32 or int64.
less than or equal to `maxlen`. Must be type int32 or int64.
- **maxlen** (int) - size of the last dimension of returned tensor. Must be positive and same
type as elements in `lengths`.
type as elements in `lengths`. Default is the maximum value in lengths.
Outputs:
One mask tensor of shape lengths.shape + (maxlen,).
@ -702,8 +702,8 @@ class SequenceMask(PrimitiveWithCheck):
``GPU``
Examples:
>>> x = Tensor(np.array([[1, 3], [2, 0]])
>>> sequence_mask = P.SequenceMask()
>>> x = Tensor(np.array([[1, 3], [2, 0]]))
>>> sequence_mask = ops.SequenceMask()
>>> output = sequence_mask(x, 3)
>>> print(output)
[[[True, False, False],

5
mindspore/ops/operations/nn_ops.py
View File

@ -5689,9 +5689,10 @@ class LARSUpdate(PrimitiveWithInfer):
... super(Net, self).__init__()
... self.lars = ops.LARSUpdate()
... self.reduce = ops.ReduceSum()
... self.square = ops.Square()
... def construct(self, weight, gradient):
... w_square_sum = self.reduce(ops.Square()(weight))
... grad_square_sum = self.reduce(ops.Square()(gradient))
... w_square_sum = self.reduce(self.square(weight))
... grad_square_sum = self.reduce(self.square(gradient))
... grad_t = self.lars(weight, gradient, w_square_sum, grad_square_sum, 0.0, 1.0)
... return grad_t
...