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!10733 BUG-Fixed: [CT][MS][Document] correct the description of the operator sequence_mask

From: @david-he91
Reviewed-by: @liangchenghui,@wuxuejian
Signed-off-by: @liangchenghui
tags/v1.2.0-rc1
mindspore-ci-bot Gitee 5 years ago
parent
commit
7e8123aecf
2 changed files with 8 additions and 6 deletions
  1. +4
    -3
      mindspore/ops/composite/array_ops.py
  2. +4
    -3
      mindspore/ops/operations/_inner_ops.py

+ 4
- 3
mindspore/ops/composite/array_ops.py View File

@@ -113,11 +113,12 @@ def sequence_mask(lengths, maxlen):
[d_1, d_2, ..., d_n, maxlen], with mask[i_1, i_2, ..., i_n, j] = (j < lengths[i_1, i_2, ..., i_n])

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.
- **lengths** (Tensor) - Tensor to calculate the mask for. All values in this tensor should be
less than or equal to `maxlen`. Values greater than `maxlen` will be treated as `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`. Default is the maximum value in lengths.
type as elements in `lengths`.

Outputs:
One mask tensor of shape lengths.shape + (maxlen,).


+ 4
- 3
mindspore/ops/operations/_inner_ops.py View File

@@ -689,11 +689,12 @@ class SequenceMask(PrimitiveWithCheck):
[d_1, d_2, ..., d_n, maxlen], with mask[i_1, i_2, ..., i_n, j] = (j < lengths[i_1, i_2, ..., i_n])

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.
- **lengths** (Tensor) - Tensor to calculate the mask for. All values in this tensor should be
less than or equal to `maxlen`. Values greater than `maxlen` will be treated as `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`. Default is the maximum value in lengths.
type as elements in `lengths`.

Outputs:
One mask tensor of shape lengths.shape + (maxlen,).


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