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!9403 Fix input/output docstring indentation for ops in random_ops.py 

From: @peilin-wang
Reviewed-by: @robingrosman,@tom__chen
Signed-off-by: @robingrosman
This commit is contained in:
mindspore-ci-bot 2020-12-04 04:15:08 +08:00 committed by Gitee
parent a15356c779 acfe9c9aab
commit 98aac335fa
1 changed files with 5 additions and 5 deletions
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10
mindspore/ops/operations/random_ops.py
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@ -401,7 +401,7 @@ class RandomChoiceWithMask(PrimitiveWithInfer):
Inputs:
- **input_x** (Tensor[bool]) - The input tensor.
The input tensor rank must be greater than or equal to 1 and less than or equal to 5.
The input tensor rank must be greater than or equal to 1 and less than or equal to 5.
Outputs:
Two tensors, the first one is the index tensor and the other one is the mask tensor.
@ -530,7 +530,7 @@ class Multinomial(PrimitiveWithInfer):
seed2 (int): Random seed2, must be non-negative. Default: 0.
Inputs:
- **input** (Tensor[float32]) - the input tensor containing the cumsum of probabilities, must be 1 or 2
dimensions.
dimensions.
- **num_samples** (int32) - number of samples to draw.
Outputs:
@ -594,11 +594,11 @@ class UniformCandidateSampler(PrimitiveWithInfer):
Outputs:
- **sampled_candidates** (Tensor) - The sampled_candidates is independent of the true classes.
Shape: (num_sampled, ).
Shape: (num_sampled, ).
- **true_expected_count** (Tensor) - The expected counts under the sampling distribution of each
of true_classes. Shape: (batch_size, num_true).
of true_classes. Shape: (batch_size, num_true).
- **sampled_expected_count** (Tensor) - The expected counts under the sampling distribution of
each of sampled_candidates. Shape: (num_sampled, ).
each of sampled_candidates. Shape: (num_sampled, ).
Supported Platforms:
``GPU``