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Restrict the range of the parameters in random ops

This commit is contained in:
peixu_ren 2020-09-14 16:50:50 -04:00
parent a92e444f21
commit 54d38e4d13
2 changed files with 9 additions and 8 deletions
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9
mindspore/ops/composite/random_ops.py
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@ -49,7 +49,8 @@ def normal(shape, mean, stddev, seed=0):
shape (tuple): The shape of random tensor to be generated.
mean (Tensor): The mean μ distribution parameter, which specifies the location of the peak.
With float32 data type.
stddev (Tensor): The deviation σ distribution parameter. With float32 data type.
stddev (Tensor): The deviation σ distribution parameter. It should be greater than 0.
With float32 data type.
seed (int): Seed is used as entropy source for Random number engines generating pseudo-random numbers.
Must be non-negative. Default: 0.
@ -136,8 +137,8 @@ def gamma(shape, alpha, beta, seed=0):
Args:
shape (tuple): The shape of random tensor to be generated.
alpha (Tensor): The alpha α distribution parameter. With float32 data type.
beta (Tensor): The beta β distribution parameter. With float32 data type.
alpha (Tensor): The alpha α distribution parameter. It should be greater than 0. With float32 data type.
beta (Tensor): The beta β distribution parameter. It should be greater than 0. With float32 data type.
seed (int): Seed is used as entropy source for Random number engines generating pseudo-random numbers.
Must be non-negative. Default: 0.
@ -164,7 +165,7 @@ def poisson(shape, mean, seed=0):
Args:
shape (tuple): The shape of random tensor to be generated.
mean (Tensor): The mean μ distribution parameter. With float32 data type.
mean (Tensor): The mean μ distribution parameter. It should be greater than 0. With float32 data type.
seed (int): Seed is used as entropy source for Random number engines generating pseudo-random numbers.
Must be non-negative. Default: 0.

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

@ -130,9 +130,9 @@ class Gamma(PrimitiveWithInfer):
Inputs:
- **shape** (tuple) - The shape of random tensor to be generated. Only constant value is allowed.
- **alpha** (Tensor) - The α distribution parameter.
- **alpha** (Tensor) - The α distribution parameter. It should be greater than 0.
It is also known as the shape parameter with float32 data type.
- **beta** (Tensor) - The β distribution parameter.
- **beta** (Tensor) - The β distribution parameter. It should be greater than 0.
It is also known as the scale parameter with float32 data type.
Outputs:
@ -185,8 +185,8 @@ class Poisson(PrimitiveWithInfer):
Inputs:
- **shape** (tuple) - The shape of random tensor to be generated. Only constant value is allowed.
- **mean** (Tensor) - μ, parameter which the distribution was constructed with.
The parameter defines the mean number of occurrences of the event, with float32 data type.
- **mean** (Tensor) - μ parameter the distribution was constructed with. The parameter defines mean number
of occurrences of the event. It should be greater than 0. With float32 data type.
Outputs:
Tensor. Its shape should be the broadcasted shape of `shape` and the shape of `mean`.