mindspore.Tensor.normal_

View Source On Gitee
Tensor.normal_(mean=0, std=1, *, generator=None)[source]

Update the self tensor in place by generating random numbers sampled from the normal distribution which constructed by the parameters mean and std.

Warning

This is an experimental API that is subject to change or deletion.

Parameters

  • mean (number, optional) – the mean of normal distribution. With float data type. Default: 0.

  • std (number, optional) – the std of normal distribution. With float data type. Default: 1.

Keyword Arguments

generator (mindspore.Generator, optional) – a pseudorandom number generator. Default: None, uses the default pseudorandom number generator.

Returns

A tensor that is filled with random numbers that follow a normal distribution and that has the same type and shape as the self tensor.

Raises

TypeError – If the dtype of mean or std is not one of: bool, int, float, complex.

Supported Platforms:

Ascend

Examples

>>> import mindspore
>>> import numpy as np
>>> x = mindspore.Tensor(np.array([[1, 2], [3, 4]]), dtype=mindspore.float32)
>>> output = x.normal_()
>>> print(output)
[[0.2788825 1.3305743]
 [1.244194 1.16303174]]