mindspore.Tensor.log_normal
- Tensor.log_normal(mean=1.0, std=2.0)[source]
Fills the elements of the input tensor with log normal values initialized by given mean and std:
\[\text{f}(x;1.0,2.0)=\frac{1}{x\delta \sqrt[]{2\pi} }e^{-\frac{(\ln x-\mu )^2}{2\delta ^2} }\]where \(\mu\), \(\delta\) is mean and standard deviation of lognormal distribution respectively.
Warning
This is an experimental API that is subject to change or deletion.
- Parameters
- Returns
Tensor. A Tensor with the same type and shape of input.
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> import mindspore >>> import numpy as np >>> x = mindspore.Tensor(np.array([[1, 2], [3, 4]]), dtype=mindspore.float32) >>> output = x.log_normal() >>> print(output) [[1.2788825 2.3305743] [14.944194 0.16303174]]