mindspore.ops.laplace

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mindspore.ops.laplace(shape, mean, lambda_param, seed=None)[source]

Generates random numbers according to the Laplace random number distribution. It is defined as:

\[\text{f}(x;μ,λ) = \frac{1}{2λ}\exp(-\frac{|x-μ|}{λ}),\]

Warning

The Ascend backend does not support the reproducibility of random numbers, so the seed parameter has no effect.

Parameters

  • shape (tuple) – The shape of random tensor to be generated. The format is \((N,*)\) where \(*\) means, any number of additional dimensions.

  • mean (Tensor) – The mean μ distribution parameter, which specifies the location of the peak. With float32 data type.

  • lambda_param (Tensor) – The parameter used for controlling the variance of this random distribution. The variance of Laplace distribution is equal to twice the square of lambda_param. With float32 data type.

  • seed (int, optional) – Seed is used as entropy source for Random number engines generating pseudo-random numbers. Default: None , which will be treated as 0.

Returns

Tensor. The shape should be the broadcasted shape of input shape and shapes of mean and lambda_param. The dtype is float32.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> from mindspore import Tensor
>>> from mindspore import ops as ops
>>> shape = (2, 3)
>>> mean = Tensor(1.0, mindspore.float32)
>>> lambda_param = Tensor(1.0, mindspore.float32)
>>> output = ops.laplace(shape, mean, lambda_param, seed=5)
>>> print(output.shape)
(2, 3)