log_normal_

paddle. log_normal_ ( x: Tensor, mean: float = 1.0, std: float = 2.0, name: str | None = None ) → Tensor [source]

This inplace version of api log_normal, which returns a Tensor filled with random values sampled from a log normal distribution. The output Tensor will be inplaced with input x. Please refer to log_normal.

Parameters

  • x (Tensor) – The input tensor to be filled with random values.

  • mean (float|int, optional) – Mean of the output tensor, default is 1.0.

  • std (float|int, optional) – Standard deviation of the output tensor, default is 2.0.

  • name (str|None, optional) – The default value is None. Normally there is no need for user to set this property. For more information, please refer to Name.

Returns

Tensor, A Tensor filled with random values sampled from a log normal distribution with the underlying normal distribution’s mean and std .

Examples

>>> import paddle
>>> paddle.seed(200)
>>> x = paddle.randn([3, 4])
>>> x.log_normal_()
>>> print(x)
Tensor(shape=[3, 4], dtype=float32, place=Place(cpu), stop_gradient=True,
[[3.99360156 , 0.11746082 , 12.14813519, 4.74383831 ],
 [0.36592522 , 0.09426476 , 31.81549835, 0.61839998 ],
 [1.33314908 , 12.31954002, 36.44527435, 1.69572163 ]])