exponential_

paddle.Tensor. exponential_ ( x: Tensor, lam: float = 1.0, name: str | None = None ) → Tensor

This inplace OP fill input Tensor x with random number from a Exponential Distribution.

lam is \(\lambda\) parameter of Exponential Distribution.

\[f(x) = \lambda e^{-\lambda x}\]

Note

Alias Support: The parameter name lambd can be used as an alias for lam. For example, exponential_(tensor_x, lambd=1.0, ...) is equivalent to exponential_(tensor_x, lam=1.0, ...).

Parameters

x (Tensor) – Input tensor. The data type should be float32, float64.
lam (float, optional) – \(\lambda\) parameter of Exponential Distribution. Default, 1.0. alias: lambd.
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 api_guide_Name.

Returns

Tensor, Input Tensor x.

Examples

           >>> import paddle
>>> paddle.set_device('cpu')
>>> paddle.seed(100)

>>> x = paddle.empty([2,3])
>>> x.exponential_()
>>> 
Tensor(shape=[2, 3], dtype=float32, place=Place(cpu), stop_gradient=True,
[[0.80643415, 0.23211166, 0.01169797],
 [0.72520679, 0.45208144, 0.30234432]])
>>> 

          