mindspore.mint.nn.functional.softshrink

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mindspore.mint.nn.functional.softshrink(input, lambd=0.5)[source]

Soft Shrink activation function. Calculates the output according to the input elements.

The formula is defined as follows:

\[\begin{split}\text{SoftShrink}(x) = \begin{cases} x - \lambda, & \text{ if } x > \lambda \\ x + \lambda, & \text{ if } x < -\lambda \\ 0, & \text{ otherwise } \end{cases}\end{split}\]

SoftShrink Activation Function Graph:

../../_images/Softshrink.png
Parameters

  • input (Tensor) –

    The input of Soft Shrink. Supported dtypes:

    • Ascend: float16, float32, bfloat16.

  • lambd (number, optional) – The threshold \(\lambda\) defined by the Soft Shrink formula. It should be greater than or equal to 0, default: 0.5 .

Returns

Tensor, has the same data type and shape as the input input.

Raises

  • TypeError – If lambd is not a float, int or bool.

  • TypeError – If input is not a tensor.

  • TypeError – If dtype of input is not float16, float32 or bfloat16.

Supported Platforms:

Ascend

Examples

>>> import mindspore
>>> from mindspore import Tensor
>>> from mindspore import mint
>>> import numpy as np
>>> x = Tensor(np.array([[ 0.5297,  0.7871,  1.1754], [ 0.7836,  0.6218, -1.1542]]), mindspore.float32)
>>> output = mint.nn.functional.softshrink(x)
>>> print(output)
[[ 0.02979  0.287    0.676  ]
[ 0.2837   0.1216  -0.6543 ]]