mindspore.ops.hardshrink

mindspore.ops.hardshrink(x, lambd=0.5)[source]

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

The formula is defined as follows:

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

HShrink Activation Function Graph:

../../_images/HShrink.png
Parameters

  • x (Tensor) – The input of Hard Shrink with data type of float16 or float32.

  • lambd (float, optional) – The threshold \(\lambda\) defined by the Hard Shrink formula. Default: 0.5 .

Returns

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

Raises

  • TypeError – If lambd is not a float.

  • TypeError – If x is not a tensor.

  • TypeError – If dtype of x is neither float16 nor float32.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> x = Tensor(np.array([[ 0.5,  1,  2.0], [0.0533,0.0776,-2.1233]]), mindspore.float32)
>>> output = ops.hardshrink(x)
>>> print(output)
[[ 0.      1.      2.    ]
[ 0.      0.     -2.1233]]