mindspore.ops.HShrink

class mindspore.ops.HShrink(lambd=0.5)[source]

Applies the hard shrinkage function element-wise, each element complies with the following function:

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

lambd (float) – The value for the HardShrink formulation. Default: 0.5

Inputs:

  • input_x (Tensor) - The input of HardShrink with data type of float16 or float32.

Outputs:

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

Supported Platforms:

Ascend

Raises

  • TypeError – If lambd is not a float.

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

Examples

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