mindspore.nn.HShrink
- class mindspore.nn.HShrink(lambd=0.5)[source]
Hard Shrink activation function. Calculates the output according to the input elements.
The formula is defined as follows:
\[\begin{split}\text{HardShrink}(x) = \begin{cases} x, & \text{ if } x > \lambda \\ x, & \text{ if } x < -\lambda \\ 0, & \text{ otherwise } \end{cases}\end{split}\]- Parameters
lambd (float) – The threshold \(\lambda\) defined by the Hard Shrink formula. Default: 0.5.
- Inputs:
input_x (Tensor) - The input of Hard Shrink with data type of float16 or float32.
- Outputs:
Tensor, the same shape and data type as the input.
- Supported Platforms:
Ascend
CPU
GPU
- Raises
Examples
>>> import mindspore >>> 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]]), mindspore.float32) >>> hshrink = nn.HShrink() >>> output = hshrink(input_x) >>> print(output) [[ 0. 1. 2. ] [ 0. 0. -2.1233]]