mindspore.nn.HShrink

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

Applies the hard shrinkage function element-wise, each element complies the follow 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

>>> input_x = Tensor(np.array([[ 0.5,  1,  2.0],[0.0533,0.0776,-2.1233]]),mstype.float32)
>>> hshrink = nn.HShrink()
>>> output = hshrink(input_x)
>>> print(output)
[[ 0.      1.      2.    ]
[ 0.      0.     -2.1233]]