mindspore.nn.Tanhshrink

class mindspore.nn.Tanhshrink[source]

Applies Tanhshrink activation function element-wise and returns a new tensor.

Tanh function is defined as:

t a n h s h r i n k (x_{i}) = x_{i} - \frac{\exp (x_{i}) - \exp (- x_{i})}{\exp (x_{i}) + \exp (- x_{i})} = x_{i} - \frac{\exp (2 x_{i}) - 1}{\exp (2 x_{i}) + 1},

where $x_{i}$ is an element of the input Tensor.

Inputs:

x (Tensor) - Tensor of any dimension.

Outputs:

Tensor, with the same shape as the x.

Raises: TypeError – If x is not a Tensor.

Supported Platforms:: Ascend GPU CPU

Examples

>>> import mindspore as ms
>>> from mindspore import Tensor, nn
>>> import numpy as np
>>> x = Tensor(np.array([1, 2, 3, 2, 1]), ms.float16)
>>> tanhshrink = nn.Tanhshrink()
>>> output = tanhshrink(x)
>>> print(output)
[0.2383 1.036  2.004  1.036  0.2383]