mindspore.mint.nn.Tanh

class mindspore.mint.nn.Tanh[source]

Applies the Tanh function element-wise, returns a new tensor with the hyperbolic tangent of the elements of input.

Tanh function is defined as:

\[tanh(x_i) = \frac{\exp(x_i) - \exp(-x_i)}{\exp(x_i) + \exp(-x_i)} = \frac{\exp(2x_i) - 1}{\exp(2x_i) + 1},\]

where \(x_i\) is an element of the input Tensor.

Tanh Activation Function Graph:

../../_images/Tanh.png

Warning

This is an experimental API that is subject to change or deletion.

Inputs:

  • input (Tensor) - Tensor of any dimension, input with data type of float16 or float32.

Outputs:

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

Raises

TypeError – If dtype of input is neither float16 nor float32.

Supported Platforms:

Ascend

Examples

>>> import mindspore
>>> from mindspore import Tensor, mint
>>> import numpy as np
>>> input = Tensor(np.array([1, 2, 3, 2, 1]), mindspore.float16)
>>> tanh = mint.nn.Tanh()
>>> output = tanh(input)
>>> print(output)
[0.7617 0.964  0.995  0.964  0.7617]