mindspore.mint.nn.functional.tanh
- mindspore.mint.nn.functional.tanh(input)[source]
Computes hyperbolic tangent of input element-wise. The 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:
- Parameters
input (Tensor) – Input of Tanh.
- Returns
Tensor, with the same type and shape as the input.
- Raises
TypeError – If input is not a Tensor.
- Supported Platforms:
Ascend
Examples
>>> import mindspore >>> import numpy as np >>> from mindspore import Tensor, mint >>> input = Tensor(np.array([1, 2, 3, 4, 5]), mindspore.float32) >>> output = mint.nn.functional.tanh(input) >>> print(output) [0.7615941 0.9640276 0.9950547 0.9993293 0.9999092]