mindspore.nn.Tanhshrink
- class mindspore.nn.Tanhshrink[source]
- Applies Tanhshrink activation function element-wise and returns a new tensor. - Tanh function is defined as: \[tanhshrink(x_i) =x_i- \frac{\exp(x_i) - \exp(-x_i)}{\exp(x_i) + \exp(-x_i)} = x_i-\frac{\exp(2x_i) - 1}{\exp(2x_i) + 1},\]- 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]