mindspore.ops.Tanh
- class mindspore.ops.Tanh[source]
Tanh activation function.
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.
- Inputs:
input_x (Tensor) - Tensor of shape \((N, *)\), where \(*\) means, any number of additional dimensions, with float16 or float32 data type.
- Outputs:
Tensor, with the same type and shape as the input_x.
- Raises
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> input_x = Tensor(np.array([1, 2, 3, 4, 5]), mindspore.float32) >>> tanh = ops.Tanh() >>> output = tanh(input_x) >>> print(output) [0.7615941 0.9640276 0.9950547 0.9993293 0.9999092]