mindspore.ops.tanh

mindspore.ops.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.

Parameters

input (Tensor) – Input of Tanh, with float16 or float32 data type.

Returns

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

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

  • TypeError – If input is not a Tensor.

Supported Platforms:

Ascend GPU CPU

Examples

>>> input = Tensor(np.array([1, 2, 3, 4, 5]), mindspore.float32)
>>> output = ops.tanh(input)
>>> print(output)
[0.7615941 0.9640276 0.9950547 0.9993293 0.9999092]