mindspore.ops.Elu

class mindspore.ops.Elu(*args, **kwargs)[source]

Computes exponential linear:

\[\begin{split}\text{ELU}(x)= \left\{ \begin{array}{align} \alpha(e^{x} - 1) & \text{if } x \le 0\\ x & \text{if } x \gt 0\\ \end{array}\right.\end{split}\]

The data type of input tensor must be float.

Parameters

alpha (float) – The coefficient of negative factor whose type is float, only support ‘1.0’ currently. Default: 1.0.

Inputs:

  • input_x (Tensor) - Tensor of shape \((N, *)\), where \(*\) means, any number of additional dimensions, with float16 or float32 data type.

Outputs:

Tensor, has the same shape and data type as input_x.

Raises

  • TypeError – If alpha is not a float.

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

  • ValueError – If alpha is not equal to 1.0.

Supported Platforms:

Ascend GPU CPU

Examples

>>> input_x = Tensor(np.array([[-1.0, 4.0, -8.0], [2.0, -5.0, 9.0]]), mindspore.float32)
>>> elu = ops.Elu()
>>> output = elu(input_x)
>>> print(output)
[[-0.63212055  4.         -0.99966455]
 [ 2.         -0.99326205  9.        ]]