mindspore.nn.ELU

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class mindspore.nn.ELU(alpha=1.0)[source]

Applies the exponential linear unit function element-wise.

The activation function is defined as:

\[E_{i} = \begin{cases} x_i, &\text{if } x_i \geq 0; \cr \alpha * (\exp(x_i) - 1), &\text{otherwise.} \end{cases}\]

where \(x_i\) represents the element of the input and \(\alpha\) represents the alpha parameter.

ELU Activation Function Graph:

../../_images/ELU.png
Parameters

alpha (float) – The alpha value of ELU, the data type is float. Default: 1.0 . Only alpha equal to 1.0 is supported currently.

Inputs:

  • input_x (Tensor) - The input of ELU is a Tensor of any dimension with data type of float16 or float32.

Outputs:

Tensor, with the same type and shape as the 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

>>> import mindspore
>>> from mindspore import Tensor, nn
>>> import numpy as np
>>> x = Tensor(np.array([-1, -2, 0, 2, 1]), mindspore.float32)
>>> elu = nn.ELU()
>>> result = elu(x)
>>> print(result)
[-0.63212055  -0.86466473  0.  2.  1.]