mindspore.ops.selu
- mindspore.ops.selu(input_x)[source]
Activation function SeLU (Scaled exponential Linear Unit).
The activation function is defined as:
\[E_{i} = scale * \begin{cases} x_{i}, &\text{if } x_{i} \geq 0; \cr \text{alpha} * (\exp(x_i) - 1), &\text{otherwise.} \end{cases}\]where \(alpha\) and \(scale\) are pre-defined constants(\(alpha=1.67326324\) and \(scale=1.05070098\)).
See more details in Self-Normalizing Neural Networks.
- Parameters
input_x (Tensor) – Tensor of any dimension, the data type is float16 or float32.
- Returns
Tensor, with the same type and shape as the input_x.
- Supported Platforms:
Ascend
GPU
CPU
- Raises
TypeError – If dtype of input_x is neither float16 nor float32.
Examples
>>> input_x = Tensor(np.array([[-1.0, 4.0, -8.0], [2.0, -5.0, 9.0]]), mindspore.float32) >>> output = ops.selu(input_x) >>> print(output) [[-1.1113307 4.202804 -1.7575096] [ 2.101402 -1.7462534 9.456309 ]]