mindspore.nn.HSigmoid
- class mindspore.nn.HSigmoid[source]
Applies Hard sigmoid activation function element-wise.
Hard sigmoid is defined as:
\[\text{hsigmoid}(x_{i}) = \max(0, \min(1, \frac{x_{i} + 3}{6})),\]HSigmoid Activation Function Graph:
- Inputs:
input_x (Tensor) - The input of HSigmoid. Tensor of any dimension.
- Outputs:
Tensor, with the same type and shape as the input_x.
- Raises
TypeError – If input_x is not a Tensor.
- 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.float16) >>> hsigmoid = nn.HSigmoid() >>> result = hsigmoid(x) >>> print(result) [0.3333 0.1666 0.5 0.8335 0.6665]