mindspore.ops.HSigmoid

class mindspore.ops.HSigmoid

Hard sigmoid activation function.

Applies hard sigmoid activation element-wise. The input is a Tensor with any valid shape.

Hard sigmoid is defined as:

\[\text{hsigmoid}(x_{i}) = max(0, min(1, \frac{x_{i} + 3}{6})),\]

where \(x_i\) is an element of the input Tensor.

Inputs:

• input_x (Tensor) - Tensor of shape \((N, *)\), where \(*\) means, any number of additional dimensions.

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

>>> hsigmoid = ops.HSigmoid()
>>> input_x = Tensor(np.array([-1, -2, 0, 2, 1]), mindspore.float16)
>>> result = hsigmoid(input_x)
>>> print(result)
[0.3333 0.1666 0.5    0.8335 0.6665]