mindspore.ops.hardswish
- mindspore.ops.hardswish(x)[source]
Hard swish activation function.
Applies hswish-type activation element-wise. The input is a Tensor with any valid shape.
Hard swish is defined as:
\[\text{hswish}(x_{i}) = x_{i} * \frac{ReLU6(x_{i} + 3)}{6},\]where \(x_i\) is an element of the input Tensor.
- Parameters
x (Tensor) – The input to compute the Hard Swish with data type of float16 or float32.
- Returns
Tensor, has the same data type and shape as the input.
- Raises
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> x = Tensor(np.array([-1, -2, 0, 2, 1]), mindspore.float16) >>> output = ops.hardswish(x) >>> print(output) [-0.3333 -0.3333 0 1.666 0.6665]