hardswish¶
- paddle.nn.functional. hardswish ( x, name=None ) [source]
-
hardswish activation. hardswish is proposed in MobileNetV3, and performs better in computational stability and efficiency compared to swish function. For more details please refer to: https://arxiv.org/pdf/1905.02244.pdf
\[\begin{split}hardswish(x)= \left\{ \begin{array}{cll} 0 &, & \text{if } x \leq -3 \\ x &, & \text{if } x \geq 3 \\ \frac{x(x+3)}{6} &, & \text{otherwise} \end{array} \right.\end{split}\]- Parameters
-
x (Tensor) – The input Tensor with data type float32, float64.
name (str, optional) – For details, please refer to Name. Generally, no setting is required. Default: None.
- Returns
-
A Tensor with the same data type and shape as
x
.
Examples
>>> import paddle >>> import paddle.nn.functional as F >>> x = paddle.to_tensor([-4., 5., 1.]) >>> out = F.hardswish(x) >>> print(out) Tensor(shape=[3], dtype=float32, place=Place(cpu), stop_gradient=True, [-0. , 5. , 0.66666669])