HardSwish - version 14#

This page documents version 14 of operator HardSwish. See HardSwish for the latest version (since version 22).

  • Domain: ai.onnx

  • Since version: 14

HardSwish takes one input data (Tensor ) and produces one output data (Tensor ) where the HardSwish function, y = x * max(0, min(1, alpha * x + beta)) = x * HardSigmoid (x), where alpha = 1/6 and beta = 0.5, is applied to the tensor elementwise.

Inputs

  • X (T): Input tensor

Outputs

  • Y (T): Output tensor

Type Constraints

  • T: Constrain input and output types to float tensors. Allowed types: tensor(double), tensor(float), tensor(float16).