HardSigmoid - version 1#

This page documents version 1 of operator HardSigmoid. See HardSigmoid for the latest version (since version 22).

  • Domain: ai.onnx

  • Since version: 1

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

Inputs

  • X (T): Input tensor

Outputs

  • Y (T): Output tensor

Attributes

  • alpha (float): Value of alpha default to 0.2

  • beta (float): Value of beta default to 0.5

Type Constraints

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