HardSigmoid - version 6#

This page documents version 6 of operator HardSigmoid. See HardSigmoid for the latest version (since version 22).

  • Domain: ai.onnx

  • Since version: 6

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.

  • beta (float): Value of beta.

Type Constraints

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

Differences with previous version (1)#

SchemaDiff: HardSigmoid (domain 'ai.onnx')

  • old version: 1

  • new version: 6

  • breaking: no