Relu

Relu - 14

Version

  • name: Relu (GitHub)

  • domain: main

  • since_version: 14

  • function: True

  • support_level: SupportType.COMMON

  • shape inference: True

This version of the operator has been available since version 14.

Summary

Relu takes one input data (Tensor) and produces one output data (Tensor) where the rectified linear function, y = max(0, x), is applied to the tensor elementwise.

Function Body

The function definition for this operator.

<
  domain: "",
  opset_import: ["" : 18]
>
Relu (X) => (Y)
{
   Zero = Constant <value: tensor = float {0}> ()
   ZeroCast = CastLike (Zero, X)
   Y = Max (X, ZeroCast)
}

Inputs

  • X (heterogeneous) - T:

    Input tensor

Outputs

  • Y (heterogeneous) - T:

    Output tensor

Type Constraints

  • T in ( tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8) ):

    Constrain input and output types to signed numeric tensors.

Relu - 13

Version

  • name: Relu (GitHub)

  • domain: main

  • since_version: 13

  • function: False

  • support_level: SupportType.COMMON

  • shape inference: True

This version of the operator has been available since version 13.

Summary

Relu takes one input data (Tensor) and produces one output data (Tensor) where the rectified linear function, y = max(0, x), is applied to the tensor elementwise.

Inputs

  • X (heterogeneous) - T:

    Input tensor

Outputs

  • Y (heterogeneous) - T:

    Output tensor

Type Constraints

  • T in ( tensor(bfloat16), tensor(double), tensor(float), tensor(float16) ):

    Constrain input and output types to float tensors.

Relu - 6

Version

  • name: Relu (GitHub)

  • domain: main

  • since_version: 6

  • function: False

  • support_level: SupportType.COMMON

  • shape inference: True

This version of the operator has been available since version 6.

Summary

Relu takes one input data (Tensor) and produces one output data (Tensor) where the rectified linear function, y = max(0, x), is applied to the tensor elementwise.

Inputs

  • X (heterogeneous) - T:

    Input tensor

Outputs

  • Y (heterogeneous) - T:

    Output tensor

Type Constraints

  • T in ( tensor(double), tensor(float), tensor(float16) ):

    Constrain input and output types to float tensors.

Relu - 1

Version

  • name: Relu (GitHub)

  • domain: main

  • since_version: 1

  • function: False

  • support_level: SupportType.COMMON

  • shape inference: False

This version of the operator has been available since version 1.

Summary

Relu takes one input data (Tensor) and produces one output data (Tensor) where the rectified linear function, y = max(0, x), is applied to the tensor elementwise.

Attributes

  • consumed_inputs - INTS :

    legacy optimization attribute.

Inputs

  • X (heterogeneous) - T:

    Input tensor

Outputs

  • Y (heterogeneous) - T:

    Output tensor

Type Constraints

  • T in ( tensor(double), tensor(float), tensor(float16) ):

    Constrain input and output types to float tensors.