Sum

Sum - 13

Version

  • name: Sum (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

Element-wise sum of each of the input tensors (with Numpy-style broadcasting support). All inputs and outputs must have the same data type. This operator supports multidirectional (i.e., Numpy-style) broadcasting; for more details please check Broadcasting in ONNX.

Inputs

Between 1 and 2147483647 inputs.

  • data_0 (variadic, heterogeneous) - T:

    List of tensors for sum.

Outputs

  • sum (heterogeneous) - T:

    Output tensor.

Type Constraints

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

    Constrain input and output types to float tensors.

Sum - 8

Version

  • name: Sum (GitHub)

  • domain: main

  • since_version: 8

  • function: False

  • support_level: SupportType.COMMON

  • shape inference: True

This version of the operator has been available since version 8.

Summary

Element-wise sum of each of the input tensors (with Numpy-style broadcasting support). All inputs and outputs must have the same data type. This operator supports multidirectional (i.e., Numpy-style) broadcasting; for more details please check Broadcasting in ONNX.

Inputs

Between 1 and 2147483647 inputs.

  • data_0 (variadic, heterogeneous) - T:

    List of tensors for sum.

Outputs

  • sum (heterogeneous) - T:

    Output tensor.

Type Constraints

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

    Constrain input and output types to float tensors.

Sum - 6

Version

  • name: Sum (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

Element-wise sum of each of the input tensors. All inputs and outputs must have the same shape and data type.

Inputs

Between 1 and 2147483647 inputs.

  • data_0 (variadic, heterogeneous) - T:

    List of tensors for Sum.

Outputs

  • sum (heterogeneous) - T:

    Output tensor. Same dimension as inputs.

Type Constraints

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

    Constrain input and output types to float tensors.

Sum - 1

Version

  • name: Sum (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

Element-wise sum of each of the input tensors. All inputs and outputs must have the same shape and data type.

Attributes

  • consumed_inputs - INTS :

    legacy optimization attribute.

Inputs

Between 1 and 2147483647 inputs.

  • data_0 (variadic, heterogeneous) - T:

    List of tensors for Sum.

Outputs

  • sum (heterogeneous) - T:

    Output tensor. Same dimension as inputs.

Type Constraints

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

    Constrain input and output types to float tensors.