Greater

Greater - 13

Version

  • name: Greater (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

Returns the tensor resulted from performing the greater logical operation elementwise on the input tensors A and B (with Numpy-style broadcasting support).

This operator supports multidirectional (i.e., Numpy-style) broadcasting; for more details please check Broadcasting in ONNX.

Inputs

  • A (heterogeneous) - T:

    First input operand for the logical operator.

  • B (heterogeneous) - T:

    Second input operand for the logical operator.

Outputs

  • C (heterogeneous) - T1:

    Result tensor.

Type Constraints

  • T in ( tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) ):

    Constrain input types to all numeric tensors.

  • T1 in ( tensor(bool) ):

    Constrain output to boolean tensor.

Greater - 9

Version

  • name: Greater (GitHub)

  • domain: main

  • since_version: 9

  • function: False

  • support_level: SupportType.COMMON

  • shape inference: True

This version of the operator has been available since version 9.

Summary

Returns the tensor resulted from performing the greater logical operation elementwise on the input tensors A and B (with Numpy-style broadcasting support).

This operator supports multidirectional (i.e., Numpy-style) broadcasting; for more details please check Broadcasting in ONNX.

Inputs

  • A (heterogeneous) - T:

    First input operand for the logical operator.

  • B (heterogeneous) - T:

    Second input operand for the logical operator.

Outputs

  • C (heterogeneous) - T1:

    Result tensor.

Type Constraints

  • T in ( tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) ):

    Constrain input types to all numeric tensors.

  • T1 in ( tensor(bool) ):

    Constrain output to boolean tensor.

Greater - 7

Version

  • name: Greater (GitHub)

  • domain: main

  • since_version: 7

  • function: False

  • support_level: SupportType.COMMON

  • shape inference: True

This version of the operator has been available since version 7.

Summary

Returns the tensor resulted from performing the greater logical operation elementwise on the input tensors A and B (with Numpy-style broadcasting support).

This operator supports multidirectional (i.e., Numpy-style) broadcasting; for more details please check Broadcasting in ONNX.

Inputs

  • A (heterogeneous) - T:

    First input operand for the logical operator.

  • B (heterogeneous) - T:

    Second input operand for the logical operator.

Outputs

  • C (heterogeneous) - T1:

    Result tensor.

Type Constraints

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

    Constrain input to float tensors.

  • T1 in ( tensor(bool) ):

    Constrain output to boolean tensor.

Greater - 1

Version

  • name: Greater (GitHub)

  • domain: main

  • since_version: 1

  • function: False

  • support_level: SupportType.COMMON

  • shape inference: True

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

Summary

Returns the tensor resulted from performing the greater logical operation elementwise on the input tensors A and B.

If broadcasting is enabled, the right-hand-side argument will be broadcasted to match the shape of left-hand-side argument. See the doc of Add for a detailed description of the broadcasting rules.

Attributes

  • axis - INT :

    If set, defines the broadcast dimensions.

  • broadcast - INT (default is '0'):

    Enable broadcasting

Inputs

  • A (heterogeneous) - T:

    Left input tensor for the logical operator.

  • B (heterogeneous) - T:

    Right input tensor for the logical operator.

Outputs

  • C (heterogeneous) - T1:

    Result tensor.

Type Constraints

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

    Constrain input to float tensors.

  • T1 in ( tensor(bool) ):

    Constrain output to boolean tensor.