ArgMin

ArgMin - 13

Version

  • name: ArgMin (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

Computes the indices of the min elements of the input tensor’s element along the provided axis. The resulting tensor has the same rank as the input if keepdims equals 1. If keepdims equals 0, then the resulting tensor has the reduced dimension pruned. If select_last_index is True (default False), the index of the last occurrence of the min is selected if the min appears more than once in the input. Otherwise the index of the first occurrence is selected. The type of the output tensor is integer.

Attributes

  • axis - INT (default is '0'):

    The axis in which to compute the arg indices. Accepted range is [-r, r-1] where r = rank(data).

  • keepdims - INT (default is '1'):

    Keep the reduced dimension or not, default 1 means keep reduced dimension.

  • select_last_index - INT (default is '0'):

    Whether to select the last index or the first index if the {name} appears in multiple indices, default is False (first index).

Inputs

  • data (heterogeneous) - T:

    An input tensor.

Outputs

  • reduced (heterogeneous) - tensor(int64):

    Reduced output tensor with integer data type.

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 and output types to all numeric tensors.

ArgMin - 12

Version

  • name: ArgMin (GitHub)

  • domain: main

  • since_version: 12

  • function: False

  • support_level: SupportType.COMMON

  • shape inference: True

This version of the operator has been available since version 12.

Summary

Computes the indices of the min elements of the input tensor’s element along the provided axis. The resulting tensor has the same rank as the input if keepdims equals 1. If keepdims equal 0, then the resulting tensor has the reduced dimension pruned. If select_last_index is True (default False), the index of the last occurrence of the min is selected if the min appears more than once in the input. Otherwise the index of the first occurrence is selected. The type of the output tensor is integer.

Attributes

  • axis - INT (default is '0'):

    The axis in which to compute the arg indices. Accepted range is [-r, r-1] where r = rank(data).

  • keepdims - INT (default is '1'):

    Keep the reduced dimension or not, default 1 means keep reduced dimension.

  • select_last_index - INT (default is '0'):

    Whether to select the last index or the first index if the {name} appears in multiple indices, default is False (first index).

Inputs

  • data (heterogeneous) - T:

    An input tensor.

Outputs

  • reduced (heterogeneous) - tensor(int64):

    Reduced output tensor with integer data type.

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 and output types to all numeric tensors.

ArgMin - 11

Version

  • name: ArgMin (GitHub)

  • domain: main

  • since_version: 11

  • function: False

  • support_level: SupportType.COMMON

  • shape inference: True

This version of the operator has been available since version 11.

Summary

Computes the indices of the min elements of the input tensor’s element along the provided axis. The resulting tensor has the same rank as the input if keepdims equals 1. If keepdims equal 0, then the resulting tensor has the reduced dimension pruned. The input tensor must not be empty. The type of the output tensor is integer.

Attributes

  • axis - INT (default is '0'):

    The axis in which to compute the arg indices. Accepted range is [-r, r-1] where r = rank(data).

  • keepdims - INT (default is '1'):

    Keep the reduced dimension or not, default 1 means keep reduced dimension.

Inputs

  • data (heterogeneous) - T:

    An input tensor.

Outputs

  • reduced (heterogeneous) - tensor(int64):

    Reduced output tensor with integer data type.

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 and output types to all numeric tensors.

ArgMin - 1

Version

  • name: ArgMin (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

Computes the indices of the min elements of the input tensor’s element along the provided axis. The resulting tensor has the same rank as the input if keepdims equals 1. If keepdims equal 0, then the resulted tensor have the reduced dimension pruned. The type of the output tensor is integer.

Attributes

  • axis - INT (default is '0'):

    The axis in which to compute the arg indices.

  • keepdims - INT (default is '1'):

    Keep the reduced dimension or not, default 1 means keep reduced dimension.

Inputs

  • data (heterogeneous) - T:

    An input tensor.

Outputs

  • reduced (heterogeneous) - tensor(int64):

    Reduced output tensor with integer data type.

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 and output types to all numeric tensors.