TopK

TopK - 24

Version

  • name: TopK (GitHub)

  • domain: main

  • since_version: 24

  • function: False

  • support_level: SupportType.COMMON

  • shape inference: True

This version of the operator has been available since version 24.

Summary

Retrieve the top-K largest or smallest elements along a specified axis. Given an input tensor of shape [a_0, a_1, …, a_{n-1}] and integer argument k, return two outputs:

  • Value tensor of shape [a_0, a_1, …, a_{axis-1}, k, a_{axis+1}, … a_{n-1}] which contains the values of the top k elements along the specified axis

  • Index tensor of shape [a_0, a_1, …, a_{axis-1}, k, a_{axis+1}, … a_{n-1}] which contains the indices of the top k elements (original indices from the input tensor).

  • If “largest” is 1 (the default value) then the k largest elements are returned.

  • If “sorted” is 1 (the default value) then the resulting k elements will be sorted.

  • If “sorted” is 0, order of returned ‘Values’ and ‘Indices’ are undefined.

Given two equivalent values, this operator uses the indices along the axis as a tiebreaker. That is, the element with the lower index will appear first.

Attributes

  • axis - INT (default is '-1'):

    Dimension on which to do the sort. Negative value means counting dimensions from the back. Accepted range is [-r, r-1] where r = rank(input).

  • largest - INT (default is '1'):

    Whether to return the top-K largest or smallest elements.

  • sorted - INT (default is '1'):

    Whether to return the elements in sorted order.

Inputs

  • X (heterogeneous) - T:

    Tensor of shape [a_0, a_1, …, a_{n-1}]

  • K (heterogeneous) - tensor(int64):

    A 1-D tensor containing a single positive value corresponding to the number of top elements to retrieve

Outputs

  • Values (heterogeneous) - T:

    Tensor of shape [a_0, a_1, …, a_{axis-1}, k, a_{axis+1}, … a_{n-1}] containing top K values from the input tensor

  • Indices (heterogeneous) - I:

    Tensor of shape [a_0, a_1, …, a_{axis-1}, k, a_{axis+1}, … a_{n-1}] containing the corresponding input tensor indices for the top K values.

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 numeric tensors.

  • I in ( tensor(int64) ):

    Constrain index tensor to int64

TopK - 11

Version

  • name: TopK (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

Retrieve the top-K largest or smallest elements along a specified axis. Given an input tensor of shape [a_0, a_1, …, a_{n-1}] and integer argument k, return two outputs:

  • Value tensor of shape [a_0, a_1, …, a_{axis-1}, k, a_{axis+1}, … a_{n-1}] which contains the values of the top k elements along the specified axis

  • Index tensor of shape [a_0, a_1, …, a_{axis-1}, k, a_{axis+1}, … a_{n-1}] which contains the indices of the top k elements (original indices from the input tensor).

  • If “largest” is 1 (the default value) then the k largest elements are returned.

  • If “sorted” is 1 (the default value) then the resulting k elements will be sorted.

  • If “sorted” is 0, order of returned ‘Values’ and ‘Indices’ are undefined.

Given two equivalent values, this operator uses the indices along the axis as a tiebreaker. That is, the element with the lower index will appear first.

Attributes

  • axis - INT (default is '-1'):

    Dimension on which to do the sort. Negative value means counting dimensions from the back. Accepted range is [-r, r-1] where r = rank(input).

  • largest - INT (default is '1'):

    Whether to return the top-K largest or smallest elements.

  • sorted - INT (default is '1'):

    Whether to return the elements in sorted order.

Inputs

  • X (heterogeneous) - T:

    Tensor of shape [a_0, a_1, …, a_{n-1}]

  • K (heterogeneous) - tensor(int64):

    A 1-D tensor containing a single positive value corresponding to the number of top elements to retrieve

Outputs

  • Values (heterogeneous) - T:

    Tensor of shape [a_0, a_1, …, a_{axis-1}, k, a_{axis+1}, … a_{n-1}] containing top K values from the input tensor

  • Indices (heterogeneous) - I:

    Tensor of shape [a_0, a_1, …, a_{axis-1}, k, a_{axis+1}, … a_{n-1}] containing the corresponding input tensor indices for the top K values.

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 numeric tensors.

  • I in ( tensor(int64) ):

    Constrain index tensor to int64

TopK - 10

Version

  • name: TopK (GitHub)

  • domain: main

  • since_version: 10

  • function: False

  • support_level: SupportType.COMMON

  • shape inference: True

This version of the operator has been available since version 10.

Summary

Retrieve the top-K elements along a specified axis. Given an input tensor of shape [a_0, a_1, …, a_{n-1}] and integer argument k, return two outputs: -Value tensor of shape [a_0, a_1, …, a_{axis-1}, k, a_{axis+1}, … a_{n-1}] which contains the values of the top k elements along the specified axis -Index tensor of shape [a_0, a_1, …, a_{axis-1}, k, a_{axis+1}, … a_{n-1}] which contains the indices of the top k elements (original indices from the input tensor).

Given two equivalent values, this operator uses the indices along the axis as a tiebreaker. That is, the element with the lower index will appear first.

Attributes

  • axis - INT (default is '-1'):

    Dimension on which to do the sort.

Inputs

  • X (heterogeneous) - T:

    Tensor of shape [a_0, a_1, …, a_{n-1}]

  • K (heterogeneous) - tensor(int64):

    A 1-D tensor containing a single positive value corresponding to the number of top elements to retrieve

Outputs

  • Values (heterogeneous) - T:

    Tensor of shape [a_0, a_1, …, a_{axis-1}, k, a_{axis+1}, … a_{n-1}] containing top K values from the input tensor

  • Indices (heterogeneous) - I:

    Tensor of shape [a_0, a_1, …, a_{axis-1}, k, a_{axis+1}, … a_{n-1}] containing the corresponding input tensor indices for the top K values.

Type Constraints

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

    Constrain input and output types to float tensors.

  • I in ( tensor(int64) ):

    Constrain index tensor to int64

TopK - 1

Version

  • name: TopK (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

Retrieve the top-K elements along a specified axis. Given an input tensor of shape [a_0, a_1, …, a_{n-1}] and integer argument k, return two outputs: -Value tensor of shape [a_0, a_1, …, a_{axis-1}, k, a_{axis+1}, … a_{n-1}] which contains the values of the top k elements along the specified axis -Index tensor of shape [a_0, a_1, …, a_{axis-1}, k, a_{axis+1}, … a_{n-1}] which contains the indices of the top k elements (original indices from the input tensor). Given two equivalent values, this operator uses the indices along the axis as a tiebreaker. That is, the element with the lower index will appear first.

Attributes

  • axis - INT (default is '-1'):

    Dimension on which to do the sort.

  • k - INT (required) :

    Number of top elements to retrieve

Inputs

  • X (heterogeneous) - T:

    Tensor of shape [a_0, a_1, …, a_{n-1}]

Outputs

  • Values (heterogeneous) - T:

    Tensor of shape [a_0, a_1, …, a_{axis-1}, k, a_{axis+1}, … a_{n-1}] containing top K values from the input tensor

  • Indices (heterogeneous) - I:

    Tensor of shape [a_0, a_1, …, a_{axis-1}, k, a_{axis+1}, … a_{n-1}] containing the corresponding input tensor indices for the top K values.

Type Constraints

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

    Constrain input and output types to float tensors.

  • I in ( tensor(int64) ):

    Constrain index tensor to int64