Tile

Tile - 13

Version

  • name: Tile (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

Constructs a tensor by tiling a given tensor. This is the same as function tile in Numpy, but no broadcast. For example A = [[1, 2], [3, 4]], B = [1, 2], tile(A, B) = [[1, 2, 1, 2], [3, 4, 3, 4]]

Inputs

  • input (heterogeneous) - T:

    Input tensor of any shape.

  • repeats (heterogeneous) - T1:

    1D int64 tensor of the same length as input’s dimension number, includes numbers of repeated copies along input’s dimensions.

Outputs

  • output (heterogeneous) - T:

    Output tensor of the same dimensions and type as tensor input. output_dim[i] = input_dim[i] * repeats[i]

Type Constraints

  • T in ( tensor(bfloat16), tensor(bool), tensor(complex128), tensor(complex64), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) ):

    Constrain input and output types to all tensor types.

  • T1 in ( tensor(int64) ):

    Constrain repeat’s type to int64 tensors.

Tile - 6

Version

  • name: Tile (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

Constructs a tensor by tiling a given tensor. This is the same as function tile in Numpy, but no broadcast. For example A = [[1, 2], [3, 4]], B = [1, 2], tile(A, B) = [[1, 2, 1, 2], [3, 4, 3, 4]]

Inputs

  • input (heterogeneous) - T:

    Input tensor of any shape.

  • repeats (heterogeneous) - T1:

    1D int64 tensor of the same length as input’s dimension number, includes numbers of repeated copies along input’s dimensions.

Outputs

  • output (heterogeneous) - T:

    Output tensor of the same dimensions and type as tensor input. output_dim[i] = input_dim[i] * repeats[i]

Type Constraints

  • T in ( tensor(bool), tensor(complex128), tensor(complex64), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) ):

    Constrain input and output types to all tensor types.

  • T1 in ( tensor(int64) ):

    Constrain repeat’s type to int64 tensors.

Tile - 1

Version

  • name: Tile (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

Repeat the elements of a tensor along an axis.

Inputs

  • input (heterogeneous) - T:

    Input tensor of any shape.

  • tiles (heterogeneous) - T:

    Number of repeated copies to make of the input tensor.

  • axis (heterogeneous) - T:

    Axis along which to repeat.

Outputs

  • output (heterogeneous) - T:

    Output tensor of same shape and type as input.

Type Constraints

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

    Constrain input types to float tensors.

  • T1 in ( tensor(int64) ):

    Constrain tiles and axis’s type to int64 tensors.