# 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.