# Transpose¶

## Transpose - 23¶

### Version¶

• name: Transpose (GitHub)

• domain: main

• since_version: 23

• function: False

• support_level: SupportType.COMMON

• shape inference: True

This version of the operator has been available since version 23.

### Summary¶

Transpose the input tensor similar to numpy.transpose. For example, when perm=(1, 0, 2), given an input tensor of shape (1, 2, 3), the output shape will be (2, 1, 3).

### Attributes¶

• perm - INTS :

A list of integers. By default, reverse the dimensions, otherwise permute the axes according to the values given. Its length must be equal to the rank of the input.

### Inputs¶

• data (heterogeneous) - T:

An input tensor.

### Outputs¶

• transposed (heterogeneous) - T:

Transposed output.

### Type Constraints¶

• T in ( tensor(bfloat16), tensor(bool), tensor(complex128), tensor(complex64), tensor(double), tensor(float), tensor(float16), tensor(float4e2m1), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint4), tensor(uint64), tensor(uint8) ):

Constrain input and output types to all tensor types.

## Transpose - 21¶

### Version¶

• name: Transpose (GitHub)

• domain: main

• since_version: 21

• function: False

• support_level: SupportType.COMMON

• shape inference: True

This version of the operator has been available since version 21.

### Summary¶

Transpose the input tensor similar to numpy.transpose. For example, when perm=(1, 0, 2), given an input tensor of shape (1, 2, 3), the output shape will be (2, 1, 3).

### Attributes¶

• perm - INTS :

A list of integers. By default, reverse the dimensions, otherwise permute the axes according to the values given. Its length must be equal to the rank of the input.

### Inputs¶

• data (heterogeneous) - T:

An input tensor.

### Outputs¶

• transposed (heterogeneous) - T:

Transposed output.

### Type Constraints¶

• T in ( tensor(bfloat16), tensor(bool), tensor(complex128), tensor(complex64), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint4), tensor(uint64), tensor(uint8) ):

Constrain input and output types to all tensor types.

## Transpose - 13¶

### Version¶

• name: Transpose (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¶

Transpose the input tensor similar to numpy.transpose. For example, when perm=(1, 0, 2), given an input tensor of shape (1, 2, 3), the output shape will be (2, 1, 3).

### Attributes¶

• perm - INTS :

A list of integers. By default, reverse the dimensions, otherwise permute the axes according to the values given.

### Inputs¶

• data (heterogeneous) - T:

An input tensor.

### Outputs¶

• transposed (heterogeneous) - T:

Transposed output.

### 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.

## Transpose - 1¶

### Version¶

• name: Transpose (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¶

Transpose the input tensor similar to numpy.transpose. For example, when perm=(1, 0, 2), given an input tensor of shape (1, 2, 3), the output shape will be (2, 1, 3).

### Attributes¶

• perm - INTS :

A list of integers. By default, reverse the dimensions, otherwise permute the axes according to the values given.

### Inputs¶

• data (heterogeneous) - T:

An input tensor.

### Outputs¶

• transposed (heterogeneous) - T:

Transposed output.

### 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.