(l-onnx-doc-Transpose)=

# Transpose


(l-onnx-op-transpose-21)=

## Transpose - 21

### Version

- **name**: [Transpose (GitHub)](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Transpose)
- **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.

```{toctree}
text_diff_Transpose_13_21
```

(l-onnx-op-transpose-13)=

## Transpose - 13

### Version

- **name**: [Transpose (GitHub)](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Transpose)
- **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.

```{toctree}
text_diff_Transpose_1_21
text_diff_Transpose_1_13
```

(l-onnx-op-transpose-1)=

## Transpose - 1

### Version

- **name**: [Transpose (GitHub)](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Transpose)
- **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.