(l-onnx-doc-Flatten)=

# Flatten


(l-onnx-op-flatten-23)=

## Flatten - 23

### Version

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

Flattens the input tensor into a 2D matrix. If input tensor has shape
(d_0, d_1, ... d_n) then the output will have shape
(d_0 X d_1 ... d_(axis-1), d_axis X d_(axis+1) ... X dn).

### Attributes

* **axis - INT** (default is `'1'`):

  Indicate up to which input dimensions (exclusive) should be flattened to the outer dimension of the output. The value for axis must be in the range [-r, r], where r is the rank of the input tensor. Negative value means counting dimensions from the back. When axis = 0, the shape of the output tensor is (1, (d_0 X d_1 ... d_n), where the shape of the input tensor is (d_0, d_1, ... d_n).

### Inputs

- **input** (heterogeneous) - **T**:

  A tensor of rank >= axis.

### Outputs

- **output** (heterogeneous) - **T**:

  A 2D tensor with the contents of the input tensor, with input dimensions up to axis flattened to the outer dimension of the output and remaining input dimensions flattened into the inner dimension of the 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 to all tensor types up to IRv10.

```{toctree}
text_diff_Flatten_21_23
```

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

## Flatten - 21

### Version

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

Flattens the input tensor into a 2D matrix. If input tensor has shape
(d_0, d_1, ... d_n) then the output will have shape
(d_0 X d_1 ... d_(axis-1), d_axis X d_(axis+1) ... X dn).

### Attributes

* **axis - INT** (default is `'1'`):

  Indicate up to which input dimensions (exclusive) should be flattened to the outer dimension of the output. The value for axis must be in the range [-r, r], where r is the rank of the input tensor. Negative value means counting dimensions from the back. When axis = 0, the shape of the output tensor is (1, (d_0 X d_1 ... d_n), where the shape of the input tensor is (d_0, d_1, ... d_n).

### Inputs

- **input** (heterogeneous) - **T**:

  A tensor of rank >= axis.

### Outputs

- **output** (heterogeneous) - **T**:

  A 2D tensor with the contents of the input tensor, with input dimensions up to axis flattened to the outer dimension of the output and remaining input dimensions flattened into the inner dimension of the 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 to all tensor types up to IRv10.

```{toctree}
text_diff_Flatten_13_23
text_diff_Flatten_13_21
```

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

## Flatten - 13

### Version

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

Flattens the input tensor into a 2D matrix. If input tensor has shape
(d_0, d_1, ... d_n) then the output will have shape
(d_0 X d_1 ... d_(axis-1), d_axis X d_(axis+1) ... X dn).

### Attributes

* **axis - INT** (default is `'1'`):

  Indicate up to which input dimensions (exclusive) should be flattened to the outer dimension of the output. The value for axis must be in the range [-r, r], where r is the rank of the input tensor. Negative value means counting dimensions from the back. When axis = 0, the shape of the output tensor is (1, (d_0 X d_1 ... d_n), where the shape of the input tensor is (d_0, d_1, ... d_n).

### Inputs

- **input** (heterogeneous) - **T**:

  A tensor of rank >= axis.

### Outputs

- **output** (heterogeneous) - **T**:

  A 2D tensor with the contents of the input tensor, with input dimensions up to axis flattened to the outer dimension of the output and remaining input dimensions flattened into the inner dimension of the 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 to all tensor types.

```{toctree}
text_diff_Flatten_11_23
text_diff_Flatten_11_21
text_diff_Flatten_11_13
```

(l-onnx-op-flatten-11)=

## Flatten - 11

### Version

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

Flattens the input tensor into a 2D matrix. If input tensor has shape
(d_0, d_1, ... d_n) then the output will have shape
(d_0 X d_1 ... d_(axis-1), d_axis X d_(axis+1) ... X dn).

### Attributes

* **axis - INT** (default is `'1'`):

  Indicate up to which input dimensions (exclusive) should be flattened to the outer dimension of the output. The value for axis must be in the range [-r, r], where r is the rank of the input tensor. Negative value means counting dimensions from the back. When axis = 0, the shape of the output tensor is (1, (d_0 X d_1 ... d_n), where the shape of the input tensor is (d_0, d_1, ... d_n).

### Inputs

- **input** (heterogeneous) - **T**:

  A tensor of rank >= axis.

### Outputs

- **output** (heterogeneous) - **T**:

  A 2D tensor with the contents of the input tensor, with input dimensions up to axis flattened to the outer dimension of the output and remaining input dimensions flattened into the inner dimension of the 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 to all tensor types.

```{toctree}
text_diff_Flatten_9_23
text_diff_Flatten_9_21
text_diff_Flatten_9_13
text_diff_Flatten_9_11
```

(l-onnx-op-flatten-9)=

## Flatten - 9

### Version

- **name**: [Flatten (GitHub)](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Flatten)
- **domain**: `main`
- **since_version**: `9`
- **function**: `False`
- **support_level**: `SupportType.COMMON`
- **shape inference**: `True`

This version of the operator has been available
**since version 9**.

### Summary

Flattens the input tensor into a 2D matrix. If input tensor has shape
(d_0, d_1, ... d_n) then the output will have shape
(d_0 X d_1 ... d_(axis-1), d_axis X d_(axis+1) ... X dn).

### Attributes

* **axis - INT** (default is `'1'`):

  Indicate up to which input dimensions (exclusive) should be flattened to the outer dimension of the output. The value for axis must be in the range [0, R], where R is the rank of the input tensor. When axis = 0, the shape of the output tensor is (1, (d_0 X d_1 ... d_n), where the shape of the input tensor is (d_0, d_1, ... d_n).

### Inputs

- **input** (heterogeneous) - **T**:

  A tensor of rank >= axis.

### Outputs

- **output** (heterogeneous) - **T**:

  A 2D tensor with the contents of the input tensor, with input dimensions up to axis flattened to the outer dimension of the output and remaining input dimensions flattened into the inner dimension of the 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 to all tensor types.

```{toctree}
text_diff_Flatten_1_23
text_diff_Flatten_1_21
text_diff_Flatten_1_13
text_diff_Flatten_1_11
text_diff_Flatten_1_9
```

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

## Flatten - 1

### Version

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

Flattens the input tensor into a 2D matrix. If input tensor has shape
(d_0, d_1, ... d_n) then the output will have shape
(d_0 X d_1 ... d_(axis-1), d_axis X d_(axis+1) ... X dn).

### Attributes

* **axis - INT** (default is `'1'`):

  Indicate up to which input dimensions (exclusive) should be flattened to the outer dimension of the output. The value for axis must be in the range [0, R], where R is the rank of the input tensor. When axis = 0, the shape of the output tensor is (1, (d_0 X d_1 ... d_n), where the shape of the input tensor is (d_0, d_1, ... d_n).

### Inputs

- **input** (heterogeneous) - **T**:

  A tensor of rank >= axis.

### Outputs

- **output** (heterogeneous) - **T**:

  A 2D tensor with the contents of the input tensor, with input dimensions up to axis flattened to the outer dimension of the output and remaining input dimensions flattened into the inner dimension of the output.

### Type Constraints

* **T** in ( `tensor(double)`, `tensor(float)`, `tensor(float16)` ):

  Constrain input and output types to float tensors.