(l-onnx-doc-Sign)=

# Sign


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

## Sign - 13

### Version

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

Calculate the sign of the given input tensor element-wise.
If input > 0, output 1. if input < 0, output -1. if input == 0, output 0.

### Inputs

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

  Input tensor

### Outputs

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

  The sign of the input tensor computed element-wise. It has the same shape and type of the input.

### Type Constraints

* **T** in ( `tensor(bfloat16)`, `tensor(double)`, `tensor(float)`, `tensor(float16)`, `tensor(int16)`, `tensor(int32)`, `tensor(int64)`, `tensor(int8)`, `tensor(uint16)`, `tensor(uint32)`, `tensor(uint64)`, `tensor(uint8)` ):

  Constrain input and output types to all numeric tensors.

```{toctree}
text_diff_Sign_9_13
```

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

## Sign - 9

### Version

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

Calculate the sign of the given input tensor element-wise.
If input > 0, output 1. if input < 0, output -1. if input == 0, output 0.

### Inputs

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

  Input tensor

### Outputs

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

  The sign of the input tensor computed element-wise. It has the same shape and type of the input.

### Type Constraints

* **T** in ( `tensor(double)`, `tensor(float)`, `tensor(float16)`, `tensor(int16)`, `tensor(int32)`, `tensor(int64)`, `tensor(int8)`, `tensor(uint16)`, `tensor(uint32)`, `tensor(uint64)`, `tensor(uint8)` ):

  Constrain input and output types to all numeric tensors.