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# Round


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## Round - 22

### Version

- **name**: [Round (GitHub)](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Round)
- **domain**: `main`
- **since_version**: `22`
- **function**: `False`
- **support_level**: `SupportType.COMMON`
- **shape inference**: `True`

This version of the operator has been available
**since version 22**.

### Summary

Round takes one input Tensor and rounds the values, element-wise, meaning
it finds the nearest integer for each value.
In case of halves, the rule is to round them to the nearest even integer.
If input x is integral, +0, -0, NaN,  or infinite, x itself is returned.
The output tensor has the same shape and type as the input.

Examples:
```
round([0.9]) = [1.0]
round([2.5]) = [2.0]
round([2.3]) = [2.0]
round([1.5]) = [2.0]
round([-4.5]) = [-4.0]
```

### Inputs

- **X** (heterogeneous) - **T**:

  Input tensor

### Outputs

- **Y** (heterogeneous) - **T**:

  Output tensor

### Type Constraints

* **T** in ( `tensor(bfloat16)`, `tensor(double)`, `tensor(float)`, `tensor(float16)` ):

  Constrain input and output types to float tensors.

```{toctree}
text_diff_Round_11_22
```

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

## Round - 11

### Version

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

Round takes one input Tensor and rounds the values, element-wise, meaning
it finds the nearest integer for each value.
In case of halves, the rule is to round them to the nearest even integer.
If input x is integral, +0, -0, NaN,  or infinite, x itself is returned.
The output tensor has the same shape and type as the input.

Examples:
```
round([0.9]) = [1.0]
round([2.5]) = [2.0]
round([2.3]) = [2.0]
round([1.5]) = [2.0]
round([-4.5]) = [-4.0]
```

### Inputs

- **X** (heterogeneous) - **T**:

  Input tensor

### Outputs

- **Y** (heterogeneous) - **T**:

  Output tensor

### Type Constraints

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

  Constrain input and output types to float tensors.