# round#

ivy.round(x, /, *, decimals=0, out=None)[source]#

Round each element `x_i` of the input array `x` to the nearest integer-valued number.

Note

For complex floating-point operands, real and imaginary components must be independently rounded to the nearest integer-valued number.

Rounded real and imaginary components must be equal to their equivalent rounded real-valued floating-point counterparts (i.e., for complex-valued `x`, `real(round(x))` must equal `round(real(x)))` and `imag(round(x))` must equal `round(imag(x))`).

Special cases

• If `x_i` is already an integer-valued, the result is `x_i`.

For floating-point operands,

• If `x_i` is `+infinity`, the result is `+infinity`.

• If `x_i` is `-infinity`, the result is `-infinity`.

• If `x_i` is `+0`, the result is `+0`.

• If `x_i` is `-0`, the result is `-0`.

• If `x_i` is `NaN`, the result is `NaN`.

• If two integers are equally close to `x_i`, the result is the even integer closest to `x_i`.

Note

For complex floating-point operands, the following special cases apply to real and imaginary components independently (e.g., if `real(x_i)` is `NaN`, the rounded real component is `NaN`).

• If `x_i` is already integer-valued, the result is `x_i`.

Parameters:
• x (`Union`[`Array`, `NativeArray`]) – input array containing elements to round.

• decimals (`Optional`[`int`], default: `0`) – number of decimal places to round to. Default is `0`.

• out (`Optional`[`Array`], default: `None`) – optional output array, for writing the result to. It must have a shape that the inputs broadcast to.

Return type:

`Array`

Returns:

ret – An array of the same shape and type as x, with the elements rounded to integers.

Note: PyTorch supports an additional argument `decimals` for the round function. It has been deliberately omitted here due to the imprecise nature of the argument in `torch.round`.

This function conforms to the Array API Standard. This docstring is an extension of the docstring in the standard.

Both the description and the type hints above assumes an array input for simplicity, but this function is nestable, and therefore also accepts `ivy.Container` instances in place of any of the arguments.

Examples

With `ivy.Array` input:

```>>> x = ivy.array([1.2, 2.4, 3.6])
>>> y = ivy.round(x)
>>> print(y)
ivy.array([1.,2.,4.])
```
```>>> x = ivy.array([-0, 5, 4.5])
>>> y = ivy.round(x)
>>> print(y)
ivy.array([0.,5.,4.])
```
```>>> x = ivy.array([1.5654, 2.034, 15.1, -5.0])
>>> y = ivy.zeros(4)
>>> ivy.round(x, out=y)
>>> print(y)
ivy.array([2.,2.,15.,-5.])
```
```>>> x = ivy.array([[0, 5.433, -343.3, 1.5],
...                [-5.5, 44.2, 11.5, 12.01]])
>>> ivy.round(x, out=x)
>>> print(x)
ivy.array([[0.,5.,-343.,2.],[-6.,44.,12.,12.]])
```

With `ivy.Container` input:

```>>> x = ivy.Container(a=ivy.array([4.20, 8.6, 6.90, 0.0]),
...                   b=ivy.array([-300.9, -527.3, 4.5]))
>>> y = ivy.round(x)
>>> print(y)
{
a:ivy.array([4.,9.,7.,0.]),
b:ivy.array([-301.,-527.,4.])
}
```
Array.round(self, *, decimals=0, out=None)[source]#

ivy.Array instance method variant of ivy.round. This method simply wraps the function, and so the docstring for ivy.round also applies to this method with minimal changes.

Parameters:
• self (`Array`) – input array. Should have a numeric data type.

• decimals (`int`, default: `0`) – number of decimal places to round to. Default is `0`.

• out (`Optional`[`Array`], default: `None`) – optional output array, for writing the result to. It must have a shape that the inputs broadcast to.

Return type:

`Array`

Returns:

ret – an array containing the rounded result for each element in `self`. The returned array must have the same data type as `self`.

Examples

Using `ivy.Array` instance method:

```>>> x = ivy.array([6.3, -8.1, 0.5, -4.2, 6.8])
>>> y = x.round()
>>> print(y)
ivy.array([ 6., -8.,  0., -4.,  7.])
```
```>>> x = ivy.array([-94.2, 256.0, 0.0001, -5.5, 36.6])
>>> y = x.round()
>>> print(y)
ivy.array([-94., 256., 0., -6., 37.])
```
```>>> x = ivy.array([0.23, 3., -1.2])
>>> y = ivy.zeros(3)
>>> x.round(out=y)
>>> print(y)
ivy.array([ 0.,  3., -1.])
```
```>>> x = ivy.array([[ -1., -67.,  0.,  15.5,  1.], [3, -45, 24.7, -678.5, 32.8]])
>>> y = x.round()
>>> print(y)
ivy.array([[-1., -67., 0., 16., 1.],
[3., -45., 25., -678., 33.]])
```
Container.round(self, *, decimals=0, key_chains=None, to_apply=True, prune_unapplied=False, map_sequences=False, out=None)[source]#

ivy.Container instance method variant of ivy.round. This method simply wraps the function, and so the docstring for ivy.round also applies to this method with minimal changes.

Parameters:
• self (`Container`) – input container. Should have a numeric data type.

• decimals (`Union`[`int`, `Container`], default: `0`) – number of decimal places to round to. Default is `0`.

• key_chains (`Optional`[`Union`[`List`[`str`], `Dict`[`str`, `str`], `Container`]], default: `None`) – The key-chains to apply or not apply the method to. Default is `None`.

• to_apply (`Union`[`bool`, `Container`], default: `True`) – If True, the method will be applied to key_chains, otherwise key_chains will be skipped. Default is `True`.

• prune_unapplied (`Union`[`bool`, `Container`], default: `False`) – Whether to prune key_chains for which the function was not applied. Default is `False`.

• map_sequences (`Union`[`bool`, `Container`], default: `False`) – Whether to also map method to sequences (lists, tuples). Default is `False`.

• out (`Optional`[`Container`], default: `None`) – optional output container, for writing the result to. It must have a shape that the inputs broadcast to.

Return type:

`Container`

Returns:

ret – a container containing the rounded result for each element in `self`. The returned container must have the same data type as `self`.

Examples

With `ivy.Container` input:

```>>> x = ivy.Container(a=ivy.array([4.20, 8.6, 6.90, 0.0]),
...                   b=ivy.array([-300.9, -527.3, 4.5]))
>>> y = x.round()
>>> print(y)
{
a: ivy.array([4., 9., 7., 0.]),
b: ivy.array([-301., -527., 4.])
}
```