# not_equal#

ivy.not_equal(x1, x2, /, *, out=None)[source]#

Compute the truth value of `x1_i != x2_i` for each element `x1_i` of the input array `x1` with the respective element `x2_i` of the input array `x2`.

Special Cases

For real-valued floating-point operands,

• If `x1_i` is `NaN` or `x2_i` is `NaN`, the result is `True`.

• If `x1_i` is `+infinity` and `x2_i` is `-infinity`, the result is `True`.

• If `x1_i` is `-infinity` and `x2_i` is `+infinity`, the result is `True`.

• If `x1_i` is a finite number, `x2_i` is a finite number, and `x1_i` does not equal `x2_i`, the result is `True`.

• In the remaining cases, the result is `False`.

For complex floating-point operands, let `a = real(x1_i)`, `b = imag(x1_i)`, `c = real(x2_i)`, `d = imag(x2_i)`, and

• If `a`, `b`, `c`, or `d` is `NaN`, the result is `True`.

• In the remaining cases, the result is the logical OR of the equality comparison between the real values `a` and `c` (real components) and between the real values `b` and `d` (imaginary components), as described above for real-valued floating-point operands (i.e., `a != c OR b != d`).

Parameters:
• x1 (`Union`[`float`, `Array`, `NativeArray`, `Container`]) – first input array. Should have a numeric data type.

• x2 (`Union`[`float`, `Array`, `NativeArray`, `Container`]) – second input array. Must be compatible with `x1` (see ref:broadcasting). Should have a numeric data type.

• 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 element-wise results. The returned array must have a data type of `bool`.

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` inputs:

```>>> x1 = ivy.array([1, 0, 1, 1])
>>> x2 = ivy.array([1, 0, 0, -1])
>>> y = ivy.not_equal(x1, x2)
>>> print(y)
ivy.array([False, False, True, True])
```
```>>> x1 = ivy.array([1, 0, 1, 0])
>>> x2 = ivy.array([0, 1, 0, 1])
>>> y = ivy.not_equal(x1, x2)
>>> print(y)
ivy.array([True, True, True, True])
```
```>>> x1 = ivy.array([1, -1, 1, -1])
>>> x2 = ivy.array([0, -1, 1, 0])
>>> y = ivy.zeros(4)
>>> ivy.not_equal(x1, x2, out=y)
>>> print(y)
ivy.array([1., 0., 0., 1.])
```
```>>> x1 = ivy.array([1, -1, 1, -1])
>>> x2 = ivy.array([0, -1, 1, 0])
>>> y = ivy.not_equal(x1, x2, out=x1)
>>> print(y)
ivy.array([1, 0, 0, 1])
```

With a mix of `ivy.Array` and `ivy.NativeArray` inputs:

```>>> x1 = ivy.native_array([1, 2])
>>> x2 = ivy.array([1, 2])
>>> y = ivy.not_equal(x1, x2)
>>> print(y)
ivy.array([False, False])
```
```>>> x1 = ivy.native_array([1, -1])
>>> x2 = ivy.array([0, 1])
>>> y = ivy.not_equal(x1, x2)
>>> print(y)
ivy.array([True, True])
```
```>>> x1 = ivy.native_array([1, -1, 1, -1])
>>> x2 = ivy.native_array([0, -1, 1, 0])
>>> y = ivy.zeros(4)
>>> ivy.not_equal(x1, x2, out=y)
>>> print(y)
ivy.array([1., 0., 0., 1.])
```
```>>> x1 = ivy.native_array([1, 2, 3, 4])
>>> x2 = ivy.native_array([0, 2, 3, 4])
>>> y = ivy.zeros(4)
>>> ivy.not_equal(x1, x2, out=y)
>>> print(y)
ivy.array([1., 0., 0., 0.])
```

With `ivy.Container` input:

```>>> x1 = ivy.Container(a=ivy.array([1, 0, 3]),
...                    b=ivy.array([1, 2, 3]),
...                    c=ivy.native_array([1, 2, 4]))
>>> x2 = ivy.Container(a=ivy.array([1, 2, 3]),
...                    b=ivy.array([1, 2, 3]),
...                    c=ivy.native_array([1, 2, 4]))
>>> y = ivy.not_equal(x1, x2)
>>> print(y)
{
a: ivy.array([False, True, False]),
b: ivy.array([False, False, False]),
c: ivy.array([False, False, False])
}
```
```>>> x1 = ivy.Container(a=ivy.native_array([0, 1, 0]),
...                    b=ivy.array([1, 2, 3]),
...                    c=ivy.native_array([1.0, 2.0, 4.0]))
>>> x2 = ivy.Container(a=ivy.array([1, 2, 3]),
...                    b=ivy.native_array([1.1, 2.1, 3.1]),
...                    c=ivy.native_array([1, 2, 4]))
>>> y = ivy.not_equal(x1, x2)
>>> print(y)
{
a: ivy.array([True, True, True]),
b: ivy.array([True, True, True]),
c: ivy.array([False, False, False])
}
```

With a mix of `ivy.Array` and `ivy.Container` inputs:

```>>> x1 = ivy.Container(a=ivy.array([1, 2, 3]),
...                    b=ivy.array([1, 3, 5]))
>>> x2 = ivy.Container(a=ivy.array([1, 2, 3]),
...                    b=ivy.array([1, 4, 5]))
>>> y = ivy.not_equal(x1, x2)
>>> print(y)
{
a: ivy.array([False, False, False]),
b: ivy.array([False, True, False])
}
```
```>>> x1 = ivy.Container(a=ivy.array([1.0, 2.0, 3.0]),
...                    b=ivy.array([1, 4, 5]))
>>> x2 = ivy.Container(a=ivy.array([1, 2, 3.0]),
...                    b=ivy.array([1.0, 4.0, 5.0]))
>>> y = ivy.not_equal(x1, x2)
>>> print(y)
{
a: ivy.array([False, False, False]),
b: ivy.array([False, False, False])
}
```
Array.not_equal(self, x2, /, *, out=None)[source]#

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

Parameters:
• self (`Array`) – first input array. May have any data type.

• x2 (`Union`[`float`, `Array`, `NativeArray`]) – second input array. Must be compatible with `self` (see broadcasting).

• 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 element-wise results. The returned array must have a data type of `bool`.

Examples

With `ivy.Array` inputs:

```>>> x1 = ivy.array([2., 7., 9.])
>>> x2 = ivy.array([1., 7., 9.])
>>> y = x1.not_equal(x2)
>>> print(y)
ivy.array([True, False, False])
```

With mixed `ivy.Array` and `ivy.NativeArray` inputs:

```>>> x1 = ivy.array([2.5, 7.3, 9.375])
>>> x2 = ivy.native_array([2.5, 2.9, 9.375])
>>> y = x1.not_equal(x2)
>>> print(y)
ivy.array([False, True,  False])
```

With mixed `ivy.Array` and float inputs:

```>>> x1 = ivy.array([2.5, 7.3, 9.375])
>>> x2 = 7.3
>>> y = x1.not_equal(x2)
>>> print(y)
ivy.array([True, False, True])
```

With mixed `ivy.Container` and `ivy.Array` inputs:

```>>> x1 = ivy.array([3., 1., 0.9])
>>> x2 = ivy.Container(a=ivy.array([12., 3.5, 6.3]), b=ivy.array([3., 1., 0.9]))
>>> y = x1.not_equal(x2)
>>> print(y)
{
a: ivy.array([True, True, True]),
b: ivy.array([False, False, False])
}
```
Container.not_equal(self, x2, /, *, key_chains=None, to_apply=True, prune_unapplied=False, map_sequences=False, out=None)[source]#

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

Parameters:
• self (`Container`) – input array or container. May have any data type.

• x2 (`Union`[`Container`, `Array`, `NativeArray`]) – input array or container. Must be compatible with `self` (see broadcasting). May have any data type.

• 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 element-wise results. The returned container must have a data type of `bool`.

Examples

With `ivy.Container` inputs:

```>>> x1 = ivy.Container(a=ivy.array([12, 3.5, 6.3]), b=ivy.array([3., 1., 0.9]))
>>> x2 = ivy.Container(a=ivy.array([12, 2.3, 3]), b=ivy.array([2.4, 3., 2.]))
>>> y = x1.not_equal(x2)
>>> print(y)
{
a: ivy.array([False, True, True]),
b: ivy.array([True, True, True])
}
```

With mixed `ivy.Container` and `ivy.Array` inputs:

```>>> x1 = ivy.Container(a=ivy.array([12., 3.5, 6.3]), b=ivy.array([3., 1., 0.9]))
>>> x2 = ivy.array([3., 1., 0.9])
>>> y = x1.not_equal(x2)
>>> print(y)
{
a: ivy.array([True, True, True]),
b: ivy.array([False, False, False])
}
```