# tensorplay.functional.combinations

Source: https://www.tensorplay.cn/docs/generated/tensorplay.functional.combinations.html

```python
tensorplay.functional.combinations(input: Tensor, r: int = 2, with_replacement: bool = False) → seq
```

Compute combinations of length $r$ of the given tensor. The behavior is similar to
python’s itertools.combinations when with_replacement is set to False, and
itertools.combinations_with_replacement when with_replacement is set to True.

Parameters:

- input ([Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor)) – 1D vector.

- r ([int](https://docs.python.org/3/builtins/functions.html#int), optional) – number of elements to combine

- with_replacement ([bool](https://docs.python.org/3/builtins/functions.html#bool), optional) – whether to allow duplication in combination

Returns:

A tensor equivalent to converting all the input tensors into lists, do
itertools.combinations or itertools.combinations_with_replacement on these
lists, and finally convert the resulting list into tensor.

Return type:

[Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor)

Example:

```
>>> a = [1, 2, 3]
>>> list(itertools.combinations(a, r=2))
[(1, 2), (1, 3), (2, 3)]
>>> list(itertools.combinations(a, r=3))
[(1, 2, 3)]
>>> list(itertools.combinations_with_replacement(a, r=2))
[(1, 1), (1, 2), (1, 3), (2, 2), (2, 3), (3, 3)]
>>> tensor_a = tensorplay.tensor(a)
>>> tensorplay.combinations(tensor_a)
tensor([[1, 2],
        [1, 3],
        [2, 3]])
>>> tensorplay.combinations(tensor_a, r=3)
tensor([[1, 2, 3]])
>>> tensorplay.combinations(tensor_a, with_replacement=True)
tensor([[1, 1],
        [1, 2],
        [1, 3],
        [2, 2],
        [2, 3],
        [3, 3]])
```