torch.combinations

torch.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) – 1D vector.

• r (int, optional) – number of elements to combine

• with_replacement (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

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 = torch.tensor(a)
>>> torch.combinations(tensor_a)
tensor([[1, 2],
        [1, 3],
        [2, 3]])
>>> torch.combinations(tensor_a, r=3)
tensor([[1, 2, 3]])
>>> torch.combinations(tensor_a, with_replacement=True)
tensor([[1, 1],
        [1, 2],
        [1, 3],
        [2, 2],
        [2, 3],
        [3, 3]])