Splits a tensor into multiple sub-tensors, all of which are views of input, along dimension dim according to the indices or number of sections specified by indices_or_sections. This function is based on NumPy’s numpy.array_split().
>>> x = torch.arange(8)
>>> torch.tensor_split(x, 3)
(tensor([0, 1, 2]), tensor([3, 4, 5]), tensor([6, 7]))
>>> x = torch.arange(7)
>>> torch.tensor_split(x, 3)
(tensor([0, 1, 2]), tensor([3, 4]), tensor([5, 6]))
>>> torch.tensor_split(x, (1, 6))
(tensor([0]), tensor([1, 2, 3, 4, 5]), tensor([6]))
>>> x = torch.arange(14).reshape(2, 7)
>>> x
tensor([[ 0, 1, 2, 3, 4, 5, 6],
[ 7, 8, 9, 10, 11, 12, 13]])
>>> torch.tensor_split(x, 3, dim=1)
(tensor([[0, 1, 2],
[7, 8, 9]]),
tensor([[ 3, 4],
[10, 11]]),
tensor([[ 5, 6],
[12, 13]]))
>>> torch.tensor_split(x, (1, 6), dim=1)
(tensor([[0],
[7]]),
tensor([[ 1, 2, 3, 4, 5],
[ 8, 9, 10, 11, 12]]),
tensor([[ 6],
[13]]))
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