*Memos:
- My post explains split().
- My post explains vsplit().
- My post explains dsplit().
- My post explains tensor_split().
- My post explains chunk().
- My post explains unbind().
hsplit() can get the one or more 1D or more D horizontally splitted view tensors of zero or more elements from the 1D or more D tensor of zero or more elements as shown below:
-
hsplit()
can be used with torch or a tensor. - The 1st argument(
input
) withtorch
or using a tensor(Required-Type:tensor
ofint
,float
,complex
orbool
). - The 2nd argument with
torch
or the 1st argument with a tensor issections
(Required-Type:int
). - The 2nd argument with
torch
or the 1st argument with a tensor isindices
(Required-Type:tuple
ofint
orlist
ofint
). - The total number of the zero or more elements of one or more returned tensors changes.
- One or more returned tensors keep the dimension of the original tensor.
import torch my_tensor = torch.tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]) torch.hsplit(input=my_tensor, sections=1) my_tensor.hsplit(sections=1) # (tensor([[0, 1, 2, 3], # [4, 5, 6, 7], # [8, 9, 10, 11]]),) torch.hsplit(input=my_tensor, sections=2) # (tensor([[0, 1], [4, 5], [8, 9]]), # tensor([[2, 3], [6, 7], [10, 11]])) torch.hsplit(input=my_tensor, sections=4) # (tensor([[0], [4], [8]]), # tensor([[1], [5], [9]]), # tensor([[2], [6], [10]]), # tensor([[3], [7], [11]])) torch.hsplit(input=my_tensor, indices=(0,)) torch.hsplit(input=my_tensor, indices=(-4,)) # (tensor([], size=(3, 0), dtype=torch.int64), # tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]])) torch.hsplit(input=my_tensor, indices=(1,)) torch.hsplit(input=my_tensor, indices=(-3,)) # (tensor([[0], [4], [8]]), # tensor([[1, 2, 3], [5, 6, 7], [9, 10, 11]])) torch.hsplit(input=my_tensor, indices=(2,)) torch.hsplit(input=my_tensor, indices=(-2,)) # (tensor([[0, 1], [4, 5], [8, 9]]), # tensor([[2, 3], [6, 7], [10, 11]])) torch.hsplit(input=my_tensor, indices=(3,)) torch.hsplit(input=my_tensor, indices=(-1,)) # (tensor([[0, 1, 2], [4, 5, 6], [8, 9, 10]]), # tensor([[3], [7], [11]])) torch.hsplit(input=my_tensor, indices=(4,)) # (tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]), # tensor([], size=(3, 0), dtype=torch.int64)) torch.hsplit(input=my_tensor, indices=(0, 0)) torch.hsplit(input=my_tensor, indices=(0, -4)) # (tensor([], size=(3, 0), dtype=torch.int64), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]])) torch.hsplit(input=my_tensor, indices=(0, 1)) torch.hsplit(input=my_tensor, indices=(0, -3)) # (tensor([], size=(3, 0), dtype=torch.int64), # tensor([[0], [4], [8]]), # tensor([[1, 2, 3], [5, 6, 7], [9, 10, 11]])) torch.hsplit(input=my_tensor, indices=(0, 2)) torch.hsplit(input=my_tensor, indices=(0, -2)) # (tensor([], size=(3, 0), dtype=torch.int64), # tensor([[0, 1], [4, 5], [8, 9]]), # tensor([[2, 3], [6, 7], [10, 11]])) torch.hsplit(input=my_tensor, indices=(0, 3)) torch.hsplit(input=my_tensor, indices=(0, -1)) # (tensor([], size=(3, 0), dtype=torch.int64), # tensor([[0, 1, 2], [4, 5, 6], [8, 9, 10]]), # tensor([[3], [7], [11]])) torch.hsplit(input=my_tensor, indices=(0, 4)) # (tensor([], size=(3, 0), dtype=torch.int64), # tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]), # tensor([], size=(3, 0), dtype=torch.int64)) torch.hsplit(input=my_tensor, indices=(1, 0)) torch.hsplit(input=my_tensor, indices=(1, -4)) # (tensor([[0], [4], [8]]), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]])) torch.hsplit(input=my_tensor, indices=(1, 1)) torch.hsplit(input=my_tensor, indices=(1, -3)) # (tensor([[0], [4], [8]]), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[1, 2, 3], [5, 6, 7], [9, 10, 11]])) torch.hsplit(input=my_tensor, indices=(1, 2)) torch.hsplit(input=my_tensor, indices=(1, -2)) # (tensor([[0], [4], [8]]), # tensor([[1], [5], [9]]), # tensor([[2, 3], [6, 7], [10, 11]])) torch.hsplit(input=my_tensor, indices=(1, 3)) torch.hsplit(input=my_tensor, indices=(1, -1)) # (tensor([[0], [4], [8]]), # tensor([[1, 2], [5, 6], [9, 10]]), # tensor([[3], [7], [11]])) torch.hsplit(input=my_tensor, indices=(1, 4)) # (tensor([[0], [4], [8]]), # tensor([[1, 2, 3], [5, 6, 7], [9, 10, 11]]), # tensor([], size=(3, 0), dtype=torch.int64)) torch.hsplit(input=my_tensor, indices=(2, 0)) torch.hsplit(input=my_tensor, indices=(2, -4)) # (tensor([[0, 1], [4, 5], [8, 9]]), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]])) torch.hsplit(input=my_tensor, indices=(2, 1)) torch.hsplit(input=my_tensor, indices=(2, -3)) # (tensor([[0, 1], [4, 5], [8, 9]]), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[1, 2, 3], [5, 6, 7], [9, 10, 11]])) torch.hsplit(input=my_tensor, indices=(2, 2)) torch.hsplit(input=my_tensor, indices=(2, -2)) # (tensor([[0, 1], [4, 5], [8, 9]]), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[2, 3], [6, 7], [10, 11]])) torch.hsplit(input=my_tensor, indices=(2, 3)) torch.hsplit(input=my_tensor, indices=(2, -1)) # (tensor([[0, 1], [4, 5], [8, 9]]), # tensor([[2], [6], [10]]), # tensor([[3], [7], [11]])) torch.hsplit(input=my_tensor, indices=(2, 4)) # (tensor([[0, 1], [4, 5], [8, 9]]), # tensor([[2, 3], [6, 7], [10, 11]]), # tensor([], size=(3, 0), dtype=torch.int64)) torch.hsplit(input=my_tensor, indices=(3, 0)) torch.hsplit(input=my_tensor, indices=(3, -4)) # (tensor([[0, 1, 2], [4, 5, 6], [8, 9, 10]]), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]])) torch.hsplit(input=my_tensor, indices=(3, 1)) torch.hsplit(input=my_tensor, indices=(3, -3)) # (tensor([[0, 1, 2], [4, 5, 6], [8, 9, 10]]), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[1, 2, 3], [5, 6, 7], [9, 10, 11]])) torch.hsplit(input=my_tensor, indices=(3, 2)) torch.hsplit(input=my_tensor, indices=(3, -2)) # (tensor([[0, 1, 2], [4, 5, 6], [8, 9, 10]]), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[2, 3], [6, 7], [10, 11]])) torch.hsplit(input=my_tensor, indices=(3, 3)) torch.hsplit(input=my_tensor, indices=(3, -1)) # (tensor([[0, 1, 2], [4, 5, 6], [8, 9, 10]]), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[3], [7], [11]])) torch.hsplit(input=my_tensor, indices=(3, 4)) # (tensor([[0, 1, 2], [4, 5, 6], [8, 9, 10]]), # tensor([[3], [7], [11]]), # tensor([], size=(3, 0), dtype=torch.int64)) torch.hsplit(input=my_tensor, indices=(4, 0)) torch.hsplit(input=my_tensor, indices=(4, -4)) # (tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]])) torch.hsplit(input=my_tensor, indices=(4, 1)) torch.hsplit(input=my_tensor, indices=(4, -3)) # (tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[1, 2, 3], [5, 6, 7], [9, 10, 11]])) torch.hsplit(input=my_tensor, indices=(4, 2)) torch.hsplit(input=my_tensor, indices=(4, -2)) # (tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[2, 3], [6, 7], [10, 11]])) torch.hsplit(input=my_tensor, indices=(4, 3)) torch.hsplit(input=my_tensor, indices=(4, -1)) # (tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[3], [7], [11]])) torch.hsplit(input=my_tensor, indices=(4, 4)) # (tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([], size=(3, 0), dtype=torch.int64)) torch.hsplit(input=my_tensor, indices=(-1, 0)) torch.hsplit(input=my_tensor, indices=(-1, -4)) # (tensor([[0, 1, 2], [4, 5, 6], [8, 9, 10]]), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]])) torch.hsplit(input=my_tensor, indices=(-1, 1)) torch.hsplit(input=my_tensor, indices=(-1, -3)) # (tensor([[0, 1, 2], [4, 5, 6], [8, 9, 10]]), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[1, 2, 3], [5, 6, 7], [9, 10, 11]])) torch.hsplit(input=my_tensor, indices=(-1, 2)) torch.hsplit(input=my_tensor, indices=(-1, -2)) # (tensor([[0, 1, 2], [4, 5, 6], [8, 9, 10]]), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[2, 3], [6, 7], [10, 11]])) torch.hsplit(input=my_tensor, indices=(-1, 3)) torch.hsplit(input=my_tensor, indices=(-1, -1)) # (tensor([[0, 1, 2], [4, 5, 6], [8, 9, 10]]), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[3], [7], [11]])) torch.hsplit(input=my_tensor, indices=(-1, 4)) # (tensor([[0, 1, 2], [4, 5, 6], [8, 9, 10]]), # tensor([[3], [7], [11]]), # tensor([], size=(3, 0), dtype=torch.int64)) torch.hsplit(input=my_tensor, indices=(-1, -1)) # (tensor([[[0, 1, 2, 3], [4, 5, 6, 7]]]), # tensor([], size=(1, 0, 4), dtype=torch.int64), # tensor([[[8, 9, 10, 11]]])) torch.hsplit(input=my_tensor, indices=(-1, -2)) # (tensor([[[0, 1, 2, 3], [4, 5, 6, 7]]]), # tensor([], size=(1, 0, 4), dtype=torch.int64), # tensor([[[4, 5, 6, 7], [8, 9, 10, 11]]])) torch.hsplit(input=my_tensor, indices=(-2, 0)) torch.hsplit(input=my_tensor, indices=(-2, -4)) # (tensor([[0, 1], [4, 5], [8, 9]]), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]])) torch.hsplit(input=my_tensor, indices=(-2, 1)) torch.hsplit(input=my_tensor, indices=(-2, -3)) # (tensor([[0, 1], [4, 5], [8, 9]]), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[1, 2, 3], [5, 6, 7], [9, 10, 11]])) torch.hsplit(input=my_tensor, indices=(-2, 2)) torch.hsplit(input=my_tensor, indices=(-2, -2)) # (tensor([[0, 1], [4, 5], [8, 9]]), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[2, 3], [6, 7], [10, 11]])) torch.hsplit(input=my_tensor, indices=(-2, 3)) torch.hsplit(input=my_tensor, indices=(-2, -1)) # (tensor([[0, 1], [4, 5], [8, 9]]), # tensor([[2], [6], [10]]), # tensor([[3], [7], [11]])) torch.hsplit(input=my_tensor, indices=(-2, 4)) # (tensor([[0, 1], [4, 5], [8, 9]]), # tensor([[2, 3], [6, 7], [10, 11]]), # tensor([], size=(3, 0), dtype=torch.int64)) torch.hsplit(input=my_tensor, indices=(-3, 0)) torch.hsplit(input=my_tensor, indices=(-3, -4)) # (tensor([[0], [4], [8]]), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]])) torch.hsplit(input=my_tensor, indices=(-3, 1)) torch.hsplit(input=my_tensor, indices=(-3, -3)) # (tensor([[0], [4], [8]]), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[1, 2, 3], [5, 6, 7], [9, 10, 11]])) torch.hsplit(input=my_tensor, indices=(-3, 2)) torch.hsplit(input=my_tensor, indices=(-3, -2)) # (tensor([[0], [4], [8]]), # tensor([[1], [5], [9]]), # tensor([[2, 3], [6, 7], [10, 11]])) torch.hsplit(input=my_tensor, indices=(-3, 3)) torch.hsplit(input=my_tensor, indices=(-3, -1)) # (tensor([[0], [4], [8]]), # tensor([[1, 2], [5, 6], [9, 10]]), # tensor([[3], [7], [11]])) torch.hsplit(input=my_tensor, indices=(-3, 4)) # (tensor([[0], [4], [8]]), # tensor([[1, 2, 3], [5, 6, 7], [9, 10, 11]]), # tensor([], size=(3, 0), dtype=torch.int64)) torch.hsplit(input=my_tensor, indices=(-4, 0)) torch.hsplit(input=my_tensor, indices=(-4, -4)) # (tensor([], size=(3, 0), dtype=torch.int64), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]])) torch.hsplit(input=my_tensor, indices=(-4, 1)) torch.hsplit(input=my_tensor, indices=(-4, -3)) # (tensor([], size=(3, 0), dtype=torch.int64), # tensor([[0], [4], [8]]), # tensor([[1, 2, 3], [5, 6, 7], [9, 10, 11]])) torch.hsplit(input=my_tensor, indices=(-4, 2)) torch.hsplit(input=my_tensor, indices=(-4, -2)) # (tensor([], size=(3, 0), dtype=torch.int64), # tensor([[0, 1], [4, 5], [8, 9]]), # tensor([[2, 3], [6, 7], [10, 11]])) torch.hsplit(input=my_tensor, indices=(-4, 3)) torch.hsplit(input=my_tensor, indices=(-4, -1)) # (tensor([], size=(3, 0), dtype=torch.int64), # tensor([[0, 1, 2], [4, 5, 6], [8, 9, 10]]), # tensor([[3], [7], [11]])) torch.hsplit(input=my_tensor, indices=(-4, 4)) # (tensor([], size=(3, 0), dtype=torch.int64), # tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]), # tensor([], size=(3, 0), dtype=torch.int64)) torch.hsplit(input=my_tensor, indices=(0, 0, 0)) torch.hsplit(input=my_tensor, indices=(0, 0, -4)) torch.hsplit(input=my_tensor, indices=(0, -4, 0)) torch.hsplit(input=my_tensor, indices=(0, -4, -4)) # (tensor([], size=(3, 0), dtype=torch.int64), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([], size=(3, 0), dtype=torch.int64), # tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]])) etc. my_tensor = torch.tensor([[0., 1., 2., 3.], [4., 5., 6., 7.], [8., 9., 10., 11.]]) torch.hsplit(input=my_tensor, sections=1) # (tensor([[0., 1., 2., 3.], # [4., 5., 6., 7.], # [8., 9., 10., 11.]]),) my_tensor = torch.tensor([[0.+0.j, 1.+0.j, 2.+0.j, 3.+0.j], [4.+0.j, 5.+0.j, 6.+0.j, 7.+0.j], [8.+0.j, 9.+0.j, 10.+0.j, 11.+0.j]]) torch.hsplit(input=my_tensor, sections=1) # (tensor([[0.+0.j, 1.+0.j, 2.+0.j, 3.+0.j], # [4.+0.j, 5.+0.j, 6.+0.j, 7.+0.j], # [8.+0.j, 9.+0.j, 10.+0.j, 11.+0.j]]),) my_tensor = torch.tensor([[True, False, True, False], [False, True, False, True], [True, False, True, False]]) torch.hsplit(input=my_tensor, sections=1) # (tensor([[True, False, True, False], # [False, True, False, True], # [True, False, True, False]]),)
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