*Memos:
- My post explains split().
- My post explains vsplit().
- My post explains hsplit().
- My post explains dsplit().
- My post explains tensor_split().
- My post explains chunk().
unbind() can get the one or more 0D or more D splitted view tensors of zero or more elements by the removal of only one specified dimension from the 1D or more D tensor of zero or more elements as shown below:
*Memos:
-
unbind()can be used with torch or a tensor. - The 1st argument(
input) withtorchor using a tensor(Required-Type:tensorofint,float,complexorbool). - The 2nd argument with
torchor the 1st argument isdim(Optional-Default:0-Type:int). - The total number of the zero or more elements of one or more returned tensors doesn't change.
- One or more returned tensors don't keep the dimension of the original tensor.
import torch
my_tensor = torch.tensor([0, 1, 2, 3])
torch.unbind(input=my_tensor)
my_tensor.unbind()
torch.unbind(input=my_tensor, dim=0)
torch.unbind(input=my_tensor, dim=-1)
# (tensor(0),
# tensor(1),
# tensor(2),
# tensor(3))
my_tensor = torch.tensor([[0, 1, 2, 3],
[4, 5, 6, 7],
[8, 9, 10, 11]])
torch.unbind(input=my_tensor)
torch.unbind(input=my_tensor, dim=0)
torch.unbind(input=my_tensor, dim=-2)
# (tensor([0, 1, 2, 3]),
# tensor([4, 5, 6, 7]),
# tensor([8, 9, 10, 11]))
torch.unbind(input=my_tensor, dim=1)
torch.unbind(input=my_tensor, dim=-1)
# (tensor([0, 4, 8]),
# tensor([1, 5, 9]),
# tensor([2, 6, 10]),
# tensor([3, 7, 11]))
my_tensor = torch.tensor([[[0, 1, 2, 3],
[4, 5, 6, 7],
[8, 9, 10, 11]]])
torch.unbind(input=my_tensor)
torch.unbind(input=my_tensor, dim=0)
torch.unbind(input=my_tensor, dim=-3)
# (tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]),)
torch.unbind(input=my_tensor, dim=1)
torch.unbind(input=my_tensor, dim=-2)
# (tensor([[0, 1, 2, 3]]),
# tensor([[4, 5, 6, 7]]),
# tensor([[8, 9, 10, 11]]))
torch.unbind(input=my_tensor, dim=2)
torch.unbind(input=my_tensor, dim=-1)
# (tensor([[0, 4, 8]]),
# tensor([[1, 5, 9]]),
# tensor([[2, 6, 10]]),
# tensor([[3, 7, 11]]))
my_tensor = torch.tensor([[[0., 1., 2., 3.],
[4., 5., 6., 7.],
[8., 9., 10., 11.]]])
torch.unbind(input=my_tensor)
# (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.unbind(input=my_tensor)
# (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.unbind(input=my_tensor)
# (tensor([[True, False, True, False],
# [False, True, False, True],
# [True, False, True, False]]),)
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