*Memos:
repeat() can get the 0D or more D tensor of zero or more repeated elements from the 0D or more D tensor of zero or more elements as shown below:
*Memos:
-
repeat()can be used with a tensor but not with torch. - Using a tensor(Required-Type:
tensorofint,float,complexorbool). - The 1st or more arguments with a tensor are
repeats(Required-Type:int,tupleofint,listofintor size()): *Memos:- Its D must be more than or equal to the tensor's D.
- If at least one dimension is
0, an empty tensor is returned. -
repeats=mustn't be used for the one or more dimensions without a tuple, list orsize().
import torch
my_tensor = torch.tensor([7, 4, 2])
my_tensor.repeat(repeats=(0,))
my_tensor.repeat(0)
my_tensor.repeat(repeats=torch.tensor([]).size())
# tensor([], dtype=torch.int64)
my_tensor.repeat(repeats=(1,))
my_tensor.repeat(1)
my_tensor.repeat(repeats=torch.tensor([5]).size())
# tensor([7, 4, 2])
my_tensor.repeat(repeats=(2,))
my_tensor.repeat(2)
my_tensor.repeat(repeats=torch.tensor([5, 8]).size())
# tensor([7, 4, 2, 7, 4, 2])
my_tensor.repeat(repeats=(3,))
my_tensor.repeat(3)
my_tensor.repeat(repeats=torch.tensor([5, 8, 1]).size())
# tensor([7, 4, 2, 7, 4, 2, 7, 4, 2])
etc.
my_tensor.repeat(repeats=(3, 2))
my_tensor.repeat(3, 2)
my_tensor.repeat(repeats=torch.tensor([[5, 8], [1, 9], [3, 0]]).size())
# tensor([[7, 4, 2, 7, 4, 2],
# [7, 4, 2, 7, 4, 2],
# [7, 4, 2, 7, 4, 2]])
etc.
my_tensor.repeat(repeats=(3, 2, 1))
my_tensor.repeat(3, 2, 1)
# tensor([[[7, 4, 2], [7, 4, 2]],
# [[7, 4, 2], [7, 4, 2]],
# [[7, 4, 2], [7, 4, 2]]])
etc.
my_tensor.repeat(repeats=(3, 0, 1))
my_tensor.repeat(3, 0, 1)
# tensor([], size=(3, 0, 3), dtype=torch.int64)
my_tensor = torch.tensor([[7, 4, 2], [5, 1, 6]])
my_tensor.repeat(repeats=(3, 2))
my_tensor.repeat(3, 2)
my_tensor.repeat(repeats=torch.tensor([[5, 8], [1, 9], [3, 0]]).size())
# tensor([[7, 4, 2, 7, 4, 2],
# [5, 1, 6, 5, 1, 6],
# [7, 4, 2, 7, 4, 2],
# [5, 1, 6, 5, 1, 6],
# [7, 4, 2, 7, 4, 2],
# [5, 1, 6, 5, 1, 6]])
my_tensor = torch.tensor([[7., 4., 2.], [5., 1., 6.]])
my_tensor.repeat(repeats=(3, 2))
# tensor([[7., 4., 2., 7., 4., 2.],
# [5., 1., 6., 5., 1., 6.],
# [7., 4., 2., 7., 4., 2.],
# [5., 1., 6., 5., 1., 6.],
# [7., 4., 2., 7., 4., 2.],
# [5., 1., 6., 5., 1., 6.]])
my_tensor = torch.tensor([[7.+0.j, 4.+0.j, 2.+0.j],
[5.+0.j, 1.+0.j, 6.+0.j]])
my_tensor.repeat(repeats=(3, 2))
# tensor([[7.+0.j, 4.+0.j, 2.+0.j, 7.+0.j, 4.+0.j, 2.+0.j],
# [5.+0.j, 1.+0.j, 6.+0.j, 5.+0.j, 1.+0.j, 6.+0.j],
# [7.+0.j, 4.+0.j, 2.+0.j, 7.+0.j, 4.+0.j, 2.+0.j],
# [5.+0.j, 1.+0.j, 6.+0.j, 5.+0.j, 1.+0.j, 6.+0.j],
# [7.+0.j, 4.+0.j, 2.+0.j, 7.+0.j, 4.+0.j, 2.+0.j],
# [5.+0.j, 1.+0.j, 6.+0.j, 5.+0.j, 1.+0.j, 6.+0.j]])
my_tensor = torch.tensor([[True, False, True],
[False, True, False]])
my_tensor.repeat(repeats=(3, 2))
# tensor([[True, False, True, True, False, True],
# [False, True, False, False, True, False],
# [True, False, True, True, False, True],
# [False True, False, False, True, False],
# [True, False, True, True, False, True],
# [False, True, False, False, True, False]])
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