*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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