flip() can get the 0D or more D tensor of reversed zero or more elements from the 0D or more D tensor of zero or more elements as shown below:
*Memos:
-
flip()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 or more arguments with a tensor aredims(Required-Type:int,tupleofintorlistofint). *Each number must be unique.
import torch my_tensor = torch.tensor(2) # 0D tensor torch.flip(input=my_tensor, dims=(0,)) my_tensor.flip(dims=(0,)) my_tensor.flip(0) torch.flip(input=my_tensor, dims=(-1,)) # tensor(2) my_tensor = torch.tensor([2, 7, 4]) # 1D tensor torch.flip(input=my_tensor, dims=(0,)) torch.flip(input=my_tensor, dims=(-1,)) # tensor([4, 7, 2]) my_tensor = torch.tensor([[2, 7, 4], [8, 3, 2]]) # 2D tensor torch.flip(input=my_tensor, dims=(0,)) torch.flip(input=my_tensor, dims=(-2,)) # tensor([[8, 3, 2], [2, 7, 4]]) torch.flip(input=my_tensor, dims=(1,)) torch.flip(input=my_tensor, dims=(-1,)) # tensor([[4, 7, 2], [2, 3, 8]]) torch.flip(input=my_tensor, dims=(0, 1)) torch.flip(input=my_tensor, dims=(0, -1)) torch.flip(input=my_tensor, dims=(1, 0)) torch.flip(input=my_tensor, dims=(1, -2)) torch.flip(input=my_tensor, dims=(-1, 0)) torch.flip(input=my_tensor, dims=(-1, -2)) torch.flip(input=my_tensor, dims=(-2, 1)) torch.flip(input=my_tensor, dims=(-2, -1)) # tensor([[2, 3, 8], [4, 7, 2]]) my_tensor = torch.tensor([[[2, 7, 4], [8, 3, 2]], # 3D tensor [[5, 0, 8], [3, 6, 1]]]) torch.flip(input=my_tensor, dims=(0,)) torch.flip(input=my_tensor, dims=(-3,)) # tensor([[[5, 0, 8], [3, 6, 1]], # [[2, 7, 4], [8, 3, 2]]]) torch.flip(input=my_tensor, dims=(1,)) torch.flip(input=my_tensor, dims=(-2,)) # tensor([[[8, 3, 2], [2, 7, 4]], # [[3, 6, 1], [5, 0, 8]]]) torch.flip(input=my_tensor, dims=(2,)) torch.flip(input=my_tensor, dims=(-1,)) # tensor([[[4, 7, 2], [2, 3, 8]], # [[8, 0, 5], [1, 6, 3]]]) torch.flip(input=my_tensor, dims=(0, 1)) torch.flip(input=my_tensor, dims=(0, -2)) torch.flip(input=my_tensor, dims=(1, 0)) torch.flip(input=my_tensor, dims=(1, -3)) torch.flip(input=my_tensor, dims=(-2, 0)) torch.flip(input=my_tensor, dims=(-2, -3)) torch.flip(input=my_tensor, dims=(-3, 1)) torch.flip(input=my_tensor, dims=(-3, -2)) # tensor([[[3, 6, 1], [5, 0, 8]], # [[8, 3, 2], [2, 7, 4]]]) torch.flip(input=my_tensor, dims=(0, 2)) torch.flip(input=my_tensor, dims=(0, -1)) torch.flip(input=my_tensor, dims=(2, 0)) torch.flip(input=my_tensor, dims=(2, -3)) torch.flip(input=my_tensor, dims=(-1, 0)) torch.flip(input=my_tensor, dims=(-1, -3)) torch.flip(input=my_tensor, dims=(-3, 2)) torch.flip(input=my_tensor, dims=(-3, -1)) # tensor([[[8, 0, 5], [1, 6, 3]], # [[4, 7, 2], [2, 3, 8]]]) torch.flip(input=my_tensor, dims=(1, 2)) torch.flip(input=my_tensor, dims=(1, -1)) torch.flip(input=my_tensor, dims=(2, 1)) torch.flip(input=my_tensor, dims=(2, -2)) torch.flip(input=my_tensor, dims=(-1, 1)) torch.flip(input=my_tensor, dims=(-1, -2)) torch.flip(input=my_tensor, dims=(-2, 2)) torch.flip(input=my_tensor, dims=(-2, -1)) # tensor([[[2, 3, 8], [4, 7, 2]], # [[1, 6, 3], [8, 0, 5]]]) torch.flip(input=my_tensor, dims=(0, 1, 2)) etc. # tensor([[[1, 6, 3], [8, 0, 5]], # [[2, 3, 8], [4, 7, 2]]]) my_tensor = torch.tensor([[[2., 7., 4.], [8., 3., 2.]], # 3D tensor [[5., 0., 8.], [3., 6., 1.]]]) torch.flip(input=my_tensor, dims=(0,)) # tensor([[[5., 0., 8.], [3., 6., 1.]], # [[2., 7., 4.], [8., 3., 2.]]]) my_tensor = torch.tensor([[[2.+0.j, 7.+0.j, 4.+0.j], # 3D tensor [8.+0.j, 3.+0.j, 2.+0.j]], [[5.+0.j, 0.+0.j, 8.+0.j], [3.+0.j, 6.+0.j, 1.+0.j]]]) torch.flip(input=my_tensor, dims=(0,)) # tensor([[[5.+0.j, 0.+0.j, 8.+0.j], # [3.+0.j, 6.+0.j, 1.+0.j]], # [[2.+0.j, 7.+0.j, 4.+0.j], # [8.+0.j, 3.+0.j, 2.+0.j]]]) # 3D tensor my_tensor = torch.tensor([[[True, False, True], [True, False, True]], [[False, True, False], [False, True, False]]]) torch.flip(input=my_tensor, dims=(0,)) # tensor([[[False, True, False], [False, True, False]], # [[True, False, True], [True, False, True]]]) 
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