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*Mein Beitrag erklärt unsqueeze().
squeeze() kann den 0D- oder mehr D-Tensor von null oder mehr Elementen abrufen, deren null oder mehr Dimensionen entfernt werden, wenn die Größe 1 aus dem 0D- oder mehr D-Tensor von null oder mehr Elementen beträgt, wie unten gezeigt:
*Memos:
import torch my_tensor = torch.tensor([[[[0], [1]], [[2], [3]], [[4], [5]]]]) torch.squeeze(input=my_tensor) my_tensor.squeeze() torch.squeeze(input=my_tensor, dim=(0, 3)) my_tensor.squeeze(dim=(0, 3)) my_tensor.squeeze(0, 3) torch.squeeze(input=my_tensor, dim=(0, 1, 3)) my_tensor.squeeze(dim=(0, 1, 3)) my_tensor.squeeze(0, 1, 3) etc. torch.squeeze(input=my_tensor, dim=(0, 1, 2, 3)) my_tensor.squeeze(dim=(0, 1, 2, 3)) my_tensor.squeeze(0, 1, 2, 3) etc. # tensor([[0, 1], # [2, 3], # [4, 5]]) torch.squeeze(input=my_tensor, dim=0) torch.squeeze(input=my_tensor, dim=-4) torch.squeeze(input=my_tensor, dim=(0,)) torch.squeeze(input=my_tensor, dim=(-4,)) torch.squeeze(input=my_tensor, dim=(0, 1)) torch.squeeze(input=my_tensor, dim=(0, 2)) torch.squeeze(input=my_tensor, dim=(0, -2)) torch.squeeze(input=my_tensor, dim=(0, -3)) torch.squeeze(input=my_tensor, dim=(1, 0)) etc. torch.squeeze(input=my_tensor, dim=(0, 1, 2)) etc. # tensor([[[0], [1]], # [[2], [3]], # [[4], [5]]]) torch.squeeze(input=my_tensor, dim=1) torch.squeeze(input=my_tensor, dim=2) torch.squeeze(input=my_tensor, dim=-2) torch.squeeze(input=my_tensor, dim=-3) torch.squeeze(input=my_tensor, dim=()) torch.squeeze(input=my_tensor, dim=(1,)) torch.squeeze(input=my_tensor, dim=(2,)) torch.squeeze(input=my_tensor, dim=(-2,)) torch.squeeze(input=my_tensor, dim=(-3,)) torch.squeeze(input=my_tensor, dim=(1, 2)) etc. # tensor([[[[0], [1]], # [[2], [3]], # [[4], [5]]]]) torch.squeeze(input=my_tensor, dim=3) torch.squeeze(input=my_tensor, dim=-1) torch.squeeze(input=my_tensor, dim=(3,)) torch.squeeze(input=my_tensor, dim=(-1,)) torch.squeeze(input=my_tensor, dim=(1, 3)) torch.squeeze(input=my_tensor, dim=(1, -1)) torch.squeeze(input=my_tensor, dim=(2, 3)) torch.squeeze(input=my_tensor, dim=(2, -1)) torch.squeeze(input=my_tensor, dim=(3, 1)) etc. torch.squeeze(input=my_tensor, dim=(1, 2, 3)) etc. # tensor([[[0, 1], # [2, 3], # [4, 5]]]) my_tensor = torch.tensor([[[[0.], [1.]], [[2.], [3.]], [[4.], [5.]]]]) torch.squeeze(input=my_tensor) # tensor([[0., 1.], # [2., 3.], # [4., 5.]]) my_tensor = torch.tensor([[[[0.+0.j], [1.+0.j]], [[2.+0.j], [3.+0.j]], [[4.+0.j], [5.+0.j]]]]) torch.squeeze(input=my_tensor) # tensor([[0.+0.j, 1.+0.j], # [2.+0.j, 3.+0.j], # [4.+0.j, 5.+0.j]]) my_tensor = torch.tensor([[[[True], [False]], [[False], [True]], [[True], [False]]]]) torch.squeeze(input=my_tensor) # tensor([[True, False], # [False, True], # [True, False]])
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