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*备忘录：
atleast_1d()只需将一个或多个0d或多个d张量从一个或多个0d或多个d张量更改为一个或多个1d张量即可获得零个或多个元素的一个或多个1d或多个d张量的视图零个或多个元素，如下所示：
*备忘录：
import torch tensor0 = torch.tensor(2) # 0D tensor torch.atleast_1d(tensor0) # tensor([2]) tensor0 = torch.tensor(2) # 0D tensor tensor1 = torch.tensor([2, 7, 4]) # 1D tensor tensor2 = torch.tensor([[2, 7, 4], [8, 3, 2]]) # 2D tensor tensor3 = torch.tensor([[[2, 7, 4], [8, 3, 2]], # 3D tensor [[5, 0, 8], [3, 6, 1]]]) tensor4 = torch.tensor([[[[2, 7, 4], [8, 3, 2]], # 4D tensor [[5, 0, 8], [3, 6, 1]]], [[[9, 4, 7], [1, 0, 5]], [[6, 7, 4], [2, 1, 9]]]]) torch.atleast_1d(tensor0, tensor1, tensor2, tensor3, tensor4) torch.atleast_1d((tensor0, tensor1, tensor2, tensor3, tensor4)) # (tensor([2]), # tensor([2, 7, 4]), # tensor([[2, 7, 4], [8, 3, 2]]), # tensor([[[2, 7, 4], [8, 3, 2]], # [[5, 0, 8], [3, 6, 1]]]), # tensor([[[[2, 7, 4], [8, 3, 2]], # [[5, 0, 8], [3, 6, 1]]], # [[[9, 4, 7], [1, 0, 5]], # [[6, 7, 4], [2, 1, 9]]]])) tensor0 = torch.tensor(2) # 0D tensor tensor1 = torch.tensor([2, 7, 4]) # 1D tensor tensor2 = torch.tensor([[2., 7., 4.], # 2D tensor [8., 3., 2.]]) tensor3 = 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]]]) tensor4 = torch.tensor([[[[True, False, True], [False, True, False]], [[True, False, True], [False, True, False]]], [[[True, False, True], [False, True, False]], [[True, False, True], [False, True, False]]]]) # 4D tensor torch.atleast_1d(tensor0, tensor1, tensor2, tensor3, tensor4) # (tensor([2]), # tensor([2, 7, 4]), # tensor([[2., 7., 4.], # [8., 3., 2.]]), # tensor([[[2.+0.j, 7.+0.j, 4.+0.j], # [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]]]), # tensor([[[[True, False, True], [False, True, False]], # [[True, False, True], [False, True, False]]], # [[[True, False, True], [False, True, False]], # [[True, False, True], [False, True, False]]]])) torch.atleast_1d() # ()
◎欢迎参与讨论，请在这里发表您的看法、交流您的观点。