*Memos:
- My post explains flatten() and ravel().
- My post explains Unflatten().
- My post explains unflatten().
Flatten() can remove zero or more dimensions by selecting dimensions from the 0D or more D tensor of zero or more elements, getting the 1D or more D tensor of zero or more elements as shown below:
*Memos:
- The 1st argument for initialization is
start_dim(Optional-Default:1-Type:int). - The 2nd argument for initialization is
end_dim(Optional-Default:-1-Type:int). - The 1st argument is
input(Required-Type:tensorofint,float,complexorbool). -
Flatten()can change a 0D tensor to a 1D tensor. -
Flatten()does nothing for a 1D tensor. - The difference between Flatten() and flatten() is:
- The default value of
start_dimforFlatten()is1while the default value ofstart_dimforflatten()is0. - Basically,
Flatten()is used to define a model whileflatten()is not used to define a model.
- The default value of
import torch from torch import nn flatten = nn.Flatten() flatten # Flatten(start_dim=1, end_dim=-1) flatten.start_dim # 1 flatten.end_dim # -1 my_tensor = torch.tensor(7) flatten = nn.Flatten(start_dim=0, end_dim=0) flatten = nn.Flatten(start_dim=0, end_dim=-1) flatten = nn.Flatten(start_dim=-1, end_dim=0) flatten = nn.Flatten(start_dim=-1, end_dim=-1) flatten(input=my_tensor) # tensor([7]) my_tensor = torch.tensor([7, 1, -8, 3, -6, 0]) flatten = nn.Flatten(start_dim=0, end_dim=0) flatten = nn.Flatten(start_dim=0, end_dim=-1) flatten = nn.Flatten(start_dim=-1, end_dim=0) flatten = nn.Flatten(start_dim=-1, end_dim=-1) flatten(input=my_tensor) # tensor([7, 1, -8, 3, -6, 0]) my_tensor = torch.tensor([[7, 1, -8], [3, -6, 0]]) flatten = nn.Flatten(start_dim=0, end_dim=1) flatten = nn.Flatten(start_dim=0, end_dim=-1) flatten = nn.Flatten(start_dim=-2, end_dim=1) flatten = nn.Flatten(start_dim=-2, end_dim=-1) flatten(input=my_tensor) # tensor([7, 1, -8, 3, -6, 0]) flatten = nn.Flatten() flatten = nn.Flatten(start_dim=0, end_dim=0) flatten = nn.Flatten(start_dim=-1, end_dim=-1) flatten = nn.Flatten(start_dim=0, end_dim=-2) flatten = nn.Flatten(start_dim=1, end_dim=1) flatten = nn.Flatten(start_dim=1, end_dim=-1) flatten = nn.Flatten(start_dim=-1, end_dim=1) flatten = nn.Flatten(start_dim=-1, end_dim=-1) flatten = nn.Flatten(start_dim=-2, end_dim=0) flatten = nn.Flatten(start_dim=-2, end_dim=-2) flatten(input=my_tensor) # tensor([[7, 1, -8], [3, -6, 0]]) my_tensor = torch.tensor([[[7], [1], [-8]], [[3], [-6], [0]]]) flatten = nn.Flatten(start_dim=0, end_dim=2) flatten = nn.Flatten(start_dim=0, end_dim=-1) flatten = nn.Flatten(start_dim=-3, end_dim=2) flatten = nn.Flatten(start_dim=-3, end_dim=-1) flatten(input=my_tensor) # tensor([7, 1, -8, 3, -6, 0]) flatten = nn.Flatten(start_dim=0, end_dim=0) flatten = nn.Flatten(start_dim=0, end_dim=-3) flatten = nn.Flatten(start_dim=1, end_dim=1) flatten = nn.Flatten(start_dim=1, end_dim=-2) flatten = nn.Flatten(start_dim=2, end_dim=2) flatten = nn.Flatten(start_dim=2, end_dim=-1) flatten = nn.Flatten(start_dim=-1, end_dim=2) flatten = nn.Flatten(start_dim=-1, end_dim=-1) flatten = nn.Flatten(start_dim=-2, end_dim=1) flatten = nn.Flatten(start_dim=-2, end_dim=-2) flatten = nn.Flatten(start_dim=-3, end_dim=0) flatten = nn.Flatten(start_dim=-3, end_dim=-3) flatten(input=my_tensor) # tensor([[[7], [1], [-8]], [[3], [-6], [0]]]) flatten = nn.Flatten(start_dim=0, end_dim=1) flatten = nn.Flatten(start_dim=0, end_dim=-2) flatten = nn.Flatten(start_dim=-3, end_dim=1) flatten = nn.Flatten(start_dim=-3, end_dim=-2) flatten(input=my_tensor) # tensor([[7], [1], [-8], [3], [-6], [0]]) flatten = nn.Flatten() flatten = nn.Flatten(start_dim=1, end_dim=2) flatten = nn.Flatten(start_dim=1, end_dim=-1) flatten = nn.Flatten(start_dim=-2, end_dim=2) flatten = nn.Flatten(start_dim=-2, end_dim=-1) flatten(input=my_tensor) # tensor([[7, 1, -8], [3, -6, 0]]) my_tensor = torch.tensor([[[7.], [1.], [-8.]], [[3.], [-6.], [0.]]]) flatten = nn.Flatten() flatten(input=my_tensor) # tensor([[7., 1., -8.], [3., -6., 0.]]) my_tensor = torch.tensor([[[7.+0.j], [1.+0.j], [-8.+0.j]], [[3.+0.j], [-6.+0.j], [0.+0.j]]]) flatten = nn.Flatten() flatten(input=my_tensor) # tensor([[7.+0.j, 1.+0.j, -8.+0.j], # [3.+0.j, -6.+0.j, 0.+0.j]]) my_tensor = torch.tensor([[[True], [False], [True]], [[False], [True], [False]]]) flatten = nn.Flatten() flatten(input=my_tensor) # tensor([[True, False, True], # [False, True, False]]) 
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