*My post explains unflatten().
flatten() can remove zero or more dimensions from a 0D or more D tensor as shown below:
*Memos:
-
flatten()
can be used with torch or a tensor. - The 1st argument(
tensor
ofint
,float
,complex
orbool
) withtorch
or using a tensor(tensor
ofint
,float
,complex
orbool
) isinput
(Required). - The 2nd argument(
int
) withtorch
or the 1st argument(int
) with a tensor isstart_dim
(Optional-Default:0
) which is the 1st dimension. - The 3rd argument(
int
) withtorch
or the 2nd argument(int
) with a tensor isend_dim
(Optional-Default:-1
) which is the last dimension. -
flatten()
can make a 0D tensor a 1D tensor.
import torch
my_tensor = torch.tensor(7) # 0D tensor
# Size:[]
torch.flatten(input=my_tensor)
my_tensor.flatten()
torch.flatten(input=my_tensor, start_dim=0, end_dim=0)
torch.flatten(input=my_tensor, start_dim=0, end_dim=-1)
torch.flatten(input=my_tensor, start_dim=-1, end_dim=0)
torch.flatten(input=my_tensor, start_dim=-1, end_dim=-1)
# tensor([7])
# Size:[1]
my_tensor = torch.tensor([7, 1, -8, 3, -6, 0]) # 1D tensor
# Size:[3]
torch.flatten(input=my_tensor)
torch.flatten(input=my_tensor, start_dim=0, end_dim=0)
torch.flatten(input=my_tensor, start_dim=0, end_dim=-1)
torch.flatten(input=my_tensor, start_dim=-1, end_dim=0)
torch.flatten(input=my_tensor, start_dim=-1, end_dim=-1)
# tensor([7, 1, -8, 3, -6, 0])
# Size:[6]
my_tensor = torch.tensor([[7, 1, -8], [3, -6, 0]]) # 2D tensor
# Size:[2, 3]
torch.flatten(input=my_tensor)
torch.flatten(input=my_tensor, start_dim=0, end_dim=1)
torch.flatten(input=my_tensor, start_dim=0, end_dim=-1)
torch.flatten(input=my_tensor, start_dim=-2, end_dim=1)
torch.flatten(input=my_tensor, start_dim=-2, end_dim=-1)
# tensor([7, 1, -8, 3, -6, 0])
# Size:[6]
torch.flatten(input=my_tensor, start_dim=0, end_dim=0)
torch.flatten(input=my_tensor, start_dim=-1, end_dim=-1)
torch.flatten(input=my_tensor, start_dim=0, end_dim=-2)
torch.flatten(input=my_tensor, start_dim=1, end_dim=1)
torch.flatten(input=my_tensor, start_dim=1, end_dim=-1)
torch.flatten(input=my_tensor, start_dim=-1, end_dim=1)
torch.flatten(input=my_tensor, start_dim=-1, end_dim=-1)
torch.flatten(input=my_tensor, start_dim=-2, end_dim=0)
torch.flatten(input=my_tensor, start_dim=-2, end_dim=-2)
# tensor([[7, 1, -8], [3, -6, 0]])
# Size:[2, 3]
my_tensor = torch.tensor([[[7], [1], [-8]], [[3], [-6], [0]]])
# 3D tensor
# Size:[2, 3, 1]
torch.flatten(input=my_tensor)
torch.flatten(input=my_tensor, start_dim=0, end_dim=2)
torch.flatten(input=my_tensor, start_dim=0, end_dim=-1)
torch.flatten(input=my_tensor, start_dim=-3, end_dim=2)
torch.flatten(input=my_tensor, start_dim=-3, end_dim=-1)
# tensor([7, 1, -8, 3, -6, 0])
# Size:[6]
torch.flatten(input=my_tensor, start_dim=0, end_dim=0)
torch.flatten(input=my_tensor, start_dim=0, end_dim=-3)
torch.flatten(input=my_tensor, start_dim=1, end_dim=1)
torch.flatten(input=my_tensor, start_dim=1, end_dim=-2)
torch.flatten(input=my_tensor, start_dim=2, end_dim=2)
torch.flatten(input=my_tensor, start_dim=2, end_dim=-1)
torch.flatten(input=my_tensor, start_dim=-1, end_dim=2)
torch.flatten(input=my_tensor, start_dim=-1, end_dim=-1)
torch.flatten(input=my_tensor, start_dim=-2, end_dim=1)
torch.flatten(input=my_tensor, start_dim=-2, end_dim=-2)
torch.flatten(input=my_tensor, start_dim=-3, end_dim=0)
torch.flatten(input=my_tensor, start_dim=-3, end_dim=-3)
# tensor([[[7], [1], [-8]], [[3], [-6], [0]]])
# Size:[2, 3, 1]
torch.flatten(input=my_tensor, start_dim=0, end_dim=1)
torch.flatten(input=my_tensor, start_dim=0, end_dim=-2)
torch.flatten(input=my_tensor, start_dim=-3, end_dim=1)
torch.flatten(input=my_tensor, start_dim=-3, end_dim=-2)
# tensor([[7], [1], [-8], [3], [-6], [0]])
# Size:[6, 1]
torch.flatten(input=my_tensor, start_dim=1, end_dim=2)
torch.flatten(input=my_tensor, start_dim=1, end_dim=-1)
torch.flatten(input=my_tensor, start_dim=-2, end_dim=2)
torch.flatten(input=my_tensor, start_dim=-2, end_dim=-1)
# tensor([[7, 1, -8], [3, -6, 0]])
# Size:[2, 3]
my_tensor = torch.tensor([[[7.], [1.], [-8.]], # 3D tensor
[[3.], [-6.], [0.]]]) # Size:[2, 3, 1]
torch.flatten(input=my_tensor)
# tensor([7., 1., -8., 3., -6., 0.])
# Size:[6]
my_tensor = torch.tensor([[[7.+0.j], [1.+0.j], [-8.+0.j]], # 3D tensor
[[3.+0.j], [-6.+0.j], [0.+0.j]]]) # Size:[2, 3, 1]
torch.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]], # 3D tensor
[[False], [True], [False]]]) # Size:[2, 3, 1]
torch.flatten(input=my_tensor)
# tensor([True, False, True, False, True, False])
ravel() can flat a 0D or more D tensor to a 1D tensor as shown below:
*Memos:
-
ravel()
can be used withtorch
or a tensor. - The 1st argument(
tensor
ofint
,float
,complex
orbool
) withtorch
or using a tensor(tensor
ofint
,float
,complex
orbool
) isinput
(Required).
import torch
my_tensor = torch.tensor(7) # 0D tensor
# Size:[]
torch.ravel(input=my_tensor)
my_tensor.ravel()
# tensor([7])
# Size:[1]
my_tensor = torch.tensor([7, 1, -8, 3, -6, 0]) # 1D tensor
# Size:[6]
torch.ravel(input=my_tensor)
# tensor([7, 1, -8, 3, -6, 0])
# Size:[6]
my_tensor = torch.tensor([[7, 1, -8], [3, -6, 0]]) # 2D tensor
# Size:[2, 3]
torch.ravel(input=my_tensor)
# tensor([7, 1, -8, 3, -6, 0])
# Size:[6]
my_tensor = torch.tensor([[[7], [1], [-8]], # 3D tensor
[[3], [-6], [0]]]) # Size:[2, 3, 1]
torch.ravel(input=my_tensor)
# tensor([7, 1, -8, 3, -6, 0])
# Size:[6]
my_tensor = torch.tensor([[[7.], [1.], [-8.]], # 3D tensor
[[3.], [-6.], [0.]]]) # Size:[2, 3, 1]
torch.ravel(input=my_tensor)
# tensor([7., 1., -8., 3., -6., 0.])
# Size:[6]
my_tensor = torch.tensor([[[7.+0.j], [1.+0.j], [-8.+0.j]], # 3D tensor
[[3.+0.j], [-6.+0.j], [0.+0.j]]]) # Size:[2, 3, 1]
torch.ravel(input=my_tensor)
# tensor([7.+0.j, 1.+0.j, -8.+0.j, 3.+0.j, -6.+0.j, 0.+0.j])
# Size:[6]
my_tensor = torch.tensor([[[True], [False], [True]], # 3D tensor
[[False], [True], [False]]]) # Size:[2, 3, 1]
torch.ravel(input=my_tensor)
# tensor([True, False, True, False, True, False])
# Size:[6]
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