*Memos:
- My post explains eye().
- My post explains diagflat().
- My post explains diag_embed().
- My post explains diagonal().
diag() can create the 2D tensor of zero or more elements on the diagonal and zero or more 0, 0., 0.+0.j or False elsewhere from the 1D tensor of zero or more elements or can extract the 1D tensor of zero or more elements on the diagonal from the 2D tensor of zero or more elements as shown below:
*Memos:
-
diag()can be used with torch or a tensor. - The 1st argument(
input) withtorchor using a tensor(Required-Type:tensorofint,float,complexorbool). *Only a 2D or 1D tensor can be used. - The 2nd argument with
torchor the 1st argument with a tensor isdiagonal(Optional-Default:0-Type:int). - There is
outargument with torch(Optional-Default:None-Type:tensor): *Memos:-
out=must be used. -
My post explains
outargument.
-
- A 2D tensor creates a 1D tensor.
- A 1D tensor creates a 2D tensor.
import torch
my_tensor = torch.tensor([7, -4, 5])
torch.diag(input=my_tensor)
my_tensor.diag()
torch.diag(input=my_tensor, diagonal=0)
# tensor([[7, 0, 0],
# [0, -4, 0],
# [0, 0, 5]])
torch.diag(input=my_tensor, diagonal=1)
# tensor([[0, 7, 0, 0],
# [0, 0, -4, 0],
# [0, 0, 0, 5],
# [0, 0, 0, 0]])
torch.diag(input=my_tensor, diagonal=-1)
# tensor([[0, 0, 0, 0],
# [7, 0, 0, 0],
# [0, -4, 0, 0],
# [0, 0, 5, 0]])
torch.diag(input=my_tensor, diagonal=2)
# tensor([[0, 0, 7, 0, 0],
# [0, 0, 0, -4, 0],
# [0, 0, 0, 0, 5],
# [0, 0, 0, 0, 0],
# [0, 0, 0, 0, 0]])
torch.diag(input=my_tensor, diagonal=-2)
# tensor([[0, 0, 0, 0, 0],
# [0, 0, 0, 0, 0],
# [7, 0, 0, 0, 0],
# [0, -4, 0, 0, 0],
# [0, 0, 5, 0, 0]])
my_tensor = torch.tensor([7., -4., 5.])
torch.diag(input=my_tensor)
# tensor([[7., 0., 0.],
# [0., -4., 0.],
# [0., 0., 5.]])
my_tensor = torch.tensor([7.+0.j, -4.+0.j, 5.+0.j])
torch.diag(input=my_tensor)
# tensor([[7.+0.j, 0.+0.j, 0.+0.j],
# [0.+0.j, -4.+0.j, 0.+0.j],
# [0.+0.j, 0.+0.j, 5.+0.j]])
my_tensor = torch.tensor([True, True, True])
torch.diag(input=my_tensor)
# tensor([[True, False, False],
# [False, True, False],
# [False, False, True]])
my_tensor = torch.tensor([[7, -4, 5],
[-6, -3, 8],
[9, 1, -2]])
torch.diag(input=my_tensor)
torch.diag(input=my_tensor, diagonal=0)
# tensor([7, -3, -2])
torch.diag(input=my_tensor, diagonal=1)
# tensor([-4, 8])
torch.diag(input=my_tensor, diagonal=-1)
# tensor([-6, -1])
torch.diag(input=my_tensor, diagonal=2)
# tensor([5])
torch.diag(input=my_tensor, diagonal=-2)
# tensor([9])
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