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Env

import torch


x = torch.arange(12)
x 
tensor([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11])
x.shape 
torch.Size([12])
x.numel() 
12


  change shape 

X = x.reshape(3, 4)
X 
tensor([[ 0,  1,  2,  3],
        [ 4,  5,  6,  7],
        [ 8,  9, 10, 11]])
X.shape 
torch.Size([3, 4])
X.numel() 
12


  transpose 

X.T
X 
tensor([[ 0,  4,  8],
        [ 1,  5,  9],
        [ 2,  6, 10],
        [ 3,  7, 11]])


  create by python list 

P = torch.tensor([[2, 1, 4, 3], [1, 2, 3, 4], [4, 3, 2, 1]])
P 
tensor([[2, 1, 4, 3],
        [1, 2, 3, 4],
        [4, 3, 2, 1]])
P.shape 
torch.Size([3, 4])
P.numel() 
12


Other specific values
  0 

Z = torch.zeros(2,3,4)
Z 
tensor([[[0., 0., 0., 0.],
         [0., 0., 0., 0.],
         [0., 0., 0., 0.]],

        [[0., 0., 0., 0.],
         [0., 0., 0., 0.],
         [0., 0., 0., 0.]]])
Z.shape 
torch.Size([2, 3, 4])
Z.numel() 
24

  1

O = torch.ones((2, 3, 4))
O 
tensor([[[1., 1., 1., 1.],
         [1., 1., 1., 1.],
         [1., 1., 1., 1.]],

        [[1., 1., 1., 1.],
         [1., 1., 1., 1.],
         [1., 1., 1., 1.]]])
Z.shape 
torch.Size([2, 3, 4])
Z.numel() 
24


create by sum
  

X = torch.arange(12, dtype=torch.float32).reshape((3,4))
S = X.sum()
X 
tensor([[ 0.,  1.,  2.,  3.],
        [ 4.,  5.,  6.,  7.],
        [ 8.,  9., 10., 11.]])
S 
tensor(66.)