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2.1 数据操作

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

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])

Y=x.reshape(-1,4)
Y

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

Z=x.reshape(3,-1)
Z

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

torch.zeros((2,3,4))

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.]]])

torch.ones((2,3,4))

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.]]])

torch.randn(3,4)

tensor([[ 1.6438, -1.2879,  0.2324,  0.2719],
        [-0.6636,  0.9939, -0.8435, -1.0906],
        [-0.5617,  0.2107, -0.9530,  0.7362]])

x=torch.tensor([1.0,2,4,8])
y=torch.tensor([2,2,2,2])
x+y,x-y,x*y,x/y,x**y

(tensor([ 3.,  4.,  6., 10.]),
 tensor([-1.,  0.,  2.,  6.]),
 tensor([ 2.,  4.,  8., 16.]),
 tensor([0.5000, 1.0000, 2.0000, 4.0000]),
 tensor([ 1.,  4., 16., 64.]))

torch.exp(x)

tensor([2.7183e+00, 7.3891e+00, 5.4598e+01, 2.9810e+03])

X=torch.arange(12,dtype=torch.float32).reshape((3,4))
X

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

Y=torch.tensor([[2.0,1,4,3],[1,2,3,4],[4,3,2,1]])
Y

tensor([[2., 1., 4., 3.],
        [1., 2., 3., 4.],
        [4., 3., 2., 1.]])