torch数据维度

 

3,1 表示最外层括号中有3条数据，2个逗号

 

torch的数据维度表示，从外向里表示，[3,1]，表示外面有3行1列

 

import torch
    import torch.nn as nn
    import torch.nn.functional as F

    data = torch.randn(3,1,6)
    data2 = torch.randn(3, 1)
    print(data2.size())
    print(data2)

    data2 = torch.randn(1, 3)
    print(data2.size())
    print(data2)

 

torch.Size([3, 1])
tensor([[ 1.5015],
        [-1.8209],
        [ 0.9194]])
torch.Size([1, 3])
tensor([[ 1.4510, -1.3262, -0.5420]])

 

target的第2维和data的第3维数量要保持一致：不然报错：

import torch
    import torch.nn as nn
    import torch.nn.functional as F

    data = torch.randn(3,3,2)

    target = torch.tensor([[1,1],[0,1],[0,1]])
    print(data.size(),target.size())

    n = data.size(0)
    c = data.size(1)
    out_size = (n,) + data.size()[2:]
    if target.size()[1:] != data.size()[2:]:
        raise ValueError('Expected target size {}, got {}'.format(
            out_size, target.size()))
    #
    # print('data:', data.size(),target.size())
    entropy_out = F.cross_entropy(data, target)
    print('entropy_out:', entropy_out, target.size())