pytorch中tensor的属性 类型转换 形状变换 转置 最大值

import torch
import numpy as np
a = torch.tensor([[[1]]])
#只有一个数据的时候，获取其数值
print(a.item())

#tensor转化为nparray
b = a.numpy()
print(b,type(b),type(a))

#获取张量的形状
a = torch.tensor(np.arange(30).reshape(3,2,5))
print(a)
print(a.shape)
print(a.size())
print(a.size(0))

#形状变换
print(a.view([2,3,5]))


#转置
b = torch.tensor(np.arange(15).reshape(3,5))
print(b)
print(b.transpose(0,1))
print(b.T)

#最大值
print(b.max(dim=-1))




D:anacondapython.exe C:/Users/liuxinyu/Desktop/pytorch_test/day1/张量的属性和方法.py
1
[[[1]]] <class 'numpy.ndarray'> <class 'torch.Tensor'>
tensor([[[ 0,  1,  2,  3,  4],
         [ 5,  6,  7,  8,  9]],

        [[10, 11, 12, 13, 14],
         [15, 16, 17, 18, 19]],

        [[20, 21, 22, 23, 24],
         [25, 26, 27, 28, 29]]], dtype=torch.int32)
torch.Size([3, 2, 5])
torch.Size([3, 2, 5])
3
tensor([[[ 0,  1,  2,  3,  4],
         [ 5,  6,  7,  8,  9],
         [10, 11, 12, 13, 14]],

        [[15, 16, 17, 18, 19],
         [20, 21, 22, 23, 24],
         [25, 26, 27, 28, 29]]], dtype=torch.int32)
tensor([[ 0,  1,  2,  3,  4],
        [ 5,  6,  7,  8,  9],
        [10, 11, 12, 13, 14]], dtype=torch.int32)
tensor([[ 0,  5, 10],
        [ 1,  6, 11],
        [ 2,  7, 12],
        [ 3,  8, 13],
        [ 4,  9, 14]], dtype=torch.int32)
tensor([[ 0,  5, 10],
        [ 1,  6, 11],
        [ 2,  7, 12],
        [ 3,  8, 13],
        [ 4,  9, 14]], dtype=torch.int32)
torch.return_types.max(
values=tensor([ 4,  9, 14], dtype=torch.int32),
indices=tensor([4, 4, 4]))

Process finished with exit code 0