官方文档地址：https://pytorch.org/docs/stable/torch.html

代码

import torch

print('# 例1、对角线都是1的矩阵')
x = torch.eye(3, 3)  # 3x3的单位矩阵，对角线都是1
print(x)
print(x.size(), "\n")

print('# 例2、全是0的矩阵')
x = torch.zeros(3, 3)  # 3x3的矩阵，全0
print(x)
print(x.shape)  # 等价于 print(x.size())
print(x.size(), "\n")

x = torch.zeros(3, 3, dtype=torch.long)  # 指定数据类型为long
print(x)
print(x.size(), "\n")

print('# 例3、全是1的矩阵')
x = torch.ones(3, 3)  # 3x3的矩阵，全1
print(x)
print(x.size(), "\n")

print('# 例4、随机矩阵')
x = torch.rand(3, 3)  # 3x3的矩阵，随机初始化
print(x)
print(x.size(), "\n")

print('# 例5、根据范围生成一维矩阵')
x = torch.arange(0, 10, 2)  # 从0到10，步长为2
print(x)
print(x.size(), "\n")

x = torch.arange(5)  # 从0到5，步长为1
print(x)
print(x.size(), "\n")

print('# 例6、均匀分片生成一维矩阵')
x = torch.linspace(0, 10, 6)  # 从0到10，等分成6份
print(x)
print(x.size(), "\n")

print('# 例7、正态分布生成一维矩阵')
x = torch.normal(mean=torch.arange(1., 11.), std=torch.arange(1, 0, -0.1))
print(x)
print(x.size(), "\n")

print('# 例8、生成随机排列')
x = torch.randperm(10)  # 生成0到10的随机排列，10个数
print(x)
print(x.size(), "\n")

print('# 例9、从数据直接创建')
x = torch.tensor([1, 2, 3, 4])  # 从数据直接创建一维矩阵
print(x)
print(x.size(), "\n")

x = torch.tensor([[1, 2, 3], [4, 5, 6]])  # 从数据直接创建二维矩阵
print(x)
print(x.size(), "\n")

运行结果

# 例1、对角线都是1的矩阵
tensor([[1., 0., 0.],
        [0., 1., 0.],
        [0., 0., 1.]])
torch.Size([3, 3]) 

# 例2、全是0的矩阵
tensor([[0., 0., 0.],
        [0., 0., 0.],
        [0., 0., 0.]])
torch.Size([3, 3])
torch.Size([3, 3]) 

tensor([[0, 0, 0],
        [0, 0, 0],
        [0, 0, 0]])
torch.Size([3, 3]) 

# 例3、全是1的矩阵
tensor([[1., 1., 1.],
        [1., 1., 1.],
        [1., 1., 1.]])
torch.Size([3, 3]) 

# 例4、随机矩阵
tensor([[0.4530, 0.4226, 0.4092],
        [0.1351, 0.8594, 0.7021],
        [0.9496, 0.4814, 0.6343]])
torch.Size([3, 3]) 

# 例5、根据范围生成一维矩阵
tensor([0, 2, 4, 6, 8])
torch.Size([5]) 

tensor([0, 1, 2, 3, 4])
torch.Size([5]) 

# 例6、均匀分片生成一维矩阵
tensor([ 0.,  2.,  4.,  6.,  8., 10.])
torch.Size([6]) 

# 例7、正态分布生成一维矩阵
tensor([0.6623, 1.2843, 2.8861, 3.9618, 4.6383, 6.1333, 7.1289, 8.0894, 9.3103,
        9.9388])
torch.Size([10]) 

# 例8、生成随机排列
tensor([5, 4, 9, 0, 2, 8, 3, 7, 6, 1])
torch.Size([10]) 

# 例9、从数据直接创建
tensor([1, 2, 3, 4])
torch.Size([4]) 

tensor([[1, 2, 3],
        [4, 5, 6]])
torch.Size([2, 3])