1
import torch
2

3
a = torch.tensor([
4
    [1,2],
5
    [3,4]
6
])
7

8
b = torch.tensor([
9
    [10, 20]
10
])
11

12
# 加
13
print("torch.all(torch.eq(a+b, torch.add(a,b))):",
14
      torch.all(torch.eq(a+b, torch.add(a,b))))
15
print("a+b:\n{}\n".format(a+b))
16

17
# 减
18
print("torch.all(torch.eq(a-b, torch.sub(a,b))):",
19
      torch.all(torch.eq(a-b, torch.sub(a,b))))
20
print("a*b:\n{}\n".format(a-b))
21

22
# 乘（是点乘）
23
print("torch.all(torch.eq(a*b, torch.mul(a,b))):",
24
      torch.all(torch.eq(a*b, torch.mul(a,b))))
25
print("a*b:\n{}\n".format(a*b))
26

27
# 除
28
print("torch.all(torch.eq(a/b, torch.div(a,b))):",
29
      torch.all(torch.eq(a/b, torch.div(a,b))))
30
print("a*b:\n{}\n".format(a/b))

1
import torch
2

3
a = torch.tensor([
4
    [1],
5
    [3]
6
])
7

8
b = torch.tensor([
9
    [10, 20]
10
])
11

12
# mm只能运算至多二维矩阵
13
print("torch.mm(a, b):\n{}\n".format(torch.mm(a, b)))
14
# matmul可运算更高维矩阵
15
print("torch.matmul(a, b):\n{}\n".format(torch.matmul(a, b)))
16
print("a@b:\n{}\n".format(a@b))

1
import torch
2

3
a1 = torch.rand(4, 3, 28, 64)
4
b1 = torch.rand(4, 3, 64, 32)
5

6
c1 = torch.matmul(a1, b1)
7
# 对最后两维进行乘法运算
8
# 可以理解为多个矩阵并行相乘
9
print("c1.shape: ", c1.shape)
10

11
a2 = torch.rand(4, 1, 28, 64)
12
b2 = torch.rand(4, 3, 64, 32)
13
c2 = torch.matmul(a2, b2)
14
# 这里用到了广播机制
15
print("c2.shape: ", c2.shape)

1
import torch
2

3
a = torch.tensor([
4
    [1, 2],
5
    [3, 4]
6
])
7

8
print("a.pow(2):\n{}\n".format(a.pow(2)))
9
print("a**2:\n{}\n".format(a**2))
10

11
print("a.pow(0.5):\n{}\n".format(a.pow(0.5)))
12
print("a.sqrt():\n{}\n".format(a.sqrt()))
13
# 平方根的倒数
14
print("a.rsqrt():\n{}\n".format(a.rsqrt()))
15
print("a**0.5:\n{}\n".format(a**0.5))

1
import torch
2

3
a = torch.tensor([
4
    [1, 2],
5
    [3, 4]
6
])
7

8
a_exp = torch.exp(a)
9
# e^x
10
print("torch.exp(a):\n{}\n".format(a_exp))
11
# ln x
12
# 以2为底：log2
13
# 以10为底：log10
14
print("torch.log(a_exp):\n{}\n".format(torch.log(a_exp)))

1
import torch
2

3
a = torch.tensor(1.67)
4

5
# 向下取整
6
print("a.floor():", a.floor())
7
# 向上取整
8
print("a.ceil():", a.ceil())
9
# 取整数部分
10
print("a.trunc():", a.trunc())
11
# 取小数部分
12
print("a.frac():", a.frac())
13
# 四舍五入
14
print("a.round():", a.round())

1
import torch
2

3
a = torch.rand(2,3)*20
4

5
print("a:\n{}\n".format(a))
6

7
# 最大值
8
print("a.max(): ", a.max())
9
# 中位数，偶数时不取平均，取从小到大第 length/2 个
10
print("a.median(): ", a.median())
11
# 最小值
12
print("a.min(): ", a.min())

1
import torch
2

3
a = torch.rand(2,3)*20
4

5
print("a:\n{}\n".format(a))
6

7
# clamp(min)，当有值小于 min 时，用 min 替换
8
print("a.clamp(10):\n{}\n".format(a.clamp(10)))
9
# clamp(min, max)，当有值小于 min 时，用 min 替换
10
# 当有值大于 max 时，用 max 替换
11
print("a.clamp(5, 10):\n{}\n".format(a.clamp(5, 10)))