Python–PyTorch div()方法
PyTorch torch.div()方法用一个常数划分输入的每个元素，并返回一个新的修正张量。
语法:
torch.div(inp, other, out=None)论据
- inp: 这是输入张量。
- 其他:这是要分配给输入 inp 的每个元素的数字。
- 出:输出张量。
返回:它返回一个张量。
Let’s see this concept with the help of few examples:Example 1:
# Importing the PyTorch library
import torch
# A constant tensor of size n
a = torch.FloatTensor([1, 4, 6, 8, 10, 14])
print(a)
# Applying the div function and
# storing the result in 'out'
out = torch.div(a, 0.5)
print(out)
输出:
1
4
6
8
10
14
[torch.FloatTensor of size 6]
2
8
12
16
20
28
[torch.FloatTensor of size 6]
例 2:
# Importing the PyTorch library
import torch
# A constant tensor of size n
a = torch.randn(6)
print(a)
# Applying the div function and
# storing the result in 'out'
out = torch.div(a, 0.3)
print(out)
输出:
-0.8453
-0.1101
0.9431
-0.3041
1.4305
-0.0390
[torch.FloatTensor of size 6]
-2.8176
-0.3669
3.1436
-1.0137
4.7683
-0.1300
[torch.FloatTensor of size 6]
