Python – PyTorch 的钳位（）方法

PyTorch torch.clamp()方法将所有输入元素夹在 [ min, max ] 范围内并返回结果张量。

Syntax: torch.clamp(inp, min, max, out=None)

Arguments

• inp: This is input tensor.
• min: This is a number and specifies the lower-bound of the range to which input to be clamped.
• max: This is a number and specifies the upper-bound of the range to which input to be clamped.
• out: The output tensor.

Return: It returns a Tensor.

让我们通过几个例子来看看这个概念：
示例 1：

# Importing the PyTorch library 
import torch 
    
# A constant tensor of size n
a = torch.randn(6)
print(a)
  
# Applying the clamp function and 
# storing the result in 'out'
out = torch.clamp(a, min = 0.5, max = 0.9)
print(out)

输出：

-0.9214
-0.1268
 1.1570
-0.2753
-0.0746
 0.7957
[torch.FloatTensor of size 6]
 0.5000
 0.5000
 0.9000
 0.5000
 0.5000
 0.7957
[torch.FloatTensor of size 6]

示例 2：

# 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 clamp function and 
# storing the result in 'out'
out = torch.clamp(a, min = 5, max = 10)
print(out) 

输出：

1
  4
  6
  8
 10
 14
[torch.FloatTensor of size 6]
  5
  5
  6
  8
 10
 10
[torch.FloatTensor of size 6]?

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