PyTorch torch.clamp() method clamps all the input elements into the range [ min, max ] and return a resulting tensor.
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.
Let’s see this concept with the help of few examples:
Example 1:
Example 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) |
Output:
-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]
Example 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) |
Output:
1 4 6 8 10 14 [torch.FloatTensor of size 6] 5 5 6 8 10 10 [torch.FloatTensor of size 6]?
<!–
–>
Wand clamp() function – Python
How to clamp floating numbers in Python
Python | PyTorch sin() method
Python | PyTorch sinh() method
Python | PyTorch cosh() method
Python | PyTorch tanh() method
Python | PyTorch cos() method
Python | PyTorch tan() method
Python | PyTorch asin() method
Python | PyTorch acos() method
Please Login to comment…