PyTorch torch.log()
method gives a new tensor having the natural logarithm of the elements of input tensor.
Syntax:
torch.log(input, out=None)
Arguments
- input: This is input tensor.
- 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.FloatTensor([ 5 , 6 , 7 , 4 ])
print (a)
# Applying the log function and # storing the result in 'out' out = torch.log(a)
print (out)
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Output:
5 6 7 4 [torch.FloatTensor of size 4] 1.6094 1.7918 1.9459 1.3863 [torch.FloatTensor of size 4]
Example 2:
# Importing the PyTorch library import torch
# A constant tensor of size n a = torch.FloatTensor([ 1.45 , 2.3 , 10 ])
print (a)
# Applying the log function and # storing the result in 'out' out = torch.log(a)
print (out)
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Output:
1.4500 2.3000 10.0000 [torch.FloatTensor of size 3] 0.3716 0.8329 2.3026 [torch.FloatTensor of size 3]
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