PyTorch torch.exp()
method returns a new tensor after getting the exponent of the elements of the input tensor.
Syntax:
torch.exp(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.randn( 6 )
print (a)
# Applying the exp function and # storing the result in 'out' out = torch.exp(a)
print (out)
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Output:
1.0532 -1.9300 0.6392 -0.7519 0.9133 0.3998 [torch.FloatTensor of size 6] 2.8667 0.1451 1.8949 0.4715 2.4925 1.4915 [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 , 3 ])
print (a)
# Applying the exp function and # storing the result in 'out' out = torch.exp(a)
print (out)
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Output:
1 4 6 3 [torch.FloatTensor of size 4] 2.7183 54.5981 403.4288 20.0855 [torch.FloatTensor of size 4]
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