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PyTorch – torch.log2() Method
We use the torch.log2() method to compute logarithm to the base 2 of the elements of a tensor. It returns a new tensor with the logarithm values of the elements of the original input tensor. It takes a tensor as the input parameter and outputs a tensor.
Syntax
torch.log2(input)
where input is a PyTorch tensor.
It returns a new tensor with logarithm base 2 values.
Steps
Import the torch library. Make sure you have it already installed.
import torch
Create a tensor and print it.
tensor1 = torch.rand(5,3) print("Tensor:", tensor1)
Compute torch.log2(input) and optionally assign this value to a new variable. Here, input is the created tensor.
logb2 = torch.log2(tensor1)
Print the resultant tensor.
print("logarithm base 2 of elements:
",logb2)
Example 1
The following Python program shows how to compute the logarithm to the base 2 of the elements of the input tensor in PyTorch.
# import torch library import torch # create a 2D tensor tensor1 = torch.rand(5,3) print("Tensor:", tensor1) # compute logarithm base 2 of the elements of above tensor logb2 = torch.log2(tensor1) print("logarithm base 2 of elements:
",logb2)
Output
Tensor: tensor([[0.5755, 0.3263, 0.3598], [0.0498, 0.0915, 0.0119], [0.6760, 0.6329, 0.7446], [0.5575, 0.6406, 0.2418], [0.4944, 0.7194, 0.9808]]) logarithm base 2 of elements: tensor([[-0.7970, -1.6158, -1.4749], [-4.3272, -3.4495, -6.3959], [-0.5650, -0.6599, -0.4255], [-0.8430, -0.6426, -2.0480], [-1.0162, -0.4751, -0.0279]])
Example 2
# import required library import torch # create a 1D tensor t = torch.tensor([1,2,3,4,5]) print("Tensor:", tensor1) # compute logarithm base 2 of the elements of above tensor logb2 = torch.log2(t) print("logarithm base 2:
",logb2)
Output
Tensor: tensor([1, 2, 3, 3, 4, 5]) logarithm base 2: tensor([0.0000, 1.0000, 1.5850, 2.0000, 2.3219])
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