PyTorch .log()

In PyTorch, the .log() function computes the natural logarithm of each element in the input tensor. This is mathematically equivalent to applying the function $y_i = log_{e}(x_i)$ element-wise, where $log_{e}$ is the natural logarithm.

Syntax

torch.log(input, *, out=None) → Tensor

Parameters:

• input: The input tensor containing elements for which the logarithm will be computed.
• out (optional): Output tensor to store the result. Must have the same shape as input.

Return value:

Returns a new tensor where each element is the natural logarithm of the corresponding element within the input tensor.

Example

The following example shows how to compute the element-wise natural logarithm of a tensor using torch.log():

import torch
import math

# Define a tensor
x = torch.tensor([7.0 , 8.0 , 9.0 , math.log(3.)])

# Compute the natural logarithm
result = torch.log(x)

print(result)

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Here is the output:

tensor([1.9459, 2.0794, 2.1972, 0.0940])

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