Python Coding challenge - Day 405| What is the output of the following Python Code?

 

Code Explanation:

Import the Required Module

import torch.nn as nn

This imports PyTorch’s neural network module, which contains various activation functions and layers.

Create a ReLU Activation Function

relu = nn.ReLU()

This initializes an instance of the ReLU (Rectified Linear Unit) function.

Apply ReLU to a Tensor

print(relu(torch.tensor([-2.0, 0.0, 3.0])))

torch.tensor([-2.0, 0.0, 3.0]) creates a PyTorch tensor with three values: -2.0, 0.0, 3.0.

relu() applies the ReLU activation function to each element of the tensor.

Understanding ReLU:

The ReLU function is defined as:

ReLU(x)=max(0,x)

Which means:

If the input value is negative, ReLU outputs 0.

If the input value is 0 or positive, ReLU outputs the same value.

Expected Output:

For the given tensor [-2.0, 0.0, 3.0]:

ReLU(-2.0) = max(0, -2.0) = 0.0

ReLU(0.0) = max(0, 0.0) = 0.0

ReLU(3.0) = max(0, 3.0) = 3.0

So the printed output will be:

tensor([0., 0., 3.])

Final Output:

tensor([0., 0., 3.])

[0.0, 0.0, 3.0][0.0, 0.0, 3.0]

[0.0,[0.0, 0.0, 3.00.0, 3.0][0.0, 0.0, 3.0]