python-pytorchHow can I create a neural network using Python and PyTorch?

To create a neural network using Python and PyTorch, you will need to import the PyTorch library and define the model architecture. The following code block is an example of a basic neural network:

import torch
import torch.nn as nn

class Net(nn.Module):
    def __init__(self):
        super(Net, self).__init__()
        self.fc1 = nn.Linear(2, 4)
        self.fc2 = nn.Linear(4, 1)

    def forward(self, x):
        x = self.fc1(x)
        x = torch.sigmoid(x)
        x = self.fc2(x)
        x = torch.sigmoid(x)
        return x

net = Net()

The code above consists of the following parts:

1. import torch - imports the PyTorch library
2. import torch.nn as nn - imports the neural network module from PyTorch
3. class Net(nn.Module): - defines a class for the neural network
4. def __init__(self): - initializes the neural network
5. self.fc1 = nn.Linear(2, 4) - creates a linear layer with 2 input nodes and 4 output nodes
6. self.fc2 = nn.Linear(4, 1) - creates a linear layer with 4 input nodes and 1 output node
7. def forward(self, x): - defines the forward pass of the network
8. x = self.fc1(x) - applies the linear layer to the input
9. x = torch.sigmoid(x) - applies the sigmoid activation function to the output of the linear layer
10. x = self.fc2(x) - applies the second linear layer to the output of the first
11. x = torch.sigmoid(x) - applies the sigmoid activation function to the output of the second linear layer
12. return x - returns the output of the network
13. net = Net() - creates an instance of the neural network

For more information, please refer to the PyTorch documentation.

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