basic_model_pytorch.py

import torch
import torch.nn as nn
import torch.nn.functional as F


class Net(nn.Module):

    def __init__(self):
        super(Net, self).__init__()
        # Defining 3 linear layers but NOT the way they should be connected
        # Receives an array of length 240 and outputs one with length 120
        self.fc1 = nn.Linear(240, 120)
        # Receives an array of length 120 and outputs one with length 60
        self.fc2 = nn.Linear(120, 60)
        # Receives an array of length 60 and outputs one with length 10
        self.fc3 = nn.Linear(60, 10)

    def forward(self, x):
        # Defining the way that the layers of the model should be connected
        # Performs RELU on the output of layer 'self.fc1 = nn.Linear(240, 120)'
        x = F.relu(self.fc1(x))
        # Performs RELU on the output of layer 'self.fc2 = nn.Linear(120, 60)'
        x = F.relu(self.fc2(x))
        # Passes the array through the last linear layer 'self.fc3 = nn.Linear(60, 10)'
        x = self.fc3(x)
        return x


net = Net()