model.py

from torch import nn

# Define model
class NeuralNetwork(nn.Module):
    def __init__(self):
        super(NeuralNetwork, self).__init__()
        self.flatten = nn.Flatten()
        self.linear_relu_stack = nn.Sequential(
            nn.Conv2d(3, 8, 3, padding=1),
            nn.ReLU(),
            nn.MaxPool2d(2),

            nn.Conv2d(8, 16, 3, padding=1),
            nn.ReLU(),
            nn.MaxPool2d(2),

            nn.Conv2d(16, 32, 3, padding=1),
            nn.ReLU(),
            nn.MaxPool2d(2),

            nn.Conv2d(32, 32, 3, padding=1),
            nn.ReLU(),
            nn.Conv2d(32, 16, 3, padding=1),
            nn.ReLU(),
            nn.Conv2d(16, 32, 3, padding=1),
            nn.ReLU(),

            nn.Conv2d(32, 12, 1, padding=0),

            nn.AvgPool2d((3,1))
        )

    def forward(self, x):
        logits = self.linear_relu_stack(x)
        return logits