lenet.py

from abc import ABC
import torch.nn as nn


class LeNet(nn.Module, ABC):
    def __init__(self,  num_classes=10):
        super(LeNet, self).__init__()
        self.features = nn.Sequential(
            nn.Conv2d(1, 6, kernel_size=5),
            nn.ReLU(inplace=True),
            nn.MaxPool2d(kernel_size=2, stride=2),
            nn.Conv2d(6, 16, kernel_size=5),
            nn.ReLU(inplace=True),
            nn.MaxPool2d(kernel_size=2, stride=2),
        )
        self.classifier = nn.Sequential(
            nn.Linear(16 * 4 * 4, 120),
            nn.ReLU(inplace=True),
            nn.Dropout(),
            nn.Linear(120, 84),
            nn.ReLU(inplace=True),
            nn.Dropout(),
            nn.Linear(84, num_classes),
        )

    def forward(self, x):
        x = self.features(x)
        x = x.view(x.size(0), 16 * 4 * 4)
        x = self.classifier(x)
        return x