LeNet.py

#!/usr/local/bin/python3.9
# -*- coding:utf-8 -*-
"""
@Author   : Haiy. Yi
@Time     : 2024/1/18 11:29
@File     : LeNet.py
@Software : PyCharm
@System   : MacOS catalina
"""
import sys
import os

sys.path.append(os.path.dirname(os.path.dirname(__file__)))
import torch.nn as nn
import torch.nn.functional as F
from Utils.registries import MODEL_REGISTRY


@MODEL_REGISTRY.register()
class LeNet(nn.Module):
    def __init__(self, cfg=None):
        super(LeNet, self).__init__()
        self.conv1 = nn.Conv2d(3, 16, 5)
        self.pool1 = nn.MaxPool2d(2, 2)
        self.conv2 = nn.Conv2d(16, 32, 5)
        self.pool2 = nn.MaxPool2d(2, 2)
        self.fc1 = nn.Linear(32 * 5 * 5, 120)
        self.fc2 = nn.Linear(120, 84)
        self.fc3 = nn.Linear(84, 10)

    def forward(self, x):
        x = F.relu(self.conv1(x))  # input(3, 32, 32) output(16, 28, 28)
        x = self.pool1(x)  # output(16, 14, 14)
        x = F.relu(self.conv2(x))  # output(32, 10, 10)
        x = self.pool2(x)  # output(32, 5, 5)
        x = x.view(-1, 32 * 5 * 5)  # output(32*5*5)
        x = F.relu(self.fc1(x))  # output(120)
        x = F.relu(self.fc2(x))  # output(84)
        x = self.fc3(x)  # output(10)
        return x