CNN.py

"""
5.5
use 2x2 max_pool
conv layers just change channels of images
channels follow the order of [64, 128, 256, 512, 512, 512, 512]
"""
from torch import nn
import torch.nn.functional as f


class CNN(nn.Module):
    def __init__(self):
        super(CNN, self).__init__()
        self.model = nn.Sequential(
            nn.Conv2d(in_channels=3, out_channels=64, kernel_size=3, stride=1, padding=1),
            nn.BatchNorm2d(64),
            nn.ReLU(),
            nn.MaxPool2d(kernel_size=2, stride=2),
            nn.Conv2d(in_channels=64, out_channels=128, kernel_size=3, stride=1, padding=1),
            nn.BatchNorm2d(128),
            nn.ReLU(),
            nn.MaxPool2d(kernel_size=2, stride=2),
            nn.Conv2d(in_channels=128, out_channels=256, kernel_size=3, stride=1, padding=1),
            nn.BatchNorm2d(256),
            nn.ReLU(),
            nn.MaxPool2d(kernel_size=2, stride=2),
            nn.AvgPool2d(kernel_size=1, stride=1),
            nn.Flatten(),
            nn.Linear(in_features=262144, out_features=10)
        )

    def forward(self, x):
        x = self.model(x)
        return x