dfcnn.py

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


class dfcnn(nn.Module):
    def __init__(self, num_classes, input_nc):
        super(dfcnn, self).__init__()
        self.layer1 = nn.Sequential(       
            nn.Conv2d(input_nc, 32, 3, 1, 1, bias=False),
            nn.BatchNorm2d(32),
            nn.ReLU(inplace = True),
            nn.Conv2d(32, 32, 3, 1, 1, bias=False),
            nn.BatchNorm2d(32),
            nn.ReLU(inplace = True),
            nn.MaxPool2d(2),   
        )
        self.layer2 = nn.Sequential(         
            nn.Conv2d(32, 64, 3, 1, 1, bias=False),
            nn.BatchNorm2d(64),
            nn.ReLU(inplace = True),
            nn.Conv2d(64, 64, 3, 1, 1, bias=False),
            nn.BatchNorm2d(64),
            nn.ReLU(inplace = True),             
            nn.MaxPool2d(2),                
        )
        self.layer3 = nn.Sequential(         
            nn.Conv2d(64, 128, 3, 1, 1, bias=False),
            nn.BatchNorm2d(128),
            nn.ReLU(inplace = True),
            nn.Conv2d(128, 128, 3, 1, 1, bias=False),
            nn.BatchNorm2d(128),
            nn.ReLU(inplace = True),             
            nn.MaxPool2d(2),                
        )
        self.layer4 = nn.Sequential(         
            nn.Conv2d(128, 256, 3, 1, 1, bias=False),
            nn.BatchNorm2d(256),
            nn.ReLU(inplace = True),
            nn.Conv2d(256, 256, 3, 1, 1, bias=False),
            nn.BatchNorm2d(256),
            nn.ReLU(inplace = True),
            nn.MaxPool2d(2),                        
        )
        self.layer5 = nn.Sequential(         
            nn.Conv2d(256, 512, 3, 1, 1, bias=False),
            nn.BatchNorm2d(512),
            nn.ReLU(inplace = True),
            nn.Conv2d(512, 512, 3, 1, 1, bias=False),
            nn.BatchNorm2d(512),
            nn.ReLU(inplace = True),                       
        )
        self.avgpool = nn.AdaptiveAvgPool2d((1, 1))
        self.out = nn.Linear(512, num_classes)   

    def forward(self, x):
        x = self.layer1(x)
        x = self.layer2(x)
        x = self.layer3(x)
        x = self.layer4(x)
        x = self.layer5(x)
        x = self.avgpool(x)
        x = x.view(x.size(0), -1)
        x = self.out(x)
        return x