models/resnet_model.py

import torch
import torch.nn as nn
import torchvision.models as models

class ResNet18(nn.Module):
    def __init__(self, num_classes=15):
        super(ResNet18, self).__init__()
        self.model = models.resnet18(weights=models.ResNet18_Weights.DEFAULT)
        # Replace the last fully connected layer
        self.model.fc = nn.Linear(self.model.fc.in_features, num_classes)

    def forward(self, x):
        x = self.model.conv1(x)
        x = self.model.bn1(x)
        x = self.model.relu(x)
        x = self.model.maxpool(x)

        x = self.model.layer1(x)
        x = self.model.layer2(x)
        x = self.model.layer3(x)
        x = self.model.layer4(x)

        x = self.model.avgpool(x)
        x = torch.flatten(x, 1)   # <-- here torch.flatten is used, so torch must be imported
        x = self.model.fc(x)

        return x