import torch.nn as nn
from torchvision import models


def build_model(num_classes, device):
    model = models.resnet18(
        weights=models.ResNet18_Weights.IMAGENET1K_V1
    )

    # Freezing everything
    for param in model.parameters():
        param.requires_grad = False

    # Unfreezing deeper layers
    for param in model.layer3.parameters():
        param.requires_grad = True

    for param in model.layer4.parameters():
        param.requires_grad = True

    # Replacing classifier for our number of classes
    in_features = model.fc.in_features
    model.fc = nn.Linear(in_features, num_classes)

    model = model.to(device)
    return model