import torch.nn as nn
from torchvision import models

# Base model
from architectures.Model import Model

class ResNet50(Model):
    
    def get(self):
        m = models.resnet50(weights=models.ResNet50_Weights.DEFAULT)
        
        # freez all layers
        for param in m.parameters():
            param.requires_grad = False

        # unfreez the last two
        for param in m.layer3.parameters(): param.requires_grad = True
        for param in m.layer4.parameters(): param.requires_grad = True

        m.fc = nn.Linear(m.fc.in_features, self.size)
        return m.to(self.device)