model.py

import torch
import torchvision
from torch import nn



def create_effnetb2():
    torch.manual_seed(42)
    torch.cuda.manual_seed(42)


    effnetb2_weights = torchvision.models.EfficientNet_B2_Weights.DEFAULT
    transforms = effnetb2_weights.transforms()
    model = torchvision.models.efficientnet_b2(weights=effnetb2_weights)
    for param in model.parameters():
        param.requires_grad = False

    model.classifier = nn.Sequential(
        nn.Dropout(p=0.3, inplace=True), 
        nn.Linear(in_features=1408, 
                  out_features=3)) 
    model.name ='effnetb2'
    return model, transforms