model.py

import torchvision
import torch
from torch import nn

"""Script to load and create and instance of effnetb2 """

def create_effnetb2_model(num_classes=101):
  weights=torchvision.models.EfficientNet_B2_Weights.DEFAULT
  transforms=weights.transforms()
  model=torchvision.models.efficientnet_b2(weights=weights)

  for params in model.parameters():
    params.requires_grad=False

  model.classifier = nn.Sequential(
      nn.Dropout(p=0.3, inplace=True),
      nn.Linear(in_features=1408, out_features=num_classes)
  )

  return model, transforms