ahamedddd/FoodVision_Mini2

1import torch2import torchvision3 4from torch import nn5def create_effnetb2_model(num_classes:int=3, # default output classes = 3 (pizza, steak, sushi)6                          seed:int=42):7  # 1, 2, 3 Create EffNetB2 pretrained weights, transforms and model8  weights = torchvision.models.EfficientNet_B2_Weights.DEFAULT9  transforms = weights.transforms()10  model = torchvision.models.efficientnet_b2(weights=weights)11 12  # 4. Freeze all layers in the base model13  for param in model.parameters():14    param.requires_grad = False15 16  # 5. Change classifier head with random seed for reproducibility17  torch.manual_seed(seed)18  model.classifier = nn.Sequential(19      nn.Dropout(p=0.3, inplace=True),20      nn.Linear(in_features=1408, out_features=num_classes)21  )22 23  return model, transforms24