| import torch | |
| import torchvision | |
| from torch import nn | |
| def create_effnetb2_model(num_classes:int= 3, | |
| seed:int= 40): | |
| weights= torchvision.models.EfficientNet_B2_Weights.DEFAULT | |
| transforms= weights.transforms() | |
| model= torchvision.models.efficientnet_b2(weights= weights) | |
| for param in model.parameters(): | |
| param.requires_grad= False | |
| torch.manual_seed(seed) | |
| model.classifier(nn.Sequential( | |
| nn.Dropout(0.3, inplace=True), | |
| nn.Linear(in_features= 1408, out_features= num_classes), | |
| ) | |
| return model, transforms | |