| import torch | |
| import torchvision | |
| from torch import nn | |
| def create_effnetb2_model(num_classes:int=3, | |
| seed:int=42): | |
| # 1, 2, 3 Create EffNetB2 pretrained weights, transforms and model | |
| 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 | |
| model.classifier=nn.Sequential( | |
| nn.Dropout(p=0.3,inplace=True), | |
| nn.Linear(in_features=1408,out_features=num_classes) | |
| ) | |
| return model,transforms | |