import torch | |
import torchvision | |
from torch import nn | |
def create_effnetb2_model(num_classes:int=3, | |
seed:int=42): | |
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(p=0.3, inplace=True), | |
nn.Linear(in_features=1408, out_features=num_classes), | |
) | |
return model, transforms | |