Upload model.py

model.py

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+import torch
+import torchvision
+from torch import nn
+
+def create_effnetb2_model(seed: int=42 ,num_classes: int=3):
+   weights = torchvision.models.EfficientNet_B2_Weights.DEFAULT
+   effnet_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 ,bias=True)
+   )
+
+   return model ,effnet_transforms