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cat_dog_classifier.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:57f43885cf2dac0be082e7107b921821cc02641999d75e7c96068cc918c12c0d
+size 228053947

model.py

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+
+from torch import manual_seed, nn
+from torchvision import transforms, models
+
+def create_model_alexnet(num_classes:int=2, seed:int=42):
+    """Creates model and transforms.
+
+    Args:
+        num_classes (int, optional): number of classes in the classifier head, defaults to 2.
+        seed (int, optional): random seed value. Defaults to 42.
+
+    Returns:
+        model (torch.nn.Module): Alexnet model.
+        transforms (torchvision.transforms): Alexnet image transforms.
+    """
+    # Create Alexnet pretrained weights, transforms and model
+    weights = models.AlexNet_Weights.IMAGENET1K_V1.DEFAULT
+    auto_transform = weights.transforms()
+    model_alexnet = models.alexnet(weights=weights)
+
+    # Freeze all layers in base model
+    for param in model_alexnet.parameters():
+        param.requires_grad = False
+
+    # Change classifier head with random seed for reproducibility
+    manual_seed(seed)
+    model_alexnet.classifier[6] = nn.Linear(4096, out_features=num_classes)
+    return model_alexnet, auto_transform

requirements.txt

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+torch==2.0.1+cu118
+torchvision==0.15.2+cu118
+gradio==3.47.1