Reformat python files

examples/alexnet/alexnet.py

@@ -1,35 +1,10 @@
 import sys
 
-import torch
 import torchvision
-from PIL import Image
-from torchvision import transforms
 
 sys.path.append('../../tools')  # Ugly hack 
 from utils import export_model_weights, print_model_parameters
 
-
-def predict(model, image_path):
-    input_image = Image.open(image_path)
-    preprocess = transforms.Compose([
-        transforms.Resize(256),
-        transforms.CenterCrop(227),
-        transforms.ToTensor(),
-        transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),
-    ])
-    input_tensor = preprocess(input_image)
-    input_batch = input_tensor.unsqueeze(0) # create a mini-batch as expected by the model
-
-    # move the input and model to GPU for speed if available
-    if torch.cuda.is_available():
-        input_batch = input_batch.to('cuda')
-        model.to('cuda')
-
-    with torch.no_grad():
-        output = model(input_batch)
-        print(torch.argmax(output))
-
-
 if __name__ == "__main__":
     alexnet = torchvision.models.alexnet(weights=torchvision.models.AlexNet_Weights.DEFAULT)
     print_model_parameters(alexnet)  # print layer names and number of parameters