Revert "Updated notebook folders"

This reverts commit 06728004b6.

training/01.train-hyperparameter-tune-deploy-with-pytorch/pytorch_score.py

@@ -0,0 +1,57 @@
+# Copyright (c) Microsoft. All rights reserved.
+# Licensed under the MIT license.
+
+import torch
+import torch.nn as nn
+from torchvision import transforms
+import json
+import base64
+from io import BytesIO
+from PIL import Image
+
+from azureml.core.model import Model
+
+
+def preprocess_image(image_file):
+    """Preprocess the input image."""
+    data_transforms = transforms.Compose([
+        transforms.Resize(256),
+        transforms.CenterCrop(224),
+        transforms.ToTensor(),
+        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
+    ])
+
+    image = Image.open(image_file)
+    image = data_transforms(image).float()
+    image = torch.tensor(image)
+    image = image.unsqueeze(0)
+    return image
+
+
+def base64ToImg(base64ImgString):
+    base64Img = base64ImgString.encode('utf-8')
+    decoded_img = base64.b64decode(base64Img)
+    return BytesIO(decoded_img)
+
+
+def init():
+    global model
+    model_path = Model.get_model_path('pytorch-hymenoptera')
+    model = torch.load(model_path, map_location=lambda storage, loc: storage)
+    model.eval()
+
+
+def run(input_data):
+    img = base64ToImg(json.loads(input_data)['data'])
+    img = preprocess_image(img)
+
+    # get prediction
+    output = model(img)
+
+    classes = ['ants', 'bees']
+    softmax = nn.Softmax(dim=1)
+    pred_probs = softmax(model(img)).detach().numpy()[0]
+    index = torch.argmax(output, 1)
+
+    result = {"label": classes[index], "probability": str(pred_probs[index])}
+    return result