specifying pytorch version to fix model loading failure

app.py

@@ -5,6 +5,7 @@ from torchvision.transforms import v2
 import os
 import requests
 
+
 labels = ['Pastel',
             'Yellow Belly',
             'Enchi',
@@ -53,12 +54,12 @@ def predict(img, confidence):
     device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
     # Download model from GCS
-    model_path = os.environ.get('model_path')
+    model_path = os.getenv('model_path')
     response = requests.get(model_path)
 
     with open('model.pt', 'wb') as f:
         f.write(response.content)
-
+    
     checkpoint = torch.load('model.pt', map_location=device)
     densenet.load_state_dict(checkpoint['model_state_dict'])
 

requirements.txt

@@ -1,2 +1,2 @@
-torch
-torchvision
+torch==2.2.2
+torchvision==0.17.2