Update app.py

app.py

@@ -95,13 +95,15 @@ def prod_function(transformer_model, prod_dl, prod_data):
 
     # Find Embedding of the image to be evaluated
     with torch.no_grad():
-        emb_prod = accelerated_model(**acclerated_prod_data)
+        img_prod = acclerated_prod_data['pixel_values']
+        emb_prod = accelerated_model(img_prod)
 
     prod_preds = []
 
     for batch in acclerated_prod_dl:
+        img = batch['pixel_values']
         with torch.no_grad():
-            emb = accelerated_model(**batch)
+            emb = accelerated_model(img)
         distance = F.pairwise_distance(emb, emb_prod)
 
         prod_preds.append(distance)