Add application file

app.py

@@ -1,7 +1,8 @@
 import gradio as gr
 import onnxruntime as rt 
 from transformers import AutoTokenizer
-import torch, json
+import torch
+import json
 
 tokenizer = AutoTokenizer.from_pretrained("distilroberta-base")
 
@@ -14,14 +15,17 @@ inf_session = rt.InferenceSession('movie-classifier.onnx')
 input_name = inf_session.get_inputs()[0].name
 output_name = inf_session.get_outputs()[0].name
 
-def classify_movie_genre(Overview):
+def classify_movie_genre(Overview, num_top_classes=5):
     input_ids = tokenizer(Overview)['input_ids'][:512]
     logits = inf_session.run([output_name], {input_name: [input_ids]})[0]
     logits = torch.FloatTensor(logits)
     probs = torch.sigmoid(logits)[0]
-    return dict(zip(genres, map(float, probs)))
     
+    # Get the top N predicted genres
+    top_genres = [genres[i] for i in probs.argsort(descending=True)[:num_top_classes]]
+    
+    return top_genres
 
-label = gr.outputs.Label(num_top_classes=3)
+label = gr.outputs.Label()
 iface = gr.Interface(fn=classify_movie_genre, inputs="text", outputs=label)
-iface.launch(inline=False)
+iface.launch(inline=False)