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app.py

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+import gradio as gr
+import onnxruntime as rt
+from transformers import AutoTokenizer
+import torch, json
+
+tokenizer = AutoTokenizer.from_pretrained("distilroberta-base")
+
+with open("genre_types_encoded_multi_class.json", "r") as fp:
+  encode_genre_types = json.load(fp)
+
+genres = list(encode_genre_types.keys())
+
+
+inf_session = rt.InferenceSession('paper_task_classifier_quantized.onnx')
+input_name = inf_session.get_inputs()[0].name
+output_name = inf_session.get_outputs()[0].name
+
+
+def classify_film_genre(description):
+  input_ids = tokenizer(description)['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))) 
+
+label = gr.outputs.Label(num_top_classes=5)
+iface = gr.Interface(fn=classify_film_genre, inputs="text", outputs=label)
+iface.launch(inline=False)
+

film_genre_classifier_quantized.onnx

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+version https://git-lfs.github.com/spec/v1
+oid sha256:67882ca32c6eb286e4922f000644491d3a386fcfb9bd8f81b17536bbe55d0c97
+size 82588680

genre_types_encoded_multi_class.json

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+{"Drama": 0, "Crime": 1, "Adventure": 2, "Biography": 3, "War": 4, "History": 5, "Mystery": 6, "Romance": 7, "Thriller": 8, "Film-Noir": 9, "Comedy": 10, "Musical": 11, "Animation": 12, "Family": 13, "Fantasy": 14, "Action": 15, "Western": 16, "Music": 17, "Documentary": 18, "Sport": 19, "Sci-Fi": 20, "Horror": 21, "News": 22, "Unknown": 23, "Reality-TV": 24, "Talk-Show": 25, "Game-Show": 26}

requirements.txt

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+gradio==3.17.0
+onnxruntime==1.13.1
+torch==1.13.1
+transformers==4.26.0