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"""app_creation.ipynb |
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Automatically generated by Colaboratory. |
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Original file is located at |
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https://colab.research.google.com/drive/1sguK4GohScbDFj7Toyodw7faqhPrfc1a |
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""" |
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import json |
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import torch |
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import gradio as gr |
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import onnxruntime as rt |
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from transformers import AutoTokenizer |
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tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased") |
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with open("encoded_keywords.json", "r") as fp: |
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encode_keywords = json.load(fp) |
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keywords = list(encode_keywords.keys()) |
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inf_session = rt.InferenceSession('bert_quantized.onnx') |
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input_name = inf_session.get_inputs()[0].name |
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output_name = inf_session.get_outputs()[0].name |
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def classify_keywords(abstract): |
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input_ids = tokenizer(abstract)['input_ids'][:512] |
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logits = inf_session.run([output_name], { |
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input_name: [input_ids] |
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})[0] |
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logits = torch.FloatTensor(logits) |
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probs = torch.sigmoid(logits)[0] |
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return dict(zip(keywords, map(float, probs))) |
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label = gr.Label(num_top_classes = 5) |
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interface = gr.Interface( |
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fn = classify_keywords, |
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inputs = "text", |
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outputs = label |
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) |
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interface.launch() |
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