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from relbert import RelBERT |
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import gradio as gr |
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model = RelBERT(model='relbert/relbert-roberta-large') |
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def cosine_similarity(a, b, zero_vector_mask: float = -100): |
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norm_a = sum(map(lambda x: x * x, a)) ** 0.5 |
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norm_b = sum(map(lambda x: x * x, b)) ** 0.5 |
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if norm_b * norm_a == 0: |
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return zero_vector_mask |
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return sum(map(lambda x: x[0] * x[1], zip(a, b)))/(norm_a * norm_b) |
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def greet( |
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query, |
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candidate_1, |
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candidate_2, |
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candidate_3, |
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candidate_4, |
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candidate_5, |
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candidate_6, |
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candidate_7, |
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candidate_8, |
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candidate_9, |
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candidate_10): |
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pairs = [] |
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pairs_id = [] |
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for n, i in enumerate([ |
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candidate_1, |
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candidate_2, |
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candidate_3, |
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candidate_4, |
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candidate_5, |
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candidate_6, |
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candidate_7, |
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candidate_8, |
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candidate_9, |
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candidate_10 |
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]): |
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query = query.split(',') |
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if len(query) == 0: |
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raise ValueError(f'ERROR: query is empty {query}') |
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if len(query) == 1: |
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raise ValueError(f'ERROR: query contains single word {query}') |
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if len(query) > 2: |
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raise ValueError(f'ERROR: query contains more than two word {query}') |
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if i != '': |
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if len(i.split(',')) == 1: |
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raise ValueError(f'ERROR: candidate {n + 1} contains single word {i.split(",")}') |
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if len(i.split(',')) > 2: |
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raise ValueError(f'ERROR: candidate {n + 1} contains more than two word {i.split(",")}') |
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pairs.append(i.split(',')) |
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pairs_id.append(n+1) |
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if len(pairs_id) < 2: |
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raise ValueError(f'ERROR: please specify at least two candidates: {pairs}') |
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vectors = model.get_embedding(pairs+[query]) |
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vector_q = vectors.pop(-1) |
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sims = [] |
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for v in vectors: |
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sims.append(cosine_similarity(v, vector_q)) |
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output = sorted(list(zip(pairs_id, sims, pairs)), key=lambda _x: _x[1], reverse=True) |
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output = {f'candidate {n}: [{p[0]}, {p[1]}]': s for n, (i, s, p) in enumerate(output)} |
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return output |
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demo = gr.Interface( |
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fn=greet, |
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inputs=[ |
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gr.Textbox(lines=1, placeholder="Query Word Pair (separate by comma)"), |
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gr.Textbox(lines=1, placeholder="Candidate Word Pair 1 (separate by comma)"), |
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gr.Textbox(lines=1, placeholder="Candidate Word Pair 2 (separate by comma)"), |
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gr.Textbox(lines=1, placeholder="Candidate Word Pair 3 (separate by comma)"), |
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gr.Textbox(lines=1, placeholder="Candidate Word Pair 4 (separate by comma)"), |
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gr.Textbox(lines=1, placeholder="Candidate Word Pair 5 (separate by comma)"), |
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gr.Textbox(lines=1, placeholder="Candidate Word Pair 6 (separate by comma)"), |
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gr.Textbox(lines=1, placeholder="Candidate Word Pair 7 (separate by comma)"), |
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gr.Textbox(lines=1, placeholder="Candidate Word Pair 8 (separate by comma)"), |
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gr.Textbox(lines=1, placeholder="Candidate Word Pair 9 (separate by comma)"), |
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gr.Textbox(lines=1, placeholder="Candidate Word Pair 10 (separate by comma)") |
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], |
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outputs="label", |
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examples=[ |
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["beauty,aesthete", "pleasure,hedonist", "emotion,demagogue", "opinion,sympathizer", "seance,medium", "luxury,ascetic"] + [''] * 5, |
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["classroom,desk", "bank,dollar", "church,pew", "studio,paintbrush", "museum,artifact"] + [''] * 6, |
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], |
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) |
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demo.launch(show_error=True) |
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