| import json |
| import requests |
| import re |
| from relbert import RelBERT |
| import gradio as gr |
|
|
| model = RelBERT(model='relbert/relbert-roberta-large') |
|
|
|
|
| def get_example(): |
| url = "https://huggingface.co/datasets/relbert/analogy_questions/raw/main/dataset/sat/test.jsonl" |
| r = requests.get(url) |
| example = [json.loads(i) for i in r.content.decode().split('\n') if len(i) > 0] |
| return example |
|
|
|
|
| def cosine_similarity(a, b, zero_vector_mask: float = -100): |
| norm_a = sum(map(lambda x: x * x, a)) ** 0.5 |
| norm_b = sum(map(lambda x: x * x, b)) ** 0.5 |
| if norm_b * norm_a == 0: |
| return zero_vector_mask |
| return sum(map(lambda x: x[0] * x[1], zip(a, b)))/(norm_a * norm_b) |
|
|
|
|
| def clean(text): |
| text = re.sub(r"\A\s+", "", text) |
| text = re.sub(r"\s+\Z", "", text) |
| return text |
|
|
|
|
| def greet( |
| query, |
| candidate_1, |
| candidate_2, |
| candidate_3, |
| candidate_4, |
| candidate_5, |
| candidate_6): |
| query = [clean(i) for i in query.split(',')] |
| |
| if len(query) == 0: |
| raise ValueError(f'ERROR: query is empty {query}') |
| if len(query) == 1: |
| raise ValueError(f'ERROR: query contains single word {query}') |
| if len(query) > 2: |
| raise ValueError(f'ERROR: query contains more than two word {query}') |
|
|
| pairs = [] |
| pairs_id = [] |
| for n, i in enumerate([ |
| candidate_1, |
| candidate_2, |
| candidate_3, |
| candidate_4, |
| candidate_5, |
| candidate_6 |
| ]): |
| if i == '': |
| continue |
| candidate = [clean(x) for x in i.split(',')] |
| if len(candidate) == 1: |
| raise ValueError(f'ERROR: candidate {n + 1} contains single word {candidate}') |
| if len(candidate) > 2: |
| raise ValueError(f'ERROR: candidate {n + 1} contains more than two word {candidate}') |
| pairs.append(candidate) |
| pairs_id.append(n+1) |
| if len(pairs_id) < 2: |
| raise ValueError(f'ERROR: please specify at least two candidates: {pairs}') |
| vectors = model.get_embedding(pairs+[query]) |
| vector_q = vectors.pop(-1) |
| sims = [] |
| for v in vectors: |
| sims.append(cosine_similarity(v, vector_q)) |
| output = {f'candidate {i}: [{p[0]}, {p[1]}]': s for i, s, p in zip(pairs_id, sims, pairs)} |
| return output |
|
|
|
|
| examples = get_example()[:15] |
| examples = [[','.join(i['stem'])] + [','.join(c) for c in i['choice'] + [''] * (6 - len(i['choice']))] for i in examples] |
| demo = gr.Interface( |
| fn=greet, |
| inputs=[ |
| gr.Textbox(lines=1, placeholder="Query Word Pair (separate by comma)"), |
| gr.Textbox(lines=1, placeholder="Candidate Word Pair 1 (separate by comma)"), |
| gr.Textbox(lines=1, placeholder="Candidate Word Pair 2 (separate by comma)"), |
| gr.Textbox(lines=1, placeholder="Candidate Word Pair 3 (separate by comma)"), |
| gr.Textbox(lines=1, placeholder="Candidate Word Pair 4 (separate by comma)"), |
| gr.Textbox(lines=1, placeholder="Candidate Word Pair 5 (separate by comma)"), |
| gr.Textbox(lines=1, placeholder="Candidate Word Pair 6 (separate by comma)"), |
| ], |
| outputs="label", |
| examples=examples |
| ) |
| demo.launch(show_error=True) |
|
|
