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import json |
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from itertools import product |
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import pandas as pd |
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parameters_min_e_freq = [4, 8, 12, 16] |
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parameters_max_p_freq = [100, 50, 25, 10] |
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stats = [] |
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for min_e_freq, max_p_freq in product(parameters_min_e_freq, parameters_max_p_freq): |
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with open(f"data/t_rex.filter_unified.min_entity_{min_e_freq}_max_predicate_{max_p_freq}.train.jsonl") as f: |
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train = [json.loads(i) for i in f.read().split('\n') if len(i) > 0] |
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with open(f"data/t_rex.filter_unified.min_entity_{min_e_freq}_max_predicate_{max_p_freq}.validation.jsonl") as f: |
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validation = [json.loads(i) for i in f.read().split('\n') if len(i) > 0] |
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with open(f"data/t_rex.filter_unified.min_entity_{min_e_freq}_max_predicate_{max_p_freq}.test.jsonl") as f: |
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test = [json.loads(i) for i in f.read().split('\n') if len(i) > 0] |
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stats.append({ |
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"data": f"filter_unified.min_entity_{min_e_freq}_max_predicate_{max_p_freq}", |
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"train": len(train), |
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"validation": len(validation), |
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"test": len(test) |
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}) |
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df = pd.DataFrame(stats) |
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df['total'] = df['train'] + df['validation'] + df['test'] |
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print(df.to_markdown(index=False)) |