model-quantization-aggregation/src/run_evidence_extraction.py at main · santidrj/model-quantization-aggregation · GitHub

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import os

from src.config import PROCESSED_DATA_DIR
from src.data.papers.entities import Paper, Papers
from src.data.papers.knowledge_extraction import KnowledgeExtractor


def extract_knowledge_from(paper: Paper):
    data = paper.read_data()

    knowledge_extractor = KnowledgeExtractor(
        data,
        paper=paper,
    )

    knowledge_extractor.extract_knowledge()

    os.makedirs(PROCESSED_DATA_DIR / paper.KEY, exist_ok=True)

    knowledge_extractor.improvement_metrics.write_parquet(
        PROCESSED_DATA_DIR / paper.KEY / "improvement_metrics.parquet"
    )

    statistics = knowledge_extractor.get_improvement_statistics()
    statistics.write_parquet(PROCESSED_DATA_DIR / paper.KEY / "improvement_statistics_by_configuration.parquet")

    statistics_by_precision = knowledge_extractor.get_improvement_statistics(by_precision=True)
    statistics_by_precision.write_parquet(
        PROCESSED_DATA_DIR / paper.KEY / "improvement_statistics_by_precision.parquet"
    )

    knowledge_extractor.save_effects_by_configuration(PROCESSED_DATA_DIR / paper.KEY / "effects_by_configuration.json")
    knowledge_extractor.save_effects_by_precision(PROCESSED_DATA_DIR / paper.KEY / "effects_by_precision.json")


# for paper in Papers:
#     print(f"Extracting knowledge from {paper.value.AUTHOR}")
#     extract_knowledge_from(paper.value)

extract_knowledge_from(Papers.DEPUTTER.value)