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import json |
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import random |
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from pathlib import Path |
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from typing import Dict, List |
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from datetime import datetime |
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from loguru import logger |
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from models import DocumentAsset |
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class SplitManager: |
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"""Manages train/test/validation splits for documents.""" |
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def __init__( |
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self, |
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train_ratio: float = 0.6, |
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test_ratio: float = 0.25, |
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validation_ratio: float = 0.15, |
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random_seed: int = 42 |
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): |
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self.train_ratio = train_ratio |
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self.test_ratio = test_ratio |
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self.validation_ratio = validation_ratio |
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self.random_seed = random_seed |
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if abs(train_ratio + test_ratio + validation_ratio - 1.0) > 0.001: |
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raise ValueError("Split ratios must sum to 1.0") |
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def create_split( |
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self, |
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documents_by_type: Dict[str, List[DocumentAsset]] |
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) -> Dict[str, Dict[str, List[str]]]: |
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"""Create stratified train/test/validation split. |
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Returns: |
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Dict with structure: {split_name: {doc_type: [doc_names]}} |
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""" |
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random.seed(self.random_seed) |
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splits = { |
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'train': {}, |
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'test': {}, |
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'validation': {} |
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} |
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for doc_type, documents in documents_by_type.items(): |
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doc_names = [doc.doc_name for doc in documents] |
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random.shuffle(doc_names) |
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total = len(doc_names) |
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train_end = int(total * self.train_ratio) |
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test_end = train_end + int(total * self.test_ratio) |
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splits['train'][doc_type] = doc_names[:train_end] |
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splits['test'][doc_type] = doc_names[train_end:test_end] |
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splits['validation'][doc_type] = doc_names[test_end:] |
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logger.info(f"Created split: train={self._count_docs(splits['train'])}, " |
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f"test={self._count_docs(splits['test'])}, " |
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f"val={self._count_docs(splits['validation'])}") |
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return splits |
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def save_split(self, splits: Dict, output_path: str): |
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"""Save split mapping to JSON.""" |
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Path(output_path).parent.mkdir(parents=True, exist_ok=True) |
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split_data = { |
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'created_at': datetime.now().isoformat(), |
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'split_config': { |
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'train_ratio': self.train_ratio, |
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'test_ratio': self.test_ratio, |
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'validation_ratio': self.validation_ratio, |
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'random_seed': self.random_seed, |
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'stratified': True |
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}, |
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'splits': splits, |
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'statistics': { |
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'train': self._get_statistics(splits['train']), |
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'test': self._get_statistics(splits['test']), |
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'validation': self._get_statistics(splits['validation']) |
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} |
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} |
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with open(output_path, 'w') as f: |
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json.dump(split_data, f, indent=2) |
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logger.info(f"Saved split mapping to {output_path}") |
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def load_split(self, split_path: str) -> Dict[str, Dict[str, List[str]]]: |
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"""Load split mapping from JSON.""" |
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with open(split_path, 'r') as f: |
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split_data = json.load(f) |
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logger.info(f"Loaded split mapping from {split_path}") |
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return split_data['splits'] |
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def _count_docs(self, split: Dict[str, List[str]]) -> int: |
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"""Count total documents in a split.""" |
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return sum(len(docs) for docs in split.values()) |
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def _get_statistics(self, split: Dict[str, List[str]]) -> Dict[str, int]: |
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"""Get statistics for a split.""" |
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stats = {'total': self._count_docs(split)} |
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for doc_type, docs in split.items(): |
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stats[doc_type] = len(docs) |
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return stats |
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