Delete train/splits.py with huggingface_hub

train/splits.py

@@ -1,77 +0,0 @@
-"""Deterministic stratified train/eval game split."""
-
-from __future__ import annotations
-
-import random
-from typing import Dict, FrozenSet, List, Set, Tuple
-
-from common.games_meta.game_tags import GAME_TAGS
-from constant_definitions.batch4.tag_constants import CATEGORIES
-from constant_definitions.game_constants import EVAL_ZERO, EVAL_ONE
-from constant_definitions.train.split_constants import (
-    MIN_EVAL_TAG_FRACTION_DENOMINATOR,
-    MIN_EVAL_TAG_FRACTION_NUMERATOR,
-    SPLIT_SEED,
-    TRAIN_FRACTION_DENOMINATOR,
-    TRAIN_FRACTION_NUMERATOR,
-)
-
-# Domain tags are used for stratification
-_DOMAIN_TAGS: List[str] = CATEGORIES["domain"]
-
-
-def get_train_eval_split(
-    seed: int = SPLIT_SEED,
-) -> Tuple[FrozenSet[str], FrozenSet[str]]:
-    """Return (train_games, eval_games) as frozen sets of game keys.
-
-    The split is deterministic for a given seed and stratified so that
-    every domain tag has at least ``MIN_EVAL_TAG_FRACTION`` representation
-    in the eval set.
-    """
-    all_games = sorted(GAME_TAGS.keys())
-    rng = random.Random(seed)
-
-    # Build domain -> games index
-    domain_to_games: Dict[str, List[str]] = {tag: [] for tag in _DOMAIN_TAGS}
-    for game_key in all_games:
-        tags = GAME_TAGS[game_key]
-        for dtag in _DOMAIN_TAGS:
-            if dtag in tags:
-                domain_to_games[dtag].append(game_key)
-
-    # Guarantee minimum eval representation per domain
-    eval_set: Set[str] = set()
-    for dtag in _DOMAIN_TAGS:
-        games_with_tag = domain_to_games[dtag]
-        if not games_with_tag:
-            continue
-        min_eval = _min_eval_count(len(games_with_tag))
-        already_in_eval = [g for g in games_with_tag if g in eval_set]
-        needed = min_eval - len(already_in_eval)
-        if needed > EVAL_ZERO:
-            candidates = [g for g in games_with_tag if g not in eval_set]
-            rng.shuffle(candidates)
-            for g in candidates[:needed]:
-                eval_set.add(g)
-
-    # Fill remaining eval slots up to target size
-    total = len(all_games)
-    target_train = (total * TRAIN_FRACTION_NUMERATOR) // TRAIN_FRACTION_DENOMINATOR
-    target_eval = total - target_train
-    remaining = [g for g in all_games if g not in eval_set]
-    rng.shuffle(remaining)
-    slots_to_fill = target_eval - len(eval_set)
-    if slots_to_fill > EVAL_ZERO:
-        for g in remaining[:slots_to_fill]:
-            eval_set.add(g)
-
-    train_set = frozenset(g for g in all_games if g not in eval_set)
-    return train_set, frozenset(eval_set)
-
-
-def _min_eval_count(tag_total: int) -> int:
-    """Minimum number of games with a given tag that must be in eval."""
-    _numer = tag_total * MIN_EVAL_TAG_FRACTION_NUMERATOR
-    result = (_numer + MIN_EVAL_TAG_FRACTION_DENOMINATOR - EVAL_ONE) // MIN_EVAL_TAG_FRACTION_DENOMINATOR
-    return max(result, EVAL_ONE)