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- # schedulers/lnaive_scheduler.py
- from .lnaive_nb import naive_network_benchmarking_with_budget
- # 追加:重要度に比例して C_total を N ペアへ割り当てる
- def _allocate_budget_by_importance(weights, C_total: int):
- # クリップ&型
- w = [max(0.0, float(x)) for x in weights]
- W = sum(w)
- if C_total <= 0:
- return [0] * len(w)
- if W <= 0.0:
- # 全て0なら均等割
- base = C_total // max(1, len(w))
- rem = C_total - base * len(w)
- alloc = [base] * len(w)
- for i in range(rem):
- alloc[i] += 1
- return alloc
- # 連続値の割当 → 切り捨て → 余りを小数部の大きい順で配分
- quotas = [C_total * wi / W for wi in w]
- floors = [int(q) for q in quotas]
- rem = C_total - sum(floors)
- frac = [(q - f, idx) for idx, (q, f) in enumerate(zip(quotas, floors))]
- frac.sort(reverse=True) # 小数部の大きい順
- for k in range(rem):
- floors[frac[k][1]] += 1
- return floors
- def w_naive_budget_scheduler(
- node_path_list, # 例: [2, 2, 2] … 各ペアのパス本数
- importance_list, # 例: [0.3, 0.5, 0.7] … 長さは node_path_list と同じ(ここでは未使用)
- bounces, # 例: [1,2,3,4](重複なし)
- C_total, # 総予算(切り捨て配分、超過しない)
- network_generator, # callable: (path_num, pair_idx) -> network
- return_details=False,
- ):
- num_pairs = len(node_path_list)
- assert num_pairs == len(importance_list), "length mismatch: node_path_list vs importance_list"
- if num_pairs == 0:
- return ([], 0, []) if return_details else ([], 0)
- assert len(bounces) == len(set(bounces)), "bounces must be unique"
- assert all(isinstance(w, int) and w > 0 for w in bounces), "bounces must be positive ints"
- C_per_pair_list = _allocate_budget_by_importance(importance_list, int(C_total))
- per_pair_results = []
- per_pair_details = []
- total_cost = 0
- for pair_idx, path_num in enumerate(node_path_list):
- if path_num <= 0:
- per_pair_results.append((False, 0, None))
- if return_details:
- per_pair_details.append({"alloc_by_path": {}, "est_fid_by_path": {}})
- continue
- network = network_generator(path_num, pair_idx)
- path_list = list(range(1, path_num + 1))
- C_pair = int(C_per_pair_list[pair_idx]) # ★追加
- if return_details:
- correctness, cost, best_path_fidelity, alloc_by_path, est_fid_by_path = \
- naive_network_benchmarking_with_budget(
- network, path_list, list(bounces), C_pair, return_details=True
- )
- per_pair_details.append({
- "alloc_by_path": {int(k): int(v) for k, v in alloc_by_path.items()},
- "est_fid_by_path": {int(k): float(v) for k, v in est_fid_by_path.items()},
- })
- else:
- correctness, cost, best_path_fidelity = naive_network_benchmarking_with_budget(
- network, path_list, list(bounces), C_pair
- )
- per_pair_results.append((bool(correctness), int(cost), best_path_fidelity))
- total_cost += int(cost)
- return (per_pair_results, total_cost, per_pair_details) if return_details \
- else (per_pair_results, total_cost)
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