"""分支决策路由: 按决策树推导分支, 重叠区由端到端时延模型仲裁.

决策树 (v0.98 §3.3 + 各分支理论文档):
  1. 前置归约: BatchA=1 或 BatchB=1 -> 转Matmul
                K=0 / K=1 -> 特殊分支 (AIV 向量通路)
  2. B >= C 且 BatchA==BatchB: 切B -> IterBatch 与 MergeBatch 仲裁
       仲裁规则 (v1.1 §4.5 统一分界):
         MergeBatch 最优 <=> K截断(k_L1=K) 且 b_core > b0*(T_comp+T_write)/T_cmd
         L1 绑定时 MergeBatch 恒劣于 IterBatch;
       两分支同时合法时用端到端时延模型 T_total 仲裁.
  3. StreamK 检查: P <= C/2 且满足切K条件 -> StreamK (B/M/N 买不满时买 K)
  4. 兜底: ASW_Basic 切 M/N (含降核模式)
"""

from __future__ import annotations

from .hardware import NpuSpec, ASCEND950PR
from .models import BmmCase, ImplPlan, HardwareTiming
from .branches.base import BranchResult
from .branches.merge_batch import MergeBatchBranch
from .branches.iter_batch import IterBatchBranch
from .branches.to_matmul import ToMatmulBranch
from .branches.special import SpecialBranch
from .branches.stream_k import StreamKBranch
from .branches.asw_basic import AswBasicBranch


class BranchRouter:
    """case -> 理论最优分支 + 方案 + 时延评估."""

    def __init__(self, spec: NpuSpec = ASCEND950PR):
        self.spec = spec
        self.merge_batch = MergeBatchBranch(spec)
        self.iter_batch = IterBatchBranch(spec)
        self.to_matmul = ToMatmulBranch(spec)
        self.special = SpecialBranch(spec)
        self.stream_k = StreamKBranch(spec)
        self.asw_basic = AswBasicBranch(spec)

    # ------------------------------------------------------------------
    def route(self, case: BmmCase) -> dict:
        """返回 {branch, plan, timing, arbitration, candidates}."""
        s = self.spec

        # 1) 前置归约: 转Matmul / 特殊分支
        if case.batch_a == 1 or case.batch_b == 1:
            r = self.to_matmul.analyze(case)
            return self._wrap(r, "BatchA=1或BatchB=1, 折叠转普通Matmul")
        if case.k <= 1:
            r = self.special.analyze(case)
            note = "K=0纯写值" if case.k == 0 else "K=1逐元素乘, 走AIV向量通路"
            return self._wrap(r, note)

        # 2) B >= C 且 BatchA==BatchB: IterBatch / MergeBatch
        if case.batch_c >= s.aic_num and case.batch_a == case.batch_b:
            return self._route_split_b(case)

        # 3) StreamK: P <= C/2 且切K条件满足
        sk = self.stream_k.analyze(case)
        if sk.capable:
            return self._wrap(sk, f"P<=C/2, B/M/N并行度买不满, 切K (grid_K={sk.plan.grid_k})")

        # 4) 兜底: ASW_Basic (含降核模式)
        asw = self.asw_basic.analyze(case)
        note = "ASW_Basic兜底"
        if sk.checks and not sk.capable:
            note += f" (StreamK未过: {sk.failed_conditions()})"
        return self._wrap(asw, note)

    # ------------------------------------------------------------------
    def _route_split_b(self, case: BmmCase) -> dict:
        mb = self.merge_batch.analyze(case)
        ib = self.iter_batch.analyze(case)

        candidates = []
        if mb.capable:
            candidates.append((self.merge_batch.name, mb))
        if ib.capable:
            candidates.append((self.iter_batch.name, ib))

        arbitration = ""
        if mb.capable and ib.capable:
            # 统一分界条件 + 端到端时延仲裁双保险
            mb_win, detail = self.merge_batch.beats_iterbatch(case)
            t_mb = mb.timing.t_total
            t_ib = ib.timing.t_total
            lat_win = self.merge_batch.name if t_mb <= t_ib else self.iter_batch.name
            win = self.merge_batch.name if mb_win else self.iter_batch.name
            arbitration = (
                f"两分支均合法, 仲裁: "
                f"[分界条件] MergeBatch最优={mb_win} ({detail}); "
                f"[时延模型] T_MergeBatch={t_mb*1e6:.2f}us vs T_IterBatch={t_ib*1e6:.2f}us -> {lat_win}更优; "
                f"[裁决] {win}" + ("" if win == lat_win else f" (分界条件与时延模型不一致, 以时延模型为准: {lat_win})")
            )
            if win != lat_win:
                win = lat_win  # 时延模型为最终裁决
        elif candidates:
            win = candidates[0][0]
            arbitration = f"仅 {win} 条件满足"
        else:
            # 切B分支都不满足, 尝试 StreamK 再回落 ASW
            sk = self.stream_k.analyze(case)
            if sk.capable:
                return self._wrap(sk, "切B分支条件不满足, 落 StreamK")
            asw = self.asw_basic.analyze(case)
            return self._wrap(
                asw,
                f"IterBatch/MergeBatch 进入条件均不满足, 回落 ASW_Basic; "
                f"IterBatch未过: {ib.failed_conditions()}; "
                f"MergeBatch未过: {mb.failed_conditions()}")

        chosen = mb if win == self.merge_batch.name else ib
        return {
            "branch": win,
            "plan": chosen.plan,
            "timing": chosen.timing,
            "arbitration": arbitration,
            "candidates": {n: r.capable for n, r in
                           [(self.merge_batch.name, mb), (self.iter_batch.name, ib)]},
        }

    # ------------------------------------------------------------------
    @staticmethod
    def _wrap(result: BranchResult, note: str) -> dict:
        return {
            "branch": result.plan.branch if result.plan else "未知",
            "plan": result.plan,
            "timing": result.timing,
            "arbitration": note + (f" | {result.note}" if result.note else ""),
            "candidates": {},
        }