from __future__ import annotations

from dataclasses import dataclass
from typing import Any

from .duration import op_type_value


COMPUTE_OP_TYPES = frozenset({"F", "B", "VF", "VB", "GF", "GB"})


@dataclass(frozen=True)
class PlanOp:
    id: str
    rank: int
    index: int
    original_index: int
    op_type: str
    microbatch_id: int | None
    chunk_id: int | None
    base_duration: float
    label: str

    @property
    def is_forward(self) -> bool:
        return self.op_type == "F"

    @property
    def is_backward(self) -> bool:
        return self.op_type == "B"


@dataclass(frozen=True)
class Plan:
    ops_by_rank: dict[int, list[PlanOp]]
    pp_size: int
    num_microbatches: int
    scheduler_name: str
    vpp_size: int = 1
    pipeline_layout: dict[str, int] | None = None

    @property
    def ops(self) -> list[PlanOp]:
        return [
            op
            for rank in sorted(self.ops_by_rank)
            for op in self.ops_by_rank[rank]
        ]

    @classmethod
    def from_scheduler(cls, scheduler: Any, *, include_op_types=None) -> "Plan":
        if not getattr(scheduler, "schedules", None):
            scheduler.generate_schedule()

        allowed = frozenset(include_op_types or COMPUTE_OP_TYPES)
        ops_by_rank: dict[int, list[PlanOp]] = {}
        pp_size = int(getattr(scheduler, "pp_size"))

        for rank in range(pp_size):
            rank_ops: list[PlanOp] = []
            for original_index, raw_op in enumerate(scheduler.schedules.get(rank, [])):
                op_value = op_type_value(getattr(raw_op, "op_type", ""))
                if op_value not in allowed:
                    continue

                rank_index = len(rank_ops)
                microbatch_id = getattr(raw_op, "microbatch_id", None)
                chunk_id = getattr(raw_op, "chunk_id", None)
                op_id = _make_op_id(rank, rank_index, op_value, microbatch_id, chunk_id)
                rank_ops.append(
                    PlanOp(
                        id=op_id,
                        rank=rank,
                        index=rank_index,
                        original_index=original_index,
                        op_type=op_value,
                        microbatch_id=microbatch_id,
                        chunk_id=chunk_id,
                        base_duration=float(getattr(raw_op, "duration", 0.0)),
                        label=str(raw_op),
                    )
                )
            ops_by_rank[rank] = rank_ops

        return cls(
            ops_by_rank=ops_by_rank,
            pp_size=pp_size,
            num_microbatches=int(getattr(scheduler, "num_microbatches")),
            scheduler_name=scheduler.__class__.__name__,
            vpp_size=int(getattr(scheduler, "vpp_size", 1)),
            pipeline_layout=getattr(scheduler, "pipeline_layout", None),
        )


def _make_op_id(
    rank: int,
    index: int,
    op_type: str,
    microbatch_id: int | None,
    chunk_id: int | None,
) -> str:
    mb = "none" if microbatch_id is None else str(microbatch_id)
    chunk = "none" if chunk_id is None else str(chunk_id)
    return f"r{rank}:i{index}:{op_type}:mb{mb}:c{chunk}"