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# to you under the Apache License, Version 2.0 (the
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#
#   http://www.apache.org/licenses/LICENSE-2.0
#
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# pylint: disable=missing-docstring
"""A fallback schedule rule for GPU operators."""

from tvm import s_tir, tirx
from tvm.target import Target

from .. import base
from ..analysis import normalize_prim_func
from ..base import try_inline
from .base import GPUScheduleRule


def _has_internal_thread_env(stmt: tirx.Stmt) -> bool:
    """Check whether a statement already launches GPU threads internally,
    e.g. via `T.launch_thread` (AttrStmt "thread_extent") or nested
    thread-bound loops. Such blocks manage their own thread environment
    and must not be wrapped in an additional thread binding."""
    found = False

    def _visit(node):
        nonlocal found
        if isinstance(node, tirx.AttrStmt) and node.attr_key in ("thread_extent", "virtual_thread"):
            found = True
        elif isinstance(node, tirx.For) and node.kind == tirx.ForKind.THREAD_BINDING:
            found = True

    tirx.stmt_functor.post_order_visit(stmt, _visit)
    return found


class Fallback(GPUScheduleRule):
    """
    A fallback schedule rule for all GPU operators. It will try to inline all the blocks first,
    and then apply a simple block/grid mapping to the spatial loops on top of the remaining blocks.
    """

    def apply(  # pylint: disable=too-many-locals,missing-docstring
        self,
        func: tirx.PrimFunc,
        target: Target,
        _: bool,
    ) -> s_tir.Schedule:
        if not isinstance(func, tirx.PrimFunc) or not self.is_target_available(target):
            return None
        max_threads_per_block = base.max_threads_per_block(target)

        sch = s_tir.Schedule(func)
        block_infos = normalize_prim_func(sch)

        if block_infos is None:
            return None

        block_infos = try_inline(sch, block_infos)
        reduction_blocks: list[tuple[s_tir.schedule.SBlockRV, s_tir.schedule.LoopRV]] = []
        for block in block_infos:
            s_loops: list[s_tir.schedule.LoopRV] = []
            r_loops: list[s_tir.schedule.LoopRV] = []
            o_loops: list[s_tir.schedule.LoopRV] = []
            dom_kind = block.dom_kind()
            block = block.block_rv

            if any(
                [sch.get(loop_rv).thread_binding is not None for loop_rv in sch.get_loops(block)]
            ):
                continue

            if len(sch.get_loops(block)) == 0 and _has_internal_thread_env(sch.get(block).body):
                # The block (e.g. an opaque sort kernel) launches its own
                # threads; binding an outer loop would conflict with them.
                continue

            for loop, iter_type in zip(sch.get_loops(block), dom_kind):
                {"S": s_loops, "R": r_loops, "O": o_loops}[iter_type].append(loop)

            if not s_loops:
                s_loops.append(sch.add_unit_loop(block))
            sch.reorder(*s_loops, *r_loops, *o_loops)
            bx, tx = sch.split(  # pylint: disable=invalid-name
                sch.fuse(*s_loops),
                factors=[None, max_threads_per_block],
            )
            sch.bind(bx, "blockIdx.x")
            sch.bind(tx, "threadIdx.x")

            if len(r_loops) > 0:
                reduction_blocks.append((block, r_loops[0]))

        for block, r_loop in reduction_blocks:
            sch.decompose_reduction(block, r_loop)

        return sch
