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# Copyright 2018 The apache/tvm Authors. All Rights Reserved.
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
#
# Modifications Copyright (c) Microsoft.
# The code below is mostly copied from apache/tvm fallback.py in dlight.
# pylint: disable=missing-docstring
"""A fallback schedule rule for GPU operators."""
from typing import List, Tuple
from tvm import tir
from tvm.target import Target
from ..base import normalize_prim_func, try_inline
from . import utils
from .base import GPUScheduleRule
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: tir.PrimFunc,
target: Target,
_: bool,
) -> tir.Schedule:
if not isinstance(func, tir.PrimFunc) or not self.is_target_available(target):
return None
max_threads_per_block = utils.max_threads_per_block(target)
sch = 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[tir.schedule.BlockRV, tir.schedule.LoopRV]] = []
for block in block_infos:
s_loops: List[tir.schedule.LoopRV] = []
r_loops: List[tir.schedule.LoopRV] = []
o_loops: List[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)
]
)
or len(sch.get_loops(block)) == 0
):
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
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