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a3f2e4d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 | # 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 rmsnorm.py in dlight.
# pylint: disable=missing-docstring
"""A RMS norm schedule rule for GPU operators."""
from bitblas import tvm
from tvm import tir
from tvm.tir import Block, BufferStore
from tvm.tir.expr import Cast, BufferLoad, Call
from tvm.target import Target
from ..base import ScheduleRule
def identify_cast_or_load_block(block: Block) -> bool:
if len(block.reads) != 1 or len(block.writes) != 1:
return False
if not isinstance(block.body, BufferStore):
return False
store = block.body
# check types
if isinstance(store.value, BufferLoad):
load = store.value
elif isinstance(store.value, Cast):
load = store.value.value
if not isinstance(load, BufferLoad):
return False
else:
return False
# check indices
if len(load.indices) != len(store.indices):
return False
for lhs, rhs in zip(load.indices, store.indices):
if not lhs.same_as(rhs):
return False
return True
def identify_rsqrt_block(block: Block) -> bool:
if len(block.reads) != 1 or len(block.writes) != 1:
return False
if not isinstance(block.body, BufferStore):
return False
store = block.body
if not isinstance(store.value, Call):
return False
call = store.value
op = call.op
return op == tvm.ir.op.Op.get("tir.rsqrt")
class RMSNorm(ScheduleRule):
"""A rule for RMS norm."""
def apply( # pylint: disable=too-many-locals,missing-docstring
self,
func: tir.PrimFunc,
target: Target,
_: bool,
) -> tir.Schedule:
if target.kind.name == "cuda":
num_tx = 512
else:
num_tx = 64
sch = tir.Schedule(func)
root = sch.get_block(name="root", func_name="main")
blocks = sch.get_child_blocks(root)
if not any([identify_rsqrt_block(sch.get(block)) for block in blocks]):
return None
read = sch.cache_read(block=blocks[0], read_buffer_index=0, storage_scope="local")
write = sch.cache_write(block=blocks[-1], write_buffer_index=0, storage_scope="local")
for block in blocks:
if identify_cast_or_load_block(sch.get(block)):
sch.compute_inline(block)
blocks = sch.get_child_blocks(root)
read, sqr, redsum, rsqrt, norm, write = blocks
if not identify_rsqrt_block(sch.get(rsqrt)):
return None
for name in [read, sqr, redsum, rsqrt, norm, write]:
loops = sch.get_loops(name)
sch.fuse(*loops[:-1])
block_loop, loops = sch.get_loops(block=read)
thread_loop, _, _ = sch.split(
loop=loops, factors=[num_tx, None, 8], preserve_unit_iters=True
)
sch.bind(block_loop, thread_axis="blockIdx.x")
sch.bind(thread_loop, thread_axis="threadIdx.x")
sch.vectorize(sch.get_loops(block=read)[-1])
sch.reverse_compute_at(block=sqr, loop=thread_loop)
sch.reverse_compute_at(block=redsum, loop=thread_loop)
sch.reverse_compute_at(block=rsqrt, loop=block_loop, index=-1)
sch.reverse_compute_at(block=norm, loop=block_loop, index=-1)
block_loop, loops = sch.get_loops(block=norm)
thread_loop, _, _ = sch.split(
loop=loops, factors=[num_tx, None, 8], preserve_unit_iters=True
)
sch.bind(thread_loop, thread_axis="threadIdx.x")
sch.reverse_compute_at(block=write, loop=thread_loop, index=-1)
sch.vectorize(sch.get_loops(block=write)[-1])
sch.set_scope(block=sqr, buffer_index=0, storage_scope="local")
sch.set_scope(block=redsum, buffer_index=0, storage_scope="local")
sch.set_scope(block=rsqrt, buffer_index=0, storage_scope="shared")
sch.set_scope(block=norm, buffer_index=0, storage_scope="local")
return sch
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