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apache--tvm/python/tvm/s_tir/dlight/gpu/rmsnorm.py
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chore: import upstream snapshot with attribution
2026-07-13 13:36:25 +08:00

144 lines
4.6 KiB
Python

# 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.
# pylint: disable=missing-docstring
"""A RMS norm schedule rule for GPU operators."""
import tvm
from tvm import tirx
from tvm.ir import Call
from tvm.target import Target
from tvm.tirx import BufferStore, SBlock
from tvm.tirx.expr import BufferLoad, Cast
from ..base import ScheduleRule
def identify_cast_or_load_block(block: SBlock) -> 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: SBlock) -> 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("tirx.rsqrt")
class RMSNorm(ScheduleRule):
"""A rule for RMS norm."""
def apply( # pylint: disable=too-many-locals,missing-docstring
self,
func: tirx.PrimFunc,
target: Target,
_: bool,
) -> "tvm.s_tir.Schedule":
if target.kind.name == "cuda":
num_tx = 512
elif target.kind.name == "opencl":
num_tx = 256
else:
num_tx = 64
sch = tvm.s_tir.Schedule(func)
root = sch.get_sblock(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