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[MetaSchedule] Update scripts for subgraph tuning (apache#10501)
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137 changes: 137 additions & 0 deletions
137
python/tvm/meta_schedule/testing/run_subgraph_auto_scheduler.py
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| @@ -0,0 +1,137 @@ | ||
| # 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 limitatios | ||
| # under the License. | ||
| # pylint: disable=missing-docstring | ||
| import argparse | ||
| import os | ||
|
|
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| import tvm | ||
| from tvm import auto_scheduler | ||
| from tvm.meta_schedule.runner import RPCConfig | ||
| from tvm.meta_schedule.testing.te_workload import CONFIGS | ||
|
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| def _parse_args(): | ||
| args = argparse.ArgumentParser() | ||
| args.add_argument( | ||
| "--workload", | ||
| type=str, | ||
| required=True, | ||
| ) | ||
| args.add_argument( | ||
| "--target", | ||
| type=str, | ||
| required=True, | ||
| ) | ||
| args.add_argument( | ||
| "--num-trials", | ||
| type=int, | ||
| required=True, | ||
| ) | ||
| args.add_argument( | ||
| "--rpc-host", | ||
| type=str, | ||
| required=True, | ||
| ) | ||
| args.add_argument( | ||
| "--rpc-port", | ||
| type=int, | ||
| required=True, | ||
| ) | ||
| args.add_argument( | ||
| "--rpc-key", | ||
| type=str, | ||
| required=True, | ||
| ) | ||
| args.add_argument( | ||
| "--log-dir", | ||
| type=str, | ||
| required=True, | ||
| ) | ||
| parsed = args.parse_args() | ||
| parsed.target = tvm.target.Target(parsed.target) | ||
| parsed.rpc_workers = RPCConfig( | ||
| tracker_host=parsed.rpc_host, | ||
| tracker_port=parsed.rpc_port, | ||
| tracker_key=parsed.rpc_key, | ||
| session_timeout_sec=30, | ||
| ).count_num_servers(allow_missing=True) | ||
| return parsed | ||
|
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|
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| ARGS = _parse_args() | ||
|
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|
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| def main(): | ||
| log_file = os.path.join(ARGS.log_dir, f"{ARGS.workload}.json") | ||
| workload_func, params = CONFIGS[ARGS.workload] | ||
| params = params[0] # type: ignore | ||
| workload_func = auto_scheduler.register_workload(workload_func) | ||
|
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| if ARGS.target.kind.name == "llvm": | ||
| hardware_params = auto_scheduler.HardwareParams( | ||
| num_cores=int(ARGS.target.attrs["num-cores"]), | ||
| target=ARGS.target, | ||
| ) | ||
| elif ARGS.target.kind.name == "cuda": | ||
| hardware_params = auto_scheduler.HardwareParams( | ||
| num_cores=-1, | ||
| vector_unit_bytes=16, | ||
| cache_line_bytes=64, | ||
| max_shared_memory_per_block=int(ARGS.target.attrs["max_shared_memory_per_block"]), | ||
| max_threads_per_block=int(ARGS.target.attrs["max_threads_per_block"]), | ||
| max_vthread_extent=8, | ||
| warp_size=32, | ||
| ) | ||
| else: | ||
| raise NotImplementedError(f"Unsupported target {ARGS.target}") | ||
| task = auto_scheduler.SearchTask( | ||
| func=workload_func, | ||
| args=params, | ||
| target=ARGS.target, | ||
| hardware_params=hardware_params, | ||
| ) | ||
| runner = auto_scheduler.RPCRunner( | ||
| key=ARGS.rpc_key, | ||
| host=ARGS.rpc_host, | ||
| port=ARGS.rpc_port, | ||
| n_parallel=ARGS.rpc_workers, | ||
| number=3, | ||
| repeat=1, | ||
| min_repeat_ms=100, | ||
| enable_cpu_cache_flush=False, | ||
| ) | ||
|
|
||
| # Inspect the computational graph | ||
| print("Computational DAG:") | ||
| print(task.compute_dag) | ||
| tune_option = auto_scheduler.TuningOptions( | ||
| num_measure_trials=ARGS.num_trials, | ||
| measure_callbacks=[auto_scheduler.RecordToFile(log_file)], | ||
| verbose=2, | ||
| runner=runner, | ||
| ) | ||
| print("Running AutoTuning:") | ||
| task.tune(tune_option) | ||
| print("History Best:") | ||
| print(task.print_best(log_file)) | ||
| sch, args = task.apply_best(log_file) | ||
| print("Lowered TIR:") | ||
| print(tvm.lower(sch, args, simple_mode=True)) | ||
|
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| if __name__ == "__main__": | ||
| main() |
120 changes: 120 additions & 0 deletions
120
python/tvm/meta_schedule/testing/run_subgraph_meta_schedule.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,120 @@ | ||
| # 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 | ||
| import argparse | ||
| import logging | ||
| from os import cpu_count | ||
| from typing import Optional | ||
|
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| import tvm | ||
| from tvm import meta_schedule as ms | ||
| from tvm import tir | ||
| from tvm.meta_schedule.testing.te_workload import create_te_workload | ||
|
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|
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| def _parse_args(): | ||
| args = argparse.ArgumentParser() | ||
| args.add_argument( | ||
| "--workload", | ||
| type=str, | ||
| required=True, | ||
| ) | ||
| args.add_argument( | ||
| "--target", | ||
| type=str, | ||
| required=True, | ||
| ) | ||
| args.add_argument( | ||
| "--num-trials", | ||
| type=int, | ||
| required=True, | ||
| ) | ||
| args.add_argument( | ||
| "--work-dir", | ||
| type=str, | ||
| required=True, | ||
| ) | ||
| args.add_argument( | ||
| "--rpc-host", | ||
| type=str, | ||
| required=True, | ||
| ) | ||
| args.add_argument( | ||
| "--rpc-port", | ||
| type=int, | ||
| required=True, | ||
| ) | ||
| args.add_argument( | ||
| "--rpc-key", | ||
| type=str, | ||
| required=True, | ||
| ) | ||
| parsed = args.parse_args() | ||
| parsed.target = tvm.target.Target(parsed.target) | ||
| if parsed.target.attrs.get("mtriple", None) == "aarch64-linux-gnu": | ||
| parsed.alloc_repeat = 3 | ||
| else: | ||
| parsed.alloc_repeat = 1 | ||
| parsed.rpc_config = ms.runner.RPCConfig( | ||
| tracker_host=parsed.rpc_host, | ||
| tracker_port=parsed.rpc_port, | ||
| tracker_key=parsed.rpc_key, | ||
| session_timeout_sec=30, | ||
| ) | ||
| parsed.rpc_workers = parsed.rpc_config.count_num_servers(allow_missing=False) | ||
| return parsed | ||
|
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| logging.basicConfig() | ||
| logging.getLogger("tvm.meta_schedule").setLevel(logging.DEBUG) | ||
| ARGS = _parse_args() | ||
|
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| def main(): | ||
| runner = ms.runner.RPCRunner( | ||
| rpc_config=ARGS.rpc_config, | ||
| evaluator_config=ms.runner.EvaluatorConfig( | ||
| number=3, | ||
| repeat=1, | ||
| min_repeat_ms=100, | ||
| enable_cpu_cache_flush=False, | ||
| ), | ||
| alloc_repeat=ARGS.alloc_repeat, | ||
| max_workers=ARGS.rpc_workers, | ||
| ) | ||
| sch: Optional[tir.Schedule] = ms.tune_tir( | ||
| mod=create_te_workload(ARGS.workload, 0), | ||
| target=ARGS.target, | ||
| config=ms.EvolutionarySearchConfig( | ||
| num_trials_per_iter=64, | ||
| num_trials_total=ARGS.num_trials, | ||
| init_min_unmeasured=50, | ||
| ), | ||
| runner=runner, # type: ignore | ||
| task_name=ARGS.workload, | ||
| work_dir=ARGS.work_dir, | ||
| num_threads=cpu_count(), | ||
| ) | ||
| if sch is None: | ||
| print("No valid schedule found!") | ||
| else: | ||
| print(sch.mod.script()) | ||
| print(sch.trace) | ||
|
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|
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| if __name__ == "__main__": | ||
| main() |
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