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[AutoTVM][Testing] Add
tune_relay
scripts
Example: ```bash python -m tvm.autotvm.testing.tune_relay \ --workload bert_base \ --input-shape '[1,64]' \ --target "llvm" \ --num-trials 800 \ --rpc-host 192.168.6.66 \ --rpc-port 4445 \ --rpc-key 3090ti \ --work-dir /logs/autotvm-bert_base \ --cache-dir /cache-workloads \ --graph-tuner True \ --cpu-flush True \ --backend graph ```
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# 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. | ||
"""Testing utilities for autotvm""" |
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# 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 json | ||
import os | ||
import warnings | ||
from distutils.util import strtobool | ||
|
||
import tvm | ||
from tvm import autotvm | ||
from tvm import meta_schedule as ms | ||
from tvm import relay | ||
from tvm.autotvm.graph_tuner import DPTuner | ||
from tvm.autotvm.tuner import XGBTuner | ||
from tvm.meta_schedule.testing.custom_builder_runner import run_module_via_rpc | ||
from tvm.meta_schedule.testing.relay_workload import get_network | ||
from tvm.meta_schedule.testing.tune_utils import create_timer, generate_input_data | ||
from tvm.support import describe | ||
|
||
|
||
def _parse_args(): | ||
args = argparse.ArgumentParser() | ||
args.add_argument( | ||
"--workload", | ||
type=str, | ||
required=True, | ||
help="The name of the workload to tune. Supported models: " | ||
"https://github.com/apache/tvm/blob/main/python/tvm/meta_schedule/testing/relay_workload.py#L303-L322", # pylint: disable=line-too-long | ||
) | ||
args.add_argument( | ||
"--input-shape", | ||
type=str, | ||
required=True, | ||
help="The input shape of the workload. Example: '[1, 3, 224, 224]'", | ||
) | ||
args.add_argument( | ||
"--target", | ||
type=str, | ||
required=True, | ||
help="The target device to tune. " | ||
"Example: 'aws/cpu/c5.9xlarge', 'nvidia/nvidia-v100', 'nvidia/geforce-rtx-3090'", | ||
) | ||
args.add_argument( | ||
"--num-trials", | ||
type=int, | ||
required=True, | ||
help="The number of trials per kernel. Example: 800", | ||
) | ||
args.add_argument( | ||
"--rpc-host", | ||
type=str, | ||
required=True, | ||
help="The host address of the RPC tracker. Example: 192.168.6.66", | ||
) | ||
args.add_argument( | ||
"--rpc-port", | ||
type=int, | ||
required=True, | ||
help="The port of the RPC tracker. Example: 4445", | ||
) | ||
args.add_argument( | ||
"--rpc-key", | ||
type=str, | ||
required=True, | ||
help="The key of the RPC tracker. Example: '3090ti'", | ||
) | ||
args.add_argument( | ||
"--work-dir", | ||
type=str, | ||
required=True, | ||
help="The working directory to store the tuning logs. Example: '/tmp/tune_relay'", | ||
) | ||
args.add_argument( | ||
"--layout", | ||
type=str, | ||
default=None, | ||
help="The layout of the workload. Example: 'NCHW', 'NHWC'", | ||
) | ||
args.add_argument( | ||
"--cache-dir", | ||
type=str, | ||
default=None, | ||
) | ||
args.add_argument( | ||
"--number", | ||
type=int, | ||
default=3, | ||
) | ||
args.add_argument( | ||
"--repeat", | ||
type=int, | ||
default=1, | ||
) | ||
args.add_argument( | ||
"--min-repeat-ms", | ||
type=int, | ||
default=100, | ||
) | ||
args.add_argument( | ||
"--cpu-flush", | ||
type=lambda x: bool(strtobool(x)), | ||
help="example: True / False", | ||
required=True, | ||
) | ||
args.add_argument( | ||
"--graph-tuner", | ||
type=lambda x: bool(strtobool(x)), | ||
help="example: True / False", | ||
required=True, | ||
) | ||
args.add_argument( | ||
"--backend", | ||
type=str, | ||
choices=["graph", "vm"], | ||
help="example: graph / vm", | ||
required=True, | ||
) | ||
parsed = args.parse_args() | ||
parsed.target = tvm.target.Target(parsed.target) | ||
parsed.input_shape = json.loads(parsed.input_shape) | ||
parsed.rpc_config = ms.runner.RPCConfig( | ||
tracker_host=parsed.rpc_host, | ||
tracker_port=parsed.rpc_port, | ||
tracker_key=parsed.rpc_key, | ||
session_timeout_sec=600, | ||
) | ||
if ARGS.target.kind.name != "llvm" and ARGS.graph_tuner: | ||
raise ValueError("GraphTuner only supports llvm target") | ||
if ARGS.target.kind.name != "llvm" and ARGS.cpu_flush: | ||
raise ValueError("cpu_flush only supports llvm target") | ||
if ARGS.target.kind.name == "llvm" and not ARGS.cpu_flush: | ||
warnings.warn("cpu_flush is not enabled for llvm target") | ||
return parsed | ||
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|
||
ARGS = _parse_args() | ||
|
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|
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def main(): | ||
log_file = os.path.join(ARGS.work_dir, f"{ARGS.workload}.json") | ||
graph_opt_sch_file = os.path.join(ARGS.work_dir, f"{ARGS.workload}_graph_opt.log") | ||
measure_option = autotvm.measure_option( | ||
builder=autotvm.LocalBuilder(), | ||
runner=autotvm.RPCRunner( | ||
key=ARGS.rpc_key, | ||
host=ARGS.rpc_host, | ||
port=ARGS.rpc_port, | ||
number=ARGS.number, | ||
repeat=ARGS.repeat, | ||
min_repeat_ms=ARGS.min_repeat_ms, | ||
enable_cpu_cache_flush=ARGS.cpu_flush, | ||
), | ||
) | ||
describe() | ||
print(f"Workload: {ARGS.workload}") | ||
mod, params, (input_name, input_shape, input_dtype) = get_network( | ||
ARGS.workload, | ||
ARGS.input_shape, | ||
layout=ARGS.layout, | ||
cache_dir=ARGS.cache_dir, | ||
) | ||
input_info = [ | ||
{ | ||
"name": input_name, | ||
"shape": input_shape, | ||
"dtype": input_dtype, | ||
}, | ||
] | ||
input_data = { | ||
item["name"]: generate_input_data(item["shape"], item["dtype"]) for item in input_info | ||
} | ||
for item in input_info: | ||
print(f" input_name : {item['name']}") | ||
print(f" input_shape: {item['shape']}") | ||
print(f" input_dtype: {item['dtype']}") | ||
|
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with ms.Profiler() as profiler: | ||
with ms.Profiler.timeit("TaskExtraction"): | ||
# extract workloads from relay program | ||
tasks = autotvm.task.extract_from_program( | ||
mod["main"], | ||
target=ARGS.target, | ||
params=params, | ||
ops=( | ||
relay.op.get("nn.conv2d"), | ||
relay.op.get("nn.conv3d"), | ||
relay.op.get("nn.conv2d_transpose"), | ||
relay.op.get("nn.dense"), | ||
relay.op.get("nn.batch_matmul"), | ||
), | ||
) | ||
for i, task in enumerate(tasks): | ||
print(f"Task {i} {task.name}: {task}") | ||
|
||
with ms.Profiler.timeit("Tuning"): | ||
if ARGS.num_trials > 0: | ||
for i, task in enumerate(tasks): | ||
prefix = "[Task %2d/%2d] " % (i + 1, len(tasks)) | ||
tuner_obj = XGBTuner(task, loss_type="rank") | ||
n_trial = min(len(task.config_space), ARGS.num_trials) | ||
tuner_obj.tune( | ||
n_trial=n_trial, | ||
early_stopping=800, | ||
measure_option=measure_option, | ||
callbacks=[ | ||
autotvm.callback.progress_bar(n_trial, prefix=prefix), | ||
autotvm.callback.log_to_file(log_file), | ||
], | ||
) | ||
if ARGS.graph_tuner: | ||
executor = DPTuner( | ||
graph=mod["main"], | ||
input_shapes={input_name: input_shape}, | ||
records=log_file, | ||
target_ops=[ | ||
relay.op.get("nn.conv2d"), | ||
], | ||
target=ARGS.target, | ||
) | ||
executor.benchmark_layout_transform(min_exec_num=1000) | ||
executor.run() | ||
executor.write_opt_sch2record_file(graph_opt_sch_file) | ||
|
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relay_build = {"graph": relay.build, "vm": relay.vm.compile}[ARGS.backend] | ||
with ms.Profiler.timeit("PostTuningCompilation"): | ||
if ARGS.graph_tuner: | ||
ctx = autotvm.apply_graph_best(graph_opt_sch_file) | ||
else: | ||
ctx = autotvm.apply_history_best(log_file) | ||
with ctx: | ||
print("compile...") | ||
with tvm.transform.PassContext(opt_level=3): | ||
lib = relay_build(mod, target=ARGS.target, params=params) | ||
print("Tuning Time:") | ||
print(profiler.table()) | ||
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run_module_via_rpc( | ||
rpc_config=ARGS.rpc_config, | ||
lib=lib, | ||
dev_type=ARGS.target.kind.name, | ||
args=input_data, | ||
continuation=create_timer(ARGS.backend), | ||
backend=ARGS.backend, | ||
) | ||
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if __name__ == "__main__": | ||
main() |