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[tvmc] Introduce 'tune' subcommand (part 3/4) (apache#6537)
* tvmc: introduce 'tune' subcommand (part 3/4) * introduces a subcommand to drive auto-tuning Co-authored-by: Matthew Barrett <matthew.barrett@arm.com> Co-authored-by: Luke Hutton <luke.hutton@arm.com> Co-authored-by: Giuseppe Rossini <giuseppe.rossini@arm.com> * [tvmc] address code review comments * adjust --min-repeat-ms default value logic * re-arrange rpc arguments to be --rpc-tracker=hostname:port and --rpc-key=str * use a local reference of the tvmc logger * add --target-host, default to llvm Co-authored-by: Matthew Barrett <matthew.barrett@arm.com> Co-authored-by: Luke Hutton <luke.hutton@arm.com> Co-authored-by: Giuseppe Rossini <giuseppe.rossini@arm.com>
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TVMC - TVM driver command-line interface | ||
""" | ||
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from . import autotuner | ||
from . import compiler |
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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. | ||
""" | ||
Provides support to auto-tuning networks using AutoTVM. | ||
""" | ||
import os.path | ||
import logging | ||
import time | ||
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from urllib.parse import urlparse | ||
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from tvm import autotvm | ||
from tvm.autotvm.tuner import GATuner | ||
from tvm.autotvm.tuner import GridSearchTuner | ||
from tvm.autotvm.tuner import RandomTuner | ||
from tvm.autotvm.tuner import XGBTuner | ||
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from . import common, frontends | ||
from .common import TVMCException | ||
from .main import register_parser | ||
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# pylint: disable=invalid-name | ||
logger = logging.getLogger("TVMC") | ||
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@register_parser | ||
def add_tune_parser(subparsers): | ||
""" Include parser for 'tune' subcommand """ | ||
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parser = subparsers.add_parser("tune", help="auto-tune a model") | ||
parser.set_defaults(func=drive_tune) | ||
parser.add_argument( | ||
"--early-stopping", | ||
type=int, | ||
help="minimum number of trials before early stopping", | ||
) | ||
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# There is some extra processing required to define the actual default value | ||
# for --min-repeat-ms. This is done in `drive_tune`. | ||
parser.add_argument( | ||
"--min-repeat-ms", | ||
default=None, | ||
type=int, | ||
help="minimum time to run each trial, in milliseconds. " | ||
"Defaults to 0 on x86 and 1000 on all other targets", | ||
) | ||
parser.add_argument( | ||
"--model-format", | ||
choices=frontends.get_frontend_names(), | ||
help="specify input model format", | ||
) | ||
parser.add_argument( | ||
"--number", | ||
default=10, | ||
type=int, | ||
help="number of runs a single repeat is made of. " | ||
"The final number of tuning executions is: " | ||
"(1 + number * repeat)", | ||
) | ||
parser.add_argument( | ||
"-o", | ||
"--output", | ||
required=True, | ||
help="output file to store the tuning records for the tuning process", | ||
) | ||
parser.add_argument( | ||
"--parallel", | ||
default=4, | ||
type=int, | ||
help="the maximum number of parallel devices to use when tuning", | ||
) | ||
parser.add_argument( | ||
"--repeat", | ||
type=int, | ||
default=1, | ||
help="how many times to repeat each measurement", | ||
) | ||
parser.add_argument( | ||
"--rpc-key", | ||
nargs=1, | ||
help="the RPC tracker key of the target device. Required when --rpc-tracker is provided.", | ||
) | ||
parser.add_argument( | ||
"--rpc-tracker", | ||
nargs=1, | ||
help="hostname (required) and port (optional, defaults to 9090) of the RPC tracker, " | ||
"e.g. '192.168.0.100:9999'", | ||
) | ||
parser.add_argument( | ||
"--target", | ||
help="compilation target as plain string, inline JSON or path to a JSON file", | ||
required=True, | ||
) | ||
parser.add_argument( | ||
"--target-host", | ||
help="the host compilation target, defaults to 'llvm'", | ||
default="llvm", | ||
) | ||
parser.add_argument("--timeout", default=10, help="compilation timeout, in seconds") | ||
parser.add_argument( | ||
"--trials", | ||
type=int, | ||
default=1000, | ||
help="the maximum number of tuning trials to perform", | ||
) | ||
parser.add_argument( | ||
"--tuner", | ||
choices=["ga", "gridsearch", "random", "xgb", "xgb_knob", "xgb-rank"], | ||
default="xgb", | ||
help="type of tuner to use", | ||
) | ||
parser.add_argument( | ||
"--tuning-records", | ||
metavar="PATH", | ||
help="path to an auto-tuning log file by AutoTVM.", | ||
) | ||
parser.add_argument( | ||
"--desired-layout", | ||
choices=["NCHW", "NHWC"], | ||
default=None, | ||
help="change the data layout of the whole graph", | ||
) | ||
# TODO (@leandron) This is a path to a physical file, but | ||
# can be improved in future to add integration with a modelzoo | ||
# or URL, for example. | ||
parser.add_argument("FILE", help="path to the input model file") | ||
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def drive_tune(args): | ||
"""Invoke auto-tuning with command line arguments | ||
Parameters | ||
---------- | ||
args: argparse.Namespace | ||
Arguments from command line parser. | ||
""" | ||
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# extra arguments validation before importing the model, so that obvious errors | ||
# are pointed in advance. | ||
if args.rpc_tracker: | ||
parsed_url = urlparse("//%s" % args.rpc_tracker) | ||
rpc_hostname = parsed_url.hostname | ||
rpc_port = parsed_url.port or 9090 | ||
logger.info("RPC tracker hostname: %s", rpc_hostname) | ||
logger.info("RPC tracker port: %s", rpc_port) | ||
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if not args.rpc_key: | ||
raise common.TVMCException( | ||
"need to provide an RPC tracker key (--rpc-key) for remote tuning" | ||
) | ||
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target = common.target_from_cli(args.target) | ||
mod, params = frontends.load_model(args.FILE, args.model_format) | ||
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# min_repeat_ms should be: | ||
# a. the value provided by the user, if any, or | ||
# b. 0ms in case target is "cpu"; otherwise 1000ms | ||
if args.min_repeat_ms is not None: | ||
min_repeat_ms = args.min_repeat_ms | ||
else: | ||
min_repeat_ms = 0 if target.keys[0] == "cpu" else 1000 | ||
logger.debug("Default --min-repeat-ms for this target is %s", min_repeat_ms) | ||
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tasks = get_tuning_tasks( | ||
mod=mod, | ||
params=params, | ||
target=target, | ||
target_host=args.target_host, | ||
alter_layout=args.desired_layout, | ||
) | ||
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if args.rpc_tracker: | ||
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runner = autotvm.RPCRunner( | ||
key=args.rpc_key, | ||
host=rpc_hostname, | ||
port=rpc_port, | ||
number=args.number, | ||
repeat=args.repeat, | ||
n_parallel=args.parallel, | ||
timeout=args.timeout, | ||
min_repeat_ms=min_repeat_ms, | ||
) | ||
else: | ||
logger.info("starting localhost tuning") | ||
runner = autotvm.LocalRunner( | ||
number=args.number, | ||
repeat=args.repeat, | ||
timeout=args.timeout, | ||
min_repeat_ms=min_repeat_ms, | ||
) | ||
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tuning_option = { | ||
"tuner": args.tuner, | ||
"trials": args.trials, | ||
"early_stopping": args.early_stopping, | ||
"measure_option": autotvm.measure_option( | ||
builder=autotvm.LocalBuilder(build_func="default"), runner=runner | ||
), | ||
"tuning_records": args.tuning_records, | ||
} | ||
logger.debug(" tuning options: %s", tuning_option) | ||
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tune_tasks(tasks, args.output, **tuning_option) | ||
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def get_tuning_tasks(mod, params, target, target_host=None, alter_layout=None): | ||
"""Get the tuning tasks for a given relay module. | ||
Parameters | ||
---------- | ||
mod : tvm.relay.Module | ||
The relay module from which to extract tuning tasks. | ||
params : dict | ||
The params for the relay module. | ||
target : tvm.target.Target | ||
The compilation target. | ||
target_host : str, optional | ||
The compilation target for the host. | ||
alter_layout : str, optional | ||
The layout to convert the graph to. Note, the convert layout | ||
pass doesn't currently guarantee the whole of the graph will | ||
be converted to the chosen layout. | ||
Returns | ||
------- | ||
tasks : list of autotvm.Tasks | ||
list of tasks to be tuned | ||
""" | ||
if alter_layout: | ||
mod = common.convert_graph_layout(mod, alter_layout) | ||
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tasks = autotvm.task.extract_from_program( | ||
mod["main"], | ||
target=target, | ||
target_host=target_host, | ||
params=params, | ||
) | ||
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return tasks | ||
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def tune_tasks( | ||
tasks, | ||
log_file, | ||
measure_option, | ||
tuner, | ||
trials, | ||
early_stopping=None, | ||
tuning_records=None, | ||
): | ||
"""Tune a list of tasks and output the history to a log file. | ||
Parameters | ||
---------- | ||
tasks : list | ||
A list of autotvm.Tasks to tune. | ||
log_file : str | ||
A file to output the tuning history, in JSON. | ||
measure_option : autotvm.measure_option | ||
Options to build and run a tuning task. | ||
tuner : str | ||
Which tuner to use. | ||
trials : int | ||
The maximum number of tuning trials to perform. | ||
early_stopping : int, optional | ||
The minimum number of tuning trials to perform. | ||
This will be equal to 'trials' if not specified. | ||
tuning_records: str, optional | ||
Path to the file produced by the tuning, to be used during | ||
tuning. | ||
""" | ||
if not tasks: | ||
logger.warning("there were no tasks found to be tuned") | ||
return | ||
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if not early_stopping: | ||
early_stopping = trials | ||
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for i, tsk in enumerate(tasks): | ||
prefix = "[Task %2d/%2d] " % (i + 1, len(tasks)) | ||
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# Create a tuner | ||
if tuner in ("xgb", "xgb-rank"): | ||
tuner_obj = XGBTuner(tsk, loss_type="rank") | ||
elif tuner == "xgb_knob": | ||
tuner_obj = XGBTuner(tsk, loss_type="rank", feature_type="knob") | ||
elif tuner == "ga": | ||
tuner_obj = GATuner(tsk, pop_size=50) | ||
elif tuner == "random": | ||
tuner_obj = RandomTuner(tsk) | ||
elif tuner == "gridsearch": | ||
tuner_obj = GridSearchTuner(tsk) | ||
else: | ||
raise TVMCException("invalid tuner: %s " % tuner) | ||
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# If transfer learning is being used, load the existing results | ||
if tuning_records and os.path.exists(tuning_records): | ||
logger.info("loading tuning records from %s", tuning_records) | ||
start_time = time.time() | ||
tuner_obj.load_history(autotvm.record.load_from_file(tuning_records)) | ||
logging.info("loaded history in %.2f sec(s)", time.time() - start_time) | ||
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tuner_obj.tune( | ||
n_trial=min(trials, len(tsk.config_space)), | ||
early_stopping=early_stopping, | ||
measure_option=measure_option, | ||
callbacks=[ | ||
autotvm.callback.progress_bar(trials, prefix=prefix), | ||
autotvm.callback.log_to_file(log_file), | ||
], | ||
) |
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