Skip to content

Commit

Permalink
[tvmc] Introduce 'tune' subcommand (part 3/4) (apache#6537)
Browse files Browse the repository at this point in the history
* 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>
  • Loading branch information
4 people authored and Tushar Dey committed Oct 15, 2020
1 parent ee4a567 commit cb99e1f
Show file tree
Hide file tree
Showing 4 changed files with 517 additions and 0 deletions.
1 change: 1 addition & 0 deletions python/tvm/driver/tvmc/__init__.py
Original file line number Diff line number Diff line change
Expand Up @@ -18,4 +18,5 @@
TVMC - TVM driver command-line interface
"""

from . import autotuner
from . import compiler
327 changes: 327 additions & 0 deletions python/tvm/driver/tvmc/autotuner.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,327 @@
# 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

from urllib.parse import urlparse

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

from . import common, frontends
from .common import TVMCException
from .main import register_parser


# pylint: disable=invalid-name
logger = logging.getLogger("TVMC")


@register_parser
def add_tune_parser(subparsers):
""" Include parser for 'tune' subcommand """

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",
)

# 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")


def drive_tune(args):
"""Invoke auto-tuning with command line arguments
Parameters
----------
args: argparse.Namespace
Arguments from command line parser.
"""

# 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)

if not args.rpc_key:
raise common.TVMCException(
"need to provide an RPC tracker key (--rpc-key) for remote tuning"
)

target = common.target_from_cli(args.target)
mod, params = frontends.load_model(args.FILE, args.model_format)

# 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)

tasks = get_tuning_tasks(
mod=mod,
params=params,
target=target,
target_host=args.target_host,
alter_layout=args.desired_layout,
)

if args.rpc_tracker:

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,
)

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)

tune_tasks(tasks, args.output, **tuning_option)


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)

tasks = autotvm.task.extract_from_program(
mod["main"],
target=target,
target_host=target_host,
params=params,
)

return tasks


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

if not early_stopping:
early_stopping = trials

for i, tsk in enumerate(tasks):
prefix = "[Task %2d/%2d] " % (i + 1, len(tasks))

# 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)

# 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)

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),
],
)
39 changes: 39 additions & 0 deletions python/tvm/driver/tvmc/common.py
Original file line number Diff line number Diff line change
Expand Up @@ -17,10 +17,19 @@
"""
Common utility functions shared by TVMC modules.
"""
import logging
import os.path

import tvm

from tvm import relay
from tvm import transform


# pylint: disable=invalid-name
logger = logging.getLogger("TVMC")


class TVMCException(Exception):
"""TVMC Exception"""

Expand Down Expand Up @@ -63,3 +72,33 @@ def convert_graph_layout(mod, desired_layout):
raise TVMCException(
"Error converting layout to {0}: {1}".format(desired_layout, str(err))
)


# TODO In a separate PR, eliminate the duplicated code here and in compiler.py (@leandron)
def target_from_cli(target):
"""
Create a tvm.target.Target instance from a
command line interface (CLI) string.
Parameters
----------
target : str
compilation target as plain string,
inline JSON or path to a JSON file
Returns
-------
tvm.target.Target
an instance of target device information
"""

if os.path.exists(target):
with open(target) as target_file:
logger.info("using target input from file: %s", target)
target = "".join(target_file.readlines())

# TODO(@leandron) We don't have an API to collect a list of supported
# targets yet
logger.debug("creating target from input: %s", target)

return tvm.target.Target(target)
Loading

0 comments on commit cb99e1f

Please sign in to comment.