run_param_tuner.py

# =========================================================================
# Copyright (C) 2022. Huawei Technologies Co., Ltd. All rights reserved.
# 
# Licensed 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.
# =========================================================================
from datetime import datetime
import gc
import argparse
import fuxictr_version
from utils import autotuner
import warnings

warnings.filterwarnings("ignore")

if __name__ == '__main__':
    parser = argparse.ArgumentParser()
    parser.add_argument('--config', type=str, default=f'./config/DIVAN_ebnerd_large_x1_tuner_config_01.yaml',
                        help='The config file for para tuning.')
    parser.add_argument('--tag', type=str, default=None,
                        help='Use the tag to determine which expid to run (e.g. 001 for the first expid).')
    parser.add_argument('--gpu', nargs='+', default=[0], help='The list of gpu indexes, -1 for cpu.')
    parser.add_argument('--algorithm', type=str, default='grid', choices=['grid', 'tpe'],
                        help='The hyperparameter search algorithm to use (grid or tpe).')
    parser.add_argument('--max_evals', type=int, default=20, help='The maximum number of evaluations for TPE.')
    parser.add_argument('--script', type=str, default='run_expid_v3.py', help='The script file to run the expid.')
    args = vars(parser.parse_args())

    gpu_list = args['gpu']
    expid_tag = args['tag']
    algorithm = args['algorithm']
    max_evals = args['max_evals']
    script = args['script']

    # generate parameter space combinations
    config_dir = autotuner.enumerate_params(args['config'])

    if algorithm == 'grid':
        autotuner.grid_search(config_dir, gpu_list, expid_tag, script=script)
    elif algorithm == 'tpe':
        best = autotuner.tpe_search(config_dir, gpu_list, script=script, max_evals=max_evals)