# Copyright (c) 2020 PaddlePaddle Authors. 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 __future__ import absolute_import from __future__ import division from __future__ import print_function import os import sys # add python path of PadleDetection to sys.path parent_path = os.path.abspath(os.path.join(__file__, *(['..'] * 2))) sys.path.insert(0, parent_path) # ignore warning log import warnings warnings.filterwarnings('ignore') import paddle from ppdet.core.workspace import load_config, merge_config from ppdet.engine import Trainer, init_parallel_env, set_random_seed, init_fleet_env from ppdet.slim import build_slim_model import ppdet.utils.cli as cli import ppdet.utils.check as check from ppdet.utils.logger import setup_logger logger = setup_logger('train') def parse_args(): parser = cli.ArgsParser() parser.add_argument( "--eval", action='store_true', default=False, help="Whether to perform evaluation in train") parser.add_argument( "-r", "--resume", default=None, help="weights path for resume") parser.add_argument( "--slim_config", default=None, type=str, help="Configuration file of slim method.") parser.add_argument( "--enable_ce", type=bool, default=False, help="If set True, enable continuous evaluation job." "This flag is only used for internal test.") parser.add_argument( "--fp16", action='store_true', default=False, help="Enable mixed precision training.") parser.add_argument( "--fleet", action='store_true', default=False, help="Use fleet or not") parser.add_argument( "--use_vdl", type=bool, default=False, help="whether to record the data to VisualDL.") parser.add_argument( '--vdl_log_dir', type=str, default="vdl_log_dir/scalar", help='VisualDL logging directory for scalar.') parser.add_argument( '--save_prediction_only', action='store_true', default=False, help='Whether to save the evaluation results only') parser.add_argument( '--profiler_options', type=str, default=None, help="The option of profiler, which should be in " "format \"key1=value1;key2=value2;key3=value3\"." "please see ppdet/utils/profiler.py for detail.") parser.add_argument( '--save_proposals', action='store_true', default=False, help='Whether to save the train proposals') parser.add_argument( '--proposals_path', type=str, default="sniper/proposals.json", help='Train proposals directory') args = parser.parse_args() return args def run(FLAGS, cfg): # init fleet environment if cfg.fleet: init_fleet_env(cfg.get('find_unused_parameters', False)) else: # init parallel environment if nranks > 1 init_parallel_env() if FLAGS.enable_ce: set_random_seed(0) # build trainer trainer = Trainer(cfg, mode='train') # load weights if FLAGS.resume is not None: trainer.resume_weights(FLAGS.resume) elif 'pretrain_weights' in cfg and cfg.pretrain_weights: trainer.load_weights(cfg.pretrain_weights) # training trainer.train(FLAGS.eval) def main(): FLAGS = parse_args() cfg = load_config(FLAGS.config) cfg['fp16'] = FLAGS.fp16 cfg['fleet'] = FLAGS.fleet cfg['use_vdl'] = FLAGS.use_vdl cfg['vdl_log_dir'] = FLAGS.vdl_log_dir cfg['save_prediction_only'] = FLAGS.save_prediction_only cfg['profiler_options'] = FLAGS.profiler_options cfg['save_proposals'] = FLAGS.save_proposals cfg['proposals_path'] = FLAGS.proposals_path merge_config(FLAGS.opt) # disable npu in config by default if 'use_npu' not in cfg: cfg.use_npu = False if cfg.use_gpu: place = paddle.set_device('gpu') elif cfg.use_npu: place = paddle.set_device('npu') else: place = paddle.set_device('cpu') if 'norm_type' in cfg and cfg['norm_type'] == 'sync_bn' and not cfg.use_gpu: cfg['norm_type'] = 'bn' if FLAGS.slim_config: cfg = build_slim_model(cfg, FLAGS.slim_config) # FIXME: Temporarily solve the priority problem of FLAGS.opt merge_config(FLAGS.opt) check.check_config(cfg) check.check_gpu(cfg.use_gpu) check.check_npu(cfg.use_npu) check.check_version() run(FLAGS, cfg) if __name__ == "__main__": main()