()
| 100 | def main(): |
| 101 | args = parse_args() |
| 102 | |
| 103 | cfg = Config.fromfile(args.config) |
| 104 | if args.cfg_options is not None: |
| 105 | cfg.merge_from_dict(args.cfg_options) |
| 106 | # import modules from string list. |
| 107 | if cfg.get('custom_imports', None): |
| 108 | from mmcv.utils import import_modules_from_strings |
| 109 | import_modules_from_strings(**cfg['custom_imports']) |
| 110 | |
| 111 | # import modules from plguin/xx, registry will be updated |
| 112 | if hasattr(cfg, 'plugin'): |
| 113 | if cfg.plugin: |
| 114 | import importlib |
| 115 | if hasattr(cfg, 'plugin_dir'): |
| 116 | plugin_dir = cfg.plugin_dir |
| 117 | _module_dir = os.path.dirname(plugin_dir) |
| 118 | _module_dir = _module_dir.split('/') |
| 119 | _module_path = _module_dir[0] |
| 120 | |
| 121 | for m in _module_dir[1:]: |
| 122 | _module_path = _module_path + '.' + m |
| 123 | print(_module_path) |
| 124 | plg_lib = importlib.import_module(_module_path) |
| 125 | else: |
| 126 | # import dir is the dirpath for the config file |
| 127 | _module_dir = os.path.dirname(args.config) |
| 128 | _module_dir = _module_dir.split('/') |
| 129 | _module_path = _module_dir[0] |
| 130 | for m in _module_dir[1:]: |
| 131 | _module_path = _module_path + '.' + m |
| 132 | print(_module_path) |
| 133 | plg_lib = importlib.import_module(_module_path) |
| 134 | |
| 135 | from projects.mmdet3d_plugin.bevformer.apis.train import custom_train_model |
| 136 | # set cudnn_benchmark |
| 137 | if cfg.get('cudnn_benchmark', False): |
| 138 | torch.backends.cudnn.benchmark = True |
| 139 | |
| 140 | # work_dir is determined in this priority: CLI > segment in file > filename |
| 141 | if args.work_dir is not None: |
| 142 | # update configs according to CLI args if args.work_dir is not None |
| 143 | cfg.work_dir = args.work_dir |
| 144 | elif cfg.get('work_dir', None) is None: |
| 145 | # use config filename as default work_dir if cfg.work_dir is None |
| 146 | cfg.work_dir = osp.join('./work_dirs', |
| 147 | osp.splitext(osp.basename(args.config))[0]) |
| 148 | # if args.resume_from is not None: |
| 149 | if args.resume_from is not None and osp.isfile(args.resume_from): |
| 150 | cfg.resume_from = args.resume_from |
| 151 | if args.gpu_ids is not None: |
| 152 | cfg.gpu_ids = args.gpu_ids |
| 153 | else: |
| 154 | cfg.gpu_ids = range(1) if args.gpus is None else range(args.gpus) |
| 155 | if digit_version(TORCH_VERSION) == digit_version('1.8.1') and cfg.optimizer['type'] == 'AdamW': |
| 156 | cfg.optimizer['type'] = 'AdamW2' # fix bug in Adamw |
| 157 | if args.autoscale_lr: |
| 158 | # apply the linear scaling rule (https://arxiv.org/abs/1706.02677) |
| 159 | cfg.optimizer['lr'] = cfg.optimizer['lr'] * len(cfg.gpu_ids) / 8 |
no test coverage detected