# Copyright (c) OpenMMLab. All rights reserved. import torch from mmdet.models.detectors.single_stage import SingleStageDetector from mmdet.utils import ConfigType, OptConfigType, OptMultiConfig from mmengine.dist import get_world_size from mmengine.logging import print_log from mmyolo.registry import MODELS @MODELS.register_module() class YOLODetector(SingleStageDetector): r"""Implementation of YOLO Series Args: backbone (:obj:`ConfigDict` or dict): The backbone config. neck (:obj:`ConfigDict` or dict): The neck config. bbox_head (:obj:`ConfigDict` or dict): The bbox head config. train_cfg (:obj:`ConfigDict` or dict, optional): The training config of YOLO. Defaults to None. test_cfg (:obj:`ConfigDict` or dict, optional): The testing config of YOLO. Defaults to None. data_preprocessor (:obj:`ConfigDict` or dict, optional): Config of :class:`DetDataPreprocessor` to process the input data. Defaults to None. init_cfg (:obj:`ConfigDict` or list[:obj:`ConfigDict`] or dict or list[dict], optional): Initialization config dict. Defaults to None. use_syncbn (bool): whether to use SyncBatchNorm. Defaults to True. """ def __init__(self, backbone: ConfigType, neck: ConfigType, bbox_head: ConfigType, train_cfg: OptConfigType = None, test_cfg: OptConfigType = None, data_preprocessor: OptConfigType = None, init_cfg: OptMultiConfig = None, use_syncbn: bool = True): super().__init__( backbone=backbone, neck=neck, bbox_head=bbox_head, train_cfg=train_cfg, test_cfg=test_cfg, data_preprocessor=data_preprocessor, init_cfg=init_cfg) # TODOļ¼š Waiting for mmengine support if use_syncbn and get_world_size() > 1: torch.nn.SyncBatchNorm.convert_sync_batchnorm(self) print_log('Using SyncBatchNorm()', 'current')