def __init__()

in easycv/models/detection3d/detectors/mvx_two_stage.py [0:0]

• 80 lines of code
• 22 McCabe index (conditional complexity)

    def __init__(self,
                 pts_voxel_layer=None,
                 pts_voxel_encoder=None,
                 pts_middle_encoder=None,
                 pts_fusion_layer=None,
                 img_backbone=None,
                 pts_backbone=None,
                 img_neck=None,
                 pts_neck=None,
                 pts_bbox_head=None,
                 img_roi_head=None,
                 img_rpn_head=None,
                 train_cfg=None,
                 test_cfg=None,
                 pretrained=None,
                 init_cfg=None):
        super(MVXTwoStageDetector, self).__init__(init_cfg=init_cfg)

        if pts_voxel_layer:
            self.pts_voxel_layer = Voxelization(**pts_voxel_layer)
        if pts_voxel_encoder:
            self.pts_voxel_encoder = builder.build_voxel_encoder(
                pts_voxel_encoder)
        if pts_middle_encoder:
            self.pts_middle_encoder = builder.build_middle_encoder(
                pts_middle_encoder)
        if pts_backbone:
            self.pts_backbone = builder.build_backbone(pts_backbone)
        if pts_fusion_layer:
            self.pts_fusion_layer = builder.build_fusion_layer(
                pts_fusion_layer)
        if pts_neck is not None:
            self.pts_neck = builder.build_neck(pts_neck)
        if pts_bbox_head:
            pts_train_cfg = train_cfg.pts if train_cfg else None
            pts_bbox_head.update(train_cfg=pts_train_cfg)
            pts_test_cfg = test_cfg.pts if test_cfg else None
            pts_bbox_head.update(test_cfg=pts_test_cfg)
            self.pts_bbox_head = builder.build_head(pts_bbox_head)

        if img_backbone:
            self.img_backbone = builder.build_backbone(img_backbone)
        if img_neck is not None:
            self.img_neck = builder.build_neck(img_neck)
        if img_rpn_head is not None:
            self.img_rpn_head = builder.build_head(img_rpn_head)
        if img_roi_head is not None:
            self.img_roi_head = builder.build_head(img_roi_head)

        self.train_cfg = train_cfg
        self.test_cfg = test_cfg

        if pretrained is None:
            img_pretrained = None
            pts_pretrained = None
        elif isinstance(pretrained, dict):
            img_pretrained = pretrained.get('img', None)
            pts_pretrained = pretrained.get('pts', None)
        else:
            raise ValueError(
                f'pretrained should be a dict, got {type(pretrained)}')

        self.init_weights()

        logger = get_root_logger()
        if self.with_img_backbone:
            if img_pretrained is not None:
                load_checkpoint(
                    self.img_backbone,
                    img_pretrained,
                    strict=False,
                    logger=logger)
        if self.with_img_roi_head:
            if img_pretrained is not None:
                load_checkpoint(
                    self.img_roi_head,
                    img_pretrained,
                    strict=False,
                    logger=logger)
        if self.with_pts_backbone:
            if pts_pretrained is not None:
                load_checkpoint(
                    self.pts_backbone,
                    pts_pretrained,
                    strict=False,
                    logger=logger)