How to use the mmdet.models.builder.build_head function in mmdet

mask_head=None,
                 train_cfg=None,
                 test_cfg=None,
                 pretrained=None):
        super(TwoStageDetector, self).__init__()
        # ipdb.set_trace(context=35)
        self.backbone = builder.build_backbone(backbone)
        if neck is not None:
            self.neck = builder.build_neck(neck)

        if shared_head is not None:
            self.shared_head = builder.build_shared_head(shared_head)

        if rpn_head is not None:
            # RPN搭建后，有几张尺寸的特征图，执行几次其forward
            self.rpn_head = builder.build_head(rpn_head)

        if bbox_head is not None:
            self.bbox_roi_extractor = builder.build_roi_extractor(
                bbox_roi_extractor)
            self.bbox_head = builder.build_head(bbox_head)

        if mask_head is not None:
            if mask_roi_extractor is not None:
                self.mask_roi_extractor = builder.build_roi_extractor(
                    mask_roi_extractor)
                self.share_roi_extractor = False
            else:
                self.share_roi_extractor = True
                self.mask_roi_extractor = self.bbox_roi_extractor
            self.mask_head = builder.build_head(mask_head)

def __init__(self,
                 num_stages,
                 backbone,
                 semantic_roi_extractor=None,
                 semantic_head=None,
                 semantic_fusion=('bbox', 'mask'),
                 interleaved=True,
                 mask_info_flow=True,
                 **kwargs):
        super(HybridTaskCascade, self).__init__(num_stages, backbone, **kwargs)
        assert self.with_bbox and self.with_mask
        assert not self.with_shared_head  # shared head not supported
        if semantic_head is not None:
            self.semantic_roi_extractor = builder.build_roi_extractor(
                semantic_roi_extractor)
            self.semantic_head = builder.build_head(semantic_head)

        self.semantic_fusion = semantic_fusion
        self.interleaved = interleaved
        self.mask_info_flow = mask_info_flow

# ipdb.set_trace(context=35)
        self.backbone = builder.build_backbone(backbone)
        if neck is not None:
            self.neck = builder.build_neck(neck)

        if shared_head is not None:
            self.shared_head = builder.build_shared_head(shared_head)

        if rpn_head is not None:
            # RPN搭建后，有几张尺寸的特征图，执行几次其forward
            self.rpn_head = builder.build_head(rpn_head)

        if bbox_head is not None:
            self.bbox_roi_extractor = builder.build_roi_extractor(
                bbox_roi_extractor)
            self.bbox_head = builder.build_head(bbox_head)

        if mask_head is not None:
            if mask_roi_extractor is not None:
                self.mask_roi_extractor = builder.build_roi_extractor(
                    mask_roi_extractor)
                self.share_roi_extractor = False
            else:
                self.share_roi_extractor = True
                self.mask_roi_extractor = self.bbox_roi_extractor
            self.mask_head = builder.build_head(mask_head)

        self.train_cfg = train_cfg
        self.test_cfg = test_cfg

        # 在此处初始化模型。实际是逐模块调用，层层初始化
        self.init_weights(pretrained=pretrained)

def __init__(self,
                 backbone,
                 neck=None,
                 bbox_head=None,
                 train_cfg=None,
                 test_cfg=None,
                 pretrained=None):
        super(SingleStageDetector, self).__init__()
        self.backbone = builder.build_backbone(backbone)
        if neck is not None:
            self.neck = builder.build_neck(neck)
        self.bbox_head = builder.build_head(bbox_head)
        self.train_cfg = train_cfg
        self.test_cfg = test_cfg
        self.init_weights(pretrained=pretrained)

def __init__(self,
                 backbone,
                 neck=None,
                 bbox_head=None,
                 train_cfg=None,
                 test_cfg=None,
                 pretrained=None):
        super(SingleStageDetector, self).__init__()
        self.backbone = builder.build_backbone(backbone)
        if neck is not None:
            self.neck = builder.build_neck(neck)
        self.bbox_head = builder.build_head(bbox_head)
        self.train_cfg = train_cfg
        self.test_cfg = test_cfg
        self.init_weights(pretrained=pretrained)

mask_roi_extractor=None,
                 mask_head=None,
                 train_cfg=None,
                 test_cfg=None,
                 pretrained=None):
        super(TwoStageDetector, self).__init__()
        self.backbone = builder.build_backbone(backbone)

        if neck is not None:
            self.neck = builder.build_neck(neck)

        if shared_head is not None:
            self.shared_head = builder.build_shared_head(shared_head)

        if rpn_head is not None:
            self.rpn_head = builder.build_head(rpn_head)

        if bbox_head is not None:
            self.bbox_roi_extractor = builder.build_roi_extractor(
                bbox_roi_extractor)
            self.bbox_head = builder.build_head(bbox_head)

        if mask_head is not None:
            if mask_roi_extractor is not None:
                self.mask_roi_extractor = builder.build_roi_extractor(
                    mask_roi_extractor)
                self.share_roi_extractor = False
            else:
                self.share_roi_extractor = True
                self.mask_roi_extractor = self.bbox_roi_extractor
            self.mask_head = builder.build_head(mask_head)

self.rpn_head = builder.build_head(rpn_head)

        if bbox_head is not None:
            self.bbox_roi_extractor = builder.build_roi_extractor(
                bbox_roi_extractor)
            self.bbox_head = builder.build_head(bbox_head)

        if mask_head is not None:
            if mask_roi_extractor is not None:
                self.mask_roi_extractor = builder.build_roi_extractor(
                    mask_roi_extractor)
                self.share_roi_extractor = False
            else:
                self.share_roi_extractor = True
                self.mask_roi_extractor = self.bbox_roi_extractor
            self.mask_head = builder.build_head(mask_head)

        self.train_cfg = train_cfg
        self.test_cfg = test_cfg

        self.init_weights(pretrained=pretrained)

def __init__(self,
                 backbone,
                 neck,
                 rpn_head,
                 train_cfg,
                 test_cfg,
                 pretrained=None):
        super(RPN, self).__init__()
        self.backbone = builder.build_backbone(backbone)
        self.neck = builder.build_neck(neck) if neck is not None else None
        self.rpn_head = builder.build_head(rpn_head)
        self.train_cfg = train_cfg
        self.test_cfg = test_cfg
        self.init_weights(pretrained=pretrained)