def METHOD_NAME():
    """Set a fake roi head config."""
    roi_head = Config(
        dict(
            type='MultiInstanceRoIHead',
            bbox_roi_extractor=dict(
                type='SingleRoIExtractor',
                roi_layer=dict(
                    type='RoIAlign',
                    output_size=7,
                    sampling_ratio=-1,
                    aligned=True,
                    use_torchvision=True),
                out_channels=256,
                featmap_strides=[4, 8, 16, 32]),
            bbox_head=dict(
                type='MultiInstanceBBoxHead',
                with_refine=False,
                num_shared_fcs=2,
                in_channels=256,
                fc_out_channels=1024,
                roi_feat_size=7,
                num_classes=1,
                bbox_coder=dict(
                    type='DeltaXYWHBBoxCoder',
                    target_means=[0., 0., 0., 0.],
                    target_stds=[0.1, 0.1, 0.2, 0.2]),
                reg_class_agnostic=False,
                loss_cls=dict(
                    type='CrossEntropyLoss',
                    loss_weight=1.0,
                    use_sigmoid=False,
                    reduction='none'),
                loss_bbox=dict(
                    type='SmoothL1Loss', loss_weight=1.0, reduction='none')),
            train_cfg=dict(
                assigner=dict(
                    type='MultiInstanceAssigner',
                    pos_iou_thr=0.5,
                    neg_iou_thr=0.5,
                    min_pos_iou=0.3,
                    match_low_quality=False,
                    ignore_iof_thr=-1),
                sampler=dict(
                    type='MultiInsRandomSampler',
                    num=512,
                    pos_fraction=0.5,
                    neg_pos_ub=-1,
                    add_gt_as_proposals=False),
                pos_weight=-1,
                debug=False),
            test_cfg=dict(
                nms=dict(iou_threshold=0.5), score_thr=0.01, max_per_img=500)))
    return roi_head