code: def _fake_roi_head():
      """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, 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
  
file_path: mmdetection/tests/test_models/test_roi_heads/test_multi_instance_roi_head.py
imports: import unittest
  from unittest import TestCase
  import torch
  from mmengine.config import Config
  from mmdet.registry import MODELS
  from mmdet.testing import demo_mm_inputs, demo_mm_proposals
  from mmdet.utils import register_all_modules
label_desc: Use image node_id 1 for calling a global function with example usage: _fake_roi_head() and returns: roi_head