code: def _fake_roi_head(with_shared_head=False):
      """Set a fake roi head config."""
      if not with_shared_head:
          roi_head = Config(
              dict(
                  type="StandardRoIHead",
                  bbox_roi_extractor=dict(
                      type="SingleRoIExtractor",
                      roi_layer=dict(
                          type="RoIAlign",
                          output_size=7,
                          sampling_ratio=0,
                      ),
                      out_channels=1,
                      featmap_strides=[4, 8, 16, 32],
                  ),
                  bbox_head=dict(
                      type="Shared2FCBBoxHead",
                      in_channels=1,
                      fc_out_channels=1,
                      num_classes=4,
                  ),
                  mask_roi_extractor=dict(
                      type="SingleRoIExtractor",
                      roi_layer=dict(
                          type="RoIAlign",
                          output_size=14,
                          sampling_ratio=0,
                      ),
                      out_channels=1,
                      featmap_strides=[4, 8, 16, 32],
                  ),
                  mask_head=dict(
                      type="FCNMaskHead",
                      num_convs=1,
                      in_channels=1,
                      conv_out_channels=1,
                      num_classes=4,
                  ),
                  train_cfg=dict(
                      assigner=dict(
                          type="MaxIoUAssigner",
                          pos_iou_thr=0.5,
                          neg_iou_thr=0.5,
                          min_pos_iou=0.5,
                          match_low_quality=True,
                          ignore_iof_thr=-1,
                      ),
                      sampler=dict(
                          type="RandomSampler",
                          num=512,
                          pos_fraction=0.25,
                          neg_pos_ub=-1,
                          add_gt_as_proposals=True,
                      ),
                      mask_size=28,
                      pos_weight=-1,
                      debug=False,
                  ),
                  test_cfg=dict(
                      score_thr=0.05,
                      nms=dict(type="nms", iou_threshold=0.5),
                      max_per_img=100,
                      mask_thr_binary=0.5,
                  ),
              )
          )
      else:
          roi_head = Config(
              dict(
                  type="StandardRoIHead",
                  shared_head=dict(
                      type="ResLayer",
                      depth=50,
                      stage=3,
                      stride=2,
                      dilation=1,
                      style="caffe",
                      norm_cfg=dict(type="BN", requires_grad=False),
                      norm_eval=True,
                  ),
                  bbox_roi_extractor=dict(
                      type="SingleRoIExtractor",
                      roi_layer=dict(
                          type="RoIAlign",
                          output_size=14,
                          sampling_ratio=0,
                      ),
                      out_channels=1,
                      featmap_strides=[16],
                  ),
                  bbox_head=dict(
                      type="BBoxHead",
                      with_avg_pool=True,
                      in_channels=2048,
                      roi_feat_size=7,
                      num_classes=4,
                  ),
                  mask_roi_extractor=None,
                  mask_head=dict(
                      type="FCNMaskHead",
                      num_convs=0,
                      in_channels=2048,
                      conv_out_channels=1,
                      num_classes=4,
                  ),
                  train_cfg=dict(
                      assigner=dict(
                          type="MaxIoUAssigner",
                          pos_iou_thr=0.5,
                          neg_iou_thr=0.5,
                          min_pos_iou=0.5,
                          match_low_quality=False,
                          ignore_iof_thr=-1,
                      ),
                      sampler=dict(
                          type="RandomSampler",
                          num=512,
                          pos_fraction=0.25,
                          neg_pos_ub=-1,
                          add_gt_as_proposals=True,
                      ),
                      mask_size=14,
                      pos_weight=-1,
                      debug=False,
                  ),
                  test_cfg=dict(
                      score_thr=0.05,
                      nms=dict(type="nms", iou_threshold=0.5),
                      max_per_img=100,
                      mask_thr_binary=0.5,
                  ),
              )
          )
      return roi_head
  
file_path: mmdetection/tests/test_models/test_roi_heads/test_standard_roi_head.py
imports: import unittest
  from unittest import TestCase
  import torch
  from mmengine.config import Config
  from parameterized import parameterized
  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(with_shared_head) and returns: roi_head