code: def _create_model_cfg(self):
      cfg_path = "maskformer/maskformer_r50_ms-16xb1-75e_coco.py"
      model_cfg = get_detector_cfg(cfg_path)
      base_channels = 32
      model_cfg.backbone.depth = 18
      model_cfg.backbone.init_cfg = None
      model_cfg.backbone.base_channels = base_channels
      model_cfg.panoptic_head.in_channels = [
          base_channels * 2**i for i in range(4)
      ]
      model_cfg.panoptic_head.feat_channels = base_channels
      model_cfg.panoptic_head.out_channels = base_channels
      model_cfg.panoptic_head.pixel_decoder.encoder.layer_cfg.self_attn_cfg.embed_dims = (
          base_channels
      )
      model_cfg.panoptic_head.pixel_decoder.encoder.layer_cfg.ffn_cfg.embed_dims = (
          base_channels
      )
      model_cfg.panoptic_head.pixel_decoder.encoder.layer_cfg.ffn_cfg.feedforward_channels = (
          base_channels * 8
      )
      model_cfg.panoptic_head.pixel_decoder.positional_encoding.num_feats = (
          base_channels // 2
      )
      model_cfg.panoptic_head.positional_encoding.num_feats = (
          base_channels // 2
      )
      model_cfg.panoptic_head.transformer_decoder.layer_cfg.self_attn_cfg.embed_dims = (
          base_channels
      )
      model_cfg.panoptic_head.transformer_decoder.layer_cfg.cross_attn_cfg.embed_dims = (
          base_channels
      )
      model_cfg.panoptic_head.transformer_decoder.layer_cfg.ffn_cfg.embed_dims = (
          base_channels
      )
      model_cfg.panoptic_head.transformer_decoder.layer_cfg.ffn_cfg.feedforward_channels = (
          base_channels * 8
      )
      return model_cfg
  
imports: import unittest
  import torch
  from parameterized import parameterized
  from mmdet.registry import MODELS
  from mmdet.structures import DetDataSample
  from mmdet.testing._utils import demo_mm_inputs, get_detector_cfg
  from mmdet.utils import register_all_modules
label_desc: Use image node_id 2 for calling the TestMaskFormer obj's underlying member method code with example usage: obj._create_model_cfg() and returns: model_cfg