class_docstr: Implementation of `Masked-attention Mask
  Transformer for Universal Image Segmentation
  <https://arxiv.org/pdf/2112.01527>`_.
  
  Args:
      backbone (dict): Configuration of backbone. Defaults to None.
      track_head (dict): Configuration of track head. Defaults to None.
      data_preprocessor (dict or ConfigDict, optional): The pre-process
         config of :class:`TrackDataPreprocessor`.  it usually includes,
          ``pad_size_divisor``, ``pad_value``, ``mean`` and ``std``.
          Defaults to None.
      init_cfg (dict or list[dict]): Configuration of initialization.
          Defaults to None.
class_docstr_tok: ["Implementation","of","`","Masked-attention","Mask","Transformer","for","Universal","Image","Segmentation","<","https",":","\/\/arxiv.org\/pdf\/2112.01527",">","`","_",".","Args",":","backbone","(","dict",")",":","Configuration","of","backbone",".","Defaults","to","None",".","track_head","(","dict",")",":","Configuration","of","track","head",".","Defaults","to","None",".","data_preprocessor","(","dict","or","ConfigDict",",","optional",")",":","The","pre-process","config","of",":","class",":","`","TrackDataPreprocessor","`",".","it","usually","includes",",","``","pad_size_divisor","``",",","``","pad_value","``",",","``","mean","``","and","``","std","``",".","Defaults","to","None",".","init_cfg","(","dict","or","list","[","dict","]",")",":","Configuration","of","initialization",".","Defaults","to","None","."]
docstr: Overload in order to load mmdet pretrained ckpt.
docstr_tok: ["Overload","in","order","to","load","mmdet","pretrained","ckpt","."]
code: def _load_from_state_dict(
      self,
      state_dict,
      prefix,
      local_metadata,
      strict,
      missing_keys,
      unexpected_keys,
      error_msgs,
  ):
      """Overload in order to load mmdet pretrained ckpt."""
      for key in list(state_dict):
          if key.startswith("panoptic_head"):
              state_dict[
                  key.replace("panoptic", "track")
              ] = state_dict.pop(key)
  
      super()._load_from_state_dict(
          state_dict,
          prefix,
          local_metadata,
          strict,
          missing_keys,
          unexpected_keys,
          error_msgs,
      )
  
file_path: mmdetection/mmdet/models/vis/mask2former_vis.py
imports: from typing import Optional, Union
  from torch import Tensor
  from mmdet.models.mot import BaseMOTModel
  from mmdet.registry import MODELS
  from mmdet.structures import TrackDataSample, TrackSampleList
  from mmdet.utils import OptConfigType, OptMultiConfig
label_desc: Use image node_id 2 for calling the Mask2FormerVideo obj's underlying member method code with example usage: obj._load_from_state_dict(state_dict, prefix, local_metadata, strict, missing_keys, unexpected_keys, error_msgs) without return types