class_docstr: Object Detection general task.
  
  Parameters
  ----------
  config : dict
      The configurations, can be nested dict.
  logger : logging.Logger
      The desired logger object, use `None` for module specific logger with default setting.
class_docstr_tok: ["Object","Detection","general","task",".","Parameters","--","--","--","--","--","config",":","dict","The","configurations",",","can","be","nested","dict",".","logger",":","logging.Logger","The","desired","logger","object",",","use","`","None","`","for","module","specific","logger","with","default","setting","."]
code: def fit_summary(self):
      return copy.copy(self._fit_summary)
  
imports: import time
  import os
  import math
  import copy
  import logging
  import pprint
  import json
  import pickle
  from typing import Union, Tuple
  import uuid
  import shutil
  import numpy
  import pandas
  from autocfg import dataclass
  import autogluon.core
  from autogluon.core.decorator import sample_config
  from autogluon.core.scheduler.resource import get_cpu_count, get_gpu_count
  from autogluon.core.task.base import BaseTask
  from autogluon.core.searcher import RandomSearcher
  from ..estimators.base_estimator import BaseEstimator
  from ..estimators import SSDEstimator, FasterRCNNEstimator, YOLOv3Estimator, CenterNetEstimator
  from .utils import auto_suggest, config_to_nested
  from ..data.dataset import ObjectDetectionDataset
  from ..estimators.conf import _BEST_CHECKPOINT_FILE
label_desc: Use image node_id 3 for calling the ObjectDetection obj's underlying member method code with example usage: obj.fit_summary() and returns: copy