class_docstr: ### Lab
  
  Lab contains the labml specific properties.
class_docstr_tok: ["#","#","#","Lab","Lab","contains","the","labml","specific","properties","."]
code: def __default_config():
      return dict(
          path=None,
          check_repo_dirty=False,
          config_file_path=None,
          data_path="data",
          experiments_path="logs",
          analytics_path="analytics",
          analytics_templates={},
          app_url=None,
          app_track_frequency=0,
          app_open_browser=True,
          indicators=[
              {"class_name": "Scalar", "is_print": True, "name": "*"},
              {
                  "class_name": "Scalar",
                  "is_print": False,
                  "name": "param.*",
              },
              {
                  "class_name": "Scalar",
                  "is_print": False,
                  "name": "grad.*",
              },
              {
                  "class_name": "Scalar",
                  "is_print": False,
                  "name": "module.*",
              },
              {
                  "class_name": "Scalar",
                  "is_print": False,
                  "name": "optim.*",
              },
              {
                  "class_name": "Scalar",
                  "is_print": False,
                  "name": "time.*",
              },
              {
                  "class_name": "Scalar",
                  "is_print": False,
                  "name": "hp.*",
              },
          ],
      )
  
imports: from copy import deepcopy
  from pathlib import Path
  from typing import Optional, Dict
  from labml.logger import Text
  from labml.utils import get_caller_file
  from labml.utils.notice import labml_notice
  from .None import util
  from .app.configs import AppTrackConfigs
  from .util import is_colab, is_kaggle
label_desc: Use image node_id 9 for calling the Lab obj's underlying member method code with example usage: obj.__default_config() and returns: dict