code: def _download_all_example_data(verbose=True):
      """Download all datasets used in examples and tutorials."""
      # This function is designed primarily to be used by CircleCI, to:
      #
      # 1. Streamline data downloading
      # 2. Make CircleCI fail early (rather than later) if some necessary data
      #    cannot be retrieved.
      # 3. Avoid download statuses and timing biases in rendered examples.
      #
      # verbose=True by default so we get nice status messages.
      # Consider adding datasets from here to CircleCI for PR-auto-build
      paths = dict()
      for kind in (
          "sample testing misc spm_face somato hf_sef multimodal "
          "fnirs_motor opm mtrf fieldtrip_cmc kiloword phantom_kit phantom_4dbti "
          "refmeg_noise ssvep epilepsy_ecog ucl_opm_auditory eyelink "
          "erp_core brainstorm.bst_raw brainstorm.bst_auditory "
          "brainstorm.bst_resting brainstorm.bst_phantom_ctf "
          "brainstorm.bst_phantom_elekta phantom_kernel"
      ).split():
          mod = importlib.import_module(f"mne.datasets.{kind}")
          data_path_func = getattr(mod, "data_path")
          kwargs = dict()
          if "accept" in inspect.getfullargspec(data_path_func).args:
              kwargs["accept"] = True
          paths[kind] = data_path_func(**kwargs)
          logger.info(f"[done {kind}]")
  
      # Now for the exceptions:
      from . import (
          eegbci,
          fetch_fsaverage,
          fetch_hcp_mmp_parcellation,
          fetch_infant_template,
          fetch_phantom,
          limo,
          sleep_physionet,
      )
  
      eegbci.load_data(1, [6, 10, 14], update_path=True)
      for subj in range(4):
          eegbci.load_data(subj + 1, runs=[3], update_path=True)
      logger.info("[done eegbci]")
  
      sleep_physionet.age.fetch_data(subjects=[0, 1], recording=[1])
      logger.info("[done sleep_physionet]")
  
      # If the user has SUBJECTS_DIR, respect it, if not, set it to the EEG one
      # (probably on CircleCI, or otherwise advanced user)
      fetch_fsaverage(None)
      logger.info("[done fsaverage]")
  
      fetch_infant_template("6mo")
      logger.info("[done infant_template]")
  
      fetch_hcp_mmp_parcellation(
          subjects_dir=paths["sample"] / "subjects", accept=True
      )
      logger.info("[done hcp_mmp_parcellation]")
  
      fetch_phantom(
          "otaniemi",
          subjects_dir=paths["brainstorm.bst_phantom_elekta"],
      )
      logger.info("[done phantom]")
  
      limo.load_data(subject=1, update_path=True)
      logger.info("[done limo]")
  
imports: import importlib
  import inspect
  import logging
  import os
  import os.path
  import sys
  import tempfile
  import time
  import zipfile
  from collections import OrderedDict
  from pathlib import Path
  import numpy
  from ..label import Label, read_labels_from_annot, write_labels_to_annot
  from ..utils import _pl, _safe_input, _validate_type, get_config, get_subjects_dir, logger, set_config, verbose
  from ..utils.docs import _docformat, docdict
  from .config import MNE_DATASETS, _hcp_mmp_license_text
label_desc: Use image node_id 8 for calling a global function with example usage: _download_all_example_data(verbose) without return types