code: def _fetch(name, content_type=None):
      """
      Load data or models from the package folder.
  
      Args:
          name (str): name of the resource
          content_type (str): either "data" or "trained_models"
  
      Returns:
          fileset (dict): dictionary containing the file content
      """
      package_name = "neuroner"
      resource_path = "/".join((content_type, name))
  
      # get dirs
      root_dir = os.path.dirname(
          pkg_resources.resource_filename(package_name, "__init__.py")
      )
      src_dir = os.path.join(root_dir, resource_path)
      dest_dir = os.path.join(".", content_type, name)
  
      if pkg_resources.resource_isdir(package_name, resource_path):
          # copy from package to dest dir
          if os.path.isdir(dest_dir):
              msg = "Directory '{}' already exists.".format(dest_dir)
              print(msg)
          else:
              shutil.copytree(src_dir, dest_dir)
              msg = "Directory created: '{}'.".format(dest_dir)
              print(msg)
      else:
          msg = "{} not found in {} package.".format(name, package_name)
          print(msg)
  
imports: import codecs
  import configparser
  import copy
  import distutils.util
  import glob
  import os
  import pickle
  from pprint import pprint
  import random
  import shutil
  import sys
  import time
  import warnings
  import pkg_resources
  import numpy
  import matplotlib
  import tensorflow
  from tensorflow.contrib.tensorboard.plugins import projector
  from neuroner import train
  from neuroner import dataset
  from neuroner.entity_lstm import EntityLSTM
  from neuroner import utils
  from neuroner import conll_to_brat
  from neuroner import evaluate
  from neuroner import brat_to_conll
  from neuroner import utils_nlp
label_desc: Use image node_id 3 for calling a global function with example usage: _fetch(name, content_type) without return types