class_docstr: Manages a TensorFlow model for training.
docstr: Initializes the runner.
  Args:
      model_creator (dict -> Model): see tf_trainer.py.
      data_creator (dict -> tf.Dataset, tf.Dataset): see tf_trainer.py.
      config (dict): see tf_trainer.py.
      verbose (bool): Outputs training data if true.
docstr_tok: ["Initializes","the","runner",".","Args",":","model_creator","(","dict","-",">","Model",")",":","see","tf_trainer.py",".","data_creator","(","dict","-",">","tf.Dataset",",","tf.Dataset",")",":","see","tf_trainer.py",".","config","(","dict",")",":","see","tf_trainer.py",".","verbose","(","bool",")",":","Outputs","training","data","if","true","."]
code: def __init__(
      self,
      model_creator=None,
      compile_args_creator=None,
      config=None,
      verbose=False,
  ):
      """Initializes the runner.
      Args:
          model_creator (dict -> Model): see tf_trainer.py.
          data_creator (dict -> tf.Dataset, tf.Dataset): see tf_trainer.py.
          config (dict): see tf_trainer.py.
          verbose (bool): Outputs training data if true.
      """
  
      self.model_creator = model_creator
      self.compile_args_creator = compile_args_creator
      self.config = {} if config is None else config
      self.inter_op_parallelism = self.config.get(
          "inter_op_parallelism", 1
      )
      self.intra_op_parallelism = self.config.get(
          "intra_op_parallelism", 1
      )
      self.verbose = verbose
  
imports: import json
  import os
  import socket
  import shutil
  import tempfile
  import copy
  import ray
  from contextlib import closing
  from bigdl.dllib.utils import log4Error
  from bigdl.orca.data.utils import partitions_get_data_label, partitions_get_tf_dataset
  from bigdl.orca.data.file import is_file, get_remote_file_to_local, get_remote_dir_to_local, get_remote_files_with_prefix_to_local, put_local_file_to_remote, put_local_dir_tree_to_remote, put_local_files_with_prefix_to_remote
  from bigdl.orca.learn.utils import process_tensorboard_in_callbacks
  from bigdl.dllib.utils.log4Error import *
label_desc: Use image node_id 1 to create a new TFRunner object  with example: obj = TFRunner(model_creator, compile_args_creator, config, verbose)