class_docstr: Manages a TensorFlow model for training.
docstr: Load the model from provided local filepath.
docstr_tok: ["Load","the","model","from","provided","local","filepath","."]
code: def load_model(self, filepath, custom_objects, compile, options):
      """Load the model from provided local filepath."""
      self.load_params = dict(
          filepath=filepath,
          custom_objects=custom_objects,
          compile=compile,
          options=options,
      )
      if self.backend == "tf-distributed":
          with self.strategy.scope():
              self.model = self.process_model_load(**self.load_params)
      else:
          self.model = self.process_model_load(**self.load_params)
  
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 13 for calling the TFRunner obj's underlying member method code with example usage: obj.load_model(filepath, custom_objects, compile, options) without return types