code: def load_model(filepath, custom_objects=None, compile=True):
      import tensorflow as tf
  
      if is_local_path(filepath):
          model = tf.keras.models.load_model(
              filepath, custom_objects=custom_objects, compile=compile
          )
      else:
          file_name = os.path.basename(filepath)
          temp_dir = tempfile.mkdtemp()
          temp_path = os.path.join(temp_dir, file_name)
          try:
              if filepath.endswith(".h5") or filepath.endswith(
                  ".keras"
              ):
                  get_remote_file_to_local(filepath, temp_path)
              else:
                  get_remote_dir_to_local(filepath, temp_path)
  
              model = tf.keras.models.load_model(
                  temp_path,
                  custom_objects=custom_objects,
                  compile=compile,
              )
          finally:
              shutil.rmtree(temp_dir)
      return model
  
imports: from contextlib import closing
  import socket
  import sys
  import tempfile
  import shutil
  from bigdl.dllib.utils import log4Error
  from bigdl.dllib.utils.common import callBigDlFunc
  from bigdl.dllib.utils.file_utils import get_file_list, is_local_path
  from bigdl.orca.data import SparkXShards
  from bigdl.orca.data.utils import get_size
  from bigdl.orca.data.file import put_local_dir_tree_to_remote, put_local_file_to_remote, get_remote_file_to_local, get_remote_dir_to_local
  from bigdl.dllib.utils.utils import convert_row_to_numpy
  from functools import partial
  import numpy
  from bigdl.orca.common import SafePickle
  import os
  import subprocess
  from bigdl.dllib.utils.log4Error import *
label_desc: Use image node_id 37 for calling a global function with example usage: load_model(filepath, custom_objects, compile) and returns: model