class_docstr: Manages a TensorFlow model for training.
docstr: Loads all layer weights from a TensorFlow or an HDF5 weight file.
docstr_tok: ["Loads","all","layer","weights","from","a","TensorFlow","or","an","HDF5","weight","file","."]
code: def load_weights(self, filepath, by_name, skip_mismatch, options):
      """Loads all layer weights from a TensorFlow or an HDF5 weight file."""
      if options:
          self.model.load_weights(
              filepath, by_name, skip_mismatch, options
          )
      else:  # To support older TensorFlow versions such as 2.1
          self.model.load_weights(filepath, by_name, skip_mismatch)
  
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 16 for calling the TFRunner obj's underlying member method code with example usage: obj.load_weights(filepath, by_name, skip_mismatch, options) without return types