code: def load_attributes_from_hdf5_group(group, name):
      """Loads attributes of the specified name from the HDF5 group.
  
      This method deals with an inherent problem
      of HDF5 file which is not able to store
      data larger than HDF5_OBJECT_HEADER_LIMIT bytes.
  
      Args:
          group: A pointer to a HDF5 group.
          name: A name of the attributes to load.
  
      Returns:
          data: Attributes data.
      """
      if name in group.attrs:
          data = [
              n.decode("utf8") if hasattr(n, "decode") else n
              for n in group.attrs[name]
          ]
      else:
          data = []
          chunk_id = 0
          while "%s%d" % (name, chunk_id) in group.attrs:
              data.extend(
                  [
                      n.decode("utf8") if hasattr(n, "decode") else n
                      for n in group.attrs["%s%d" % (name, chunk_id)]
                  ]
              )
              chunk_id += 1
      return data
  
imports: import json
  import os
  import numpy
  from tensorflow.python.keras import backend
  from tensorflow.python.keras import optimizer_v1
  from tensorflow.python.keras.saving import model_config
  from tensorflow.python.keras.saving import saving_utils
  from tensorflow.python.keras.saving.saved_model import json_utils
  from tensorflow.python.keras.utils.generic_utils import LazyLoader
  from tensorflow.python.keras.utils.io_utils import ask_to_proceed_with_overwrite
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import gfile
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 11 for calling a global function with example usage: load_attributes_from_hdf5_group(group, name) and returns: data