code: def load_sharded_statistics(
      input_path_prefix: Optional[str] = None,
      input_paths: Optional[Iterable[str]] = None,
      io_provider: Optional[
          artifacts_io_impl.StatisticsIOProvider
      ] = None,
  ) -> DatasetListView:
      """Read a sharded DatasetFeatureStatisticsList from disk as a DatasetListView.
  
      Args:
        input_path_prefix: If passed, loads files starting with this prefix and
          ending with a pattern corresponding to the output of the provided
            io_provider.
        input_paths: A list of file paths of files containing sharded
          DatasetFeatureStatisticsList protos.
        io_provider: Optional StatisticsIOProvider. If unset, a default will be
          constructed.
  
      Returns:
        A DatasetListView containing the merged proto.
      """
      if input_path_prefix is None == input_paths is None:
          raise ValueError(
              "Must provide one of input_paths_prefix, input_paths."
          )
      if io_provider is None:
          io_provider = artifacts_io_impl.get_io_provider()
      if input_path_prefix is not None:
          input_paths = io_provider.glob(input_path_prefix)
      if not input_paths:
          raise ValueError(
              "No input paths found paths=%s, pattern=%s"
              % (input_paths, input_path_prefix)
          )
      acc = statistics.DatasetListAccumulator()
      stats_iter = io_provider.record_iterator_impl(input_paths)
      for stats_list in stats_iter:
          for dataset in stats_list.datasets:
              acc.MergeDatasetFeatureStatistics(
                  dataset.SerializeToString()
              )
      stats = statistics_pb2.DatasetFeatureStatisticsList()
      stats.ParseFromString(acc.Get())
      return DatasetListView(stats)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import logging
  from typing import Dict, Iterable, Optional, Sequence, Text, Tuple, Union
  import numpy
  import pyarrow
  import tensorflow
  from tensorflow_data_validation import constants
  from tensorflow_data_validation import types
  from tensorflow_data_validation.arrow import arrow_util
  from tensorflow_data_validation.utils import artifacts_io_impl
  from tensorflow_data_validation.utils import io_util
  from tfx_bsl import statistics
  from tfx_bsl.arrow import array_util
  from google.protobuf import text_format
  from tensorflow_metadata.proto.v0 import statistics_pb2
label_desc: Use image node_id 15 for calling a global function with example usage: load_sharded_statistics(input_path_prefix, input_paths, io_provider) and returns: DatasetListView