code: def _datasets(proto, prepare_data_iterator=True):
      datasets = OrderedDict()
      for i, d in enumerate(proto.dataset):
          datasets[d.name] = _create_dataset(
              d.uri,
              d.batch_size,
              d.shuffle,
              d.no_image_normalization,
              d.cache_dir,
              d.overwrite_cache,
              d.create_cache_explicitly,
              prepare_data_iterator,
              i,
          )
      return datasets
  
imports: from collections import OrderedDict
  import google.protobuf.text_format
  import itertools
  import numpy
  import os
  import re
  import shutil
  import tempfile
  from nnabla.initializer import NormalInitializer, UniformInitializer, ConstantInitializer, RangeInitializer, calc_normal_std_he_forward, calc_normal_std_he_backward, calc_normal_std_glorot, calc_uniform_lim_glorot
  from nnabla.logger import logger
  from nnabla.parameter import get_parameter_or_create
  from nnabla.utils import nnabla_pb2
  from nnabla.utils.data_iterator import data_iterator_csv_dataset, data_iterator_cache
  from nnabla.utils.create_cache import CreateCache
  from nnabla.utils.load_function import _create_function_instance
  from nnabla.utils.nnp_format import nnp_version
  from nnabla.utils.communicator_util import current_communicator, single_or_rankzero
  from nnabla.utils.learning_rate_scheduler import PolynomialScheduler, CosineScheduler, ExponentialScheduler, StepScheduler, LinearWarmupScheduler
  from legacy_network import Network
  from nnabla.utils.progress import progress
  from legacy_get_file_handle import get_file_handle_load, get_buf_type
  import nnabla
  import nnabla.function
  import nnabla.solver
label_desc: Use image node_id 13 for calling a global function with example usage: _datasets(proto, prepare_data_iterator) and returns: datasets