code: def ListDataset(
      data_iter: Dataset,
      freq: str,
      one_dim_target: bool = True,
      use_timestamp: bool = False,
      translate: Optional[dict] = None,
  ) -> List[DataEntry]:
      """
      Dataset backed directly by a list of dictionaries.
  
      Parameters
      ----------
      data_iter
          Iterable object yielding all items in the dataset.
          Each item should be a dictionary mapping strings to values.
          For instance: {"start": "2014-09-07", "target": [0.1, 0.2]}.
      freq
          Frequency of the observation in the time series.
          Must be a valid Pandas frequency.
      one_dim_target
          Whether to accept only univariate target time series.
      """
  
      if translate is not None:
          data_iter = Map(Translator.parse(translate), data_iter)
  
      return list(
          Map(
              ProcessDataEntry(
                  to_offset(freq), one_dim_target, use_timestamp
              ),
              data_iter,
          )
      )
  
imports: import functools
  import logging
  import shutil
  from pathlib import Path
  from types import ModuleType
  from typing import Callable, List, NamedTuple, Optional, Union, cast
  import numpy
  import pandas
  from pandas.tseries.frequencies import to_offset
  from gluonts import json
  from gluonts.itertools import Cached, Map
  from gluonts.dataset.field_names import FieldName
  from gluonts.dataset.schema import Translator
  from gluonts.exceptions import GluonTSDataError
  from gluonts.pydantic import pydantic
  from .None import Dataset, DatasetCollection, DataEntry, DataBatch
  from .None import jsonl, DatasetWriter
label_desc: Use image node_id 5 for calling a global function with example usage: ListDataset(data_iter, freq, one_dim_target, use_timestamp, translate) and returns: list