code: def get_public_dataset(
      name, path="~/.chronos/dataset", redownload=False, **kwargs
  ):
      """
      Get public dataset.
  
      >>> from bigdl.chronos.data import get_public_dataset
      >>> tsdata_network_traffic = get_public_dataset(name="network_traffic")
  
      :param name: str, public dataset name, e.g. "network_traffic".
             We only support network_traffic, AIOps, fsi, nyc_taxi, uci_electricity,
             uci_electricity_wide, tsinghua_electricity
      :param path: str, download path, the value defatults to "~/.chronos/dataset/".
      :param redownload: bool, if redownload the raw dataset file(s).
      :param kwargs: extra arguments passed to initialize the tsdataset,
             including with_split, val_ratio and test_ratio.
      """
      from bigdl.nano.utils.common import invalidInputError
  
      invalidInputError(
          isinstance(name, str) and isinstance(path, str),
          "Name and path must be string.",
      )
  
      if name.lower().strip() == "network_traffic":
          return (
              PublicDataset(
                  name="network_traffic",
                  path=path,
                  redownload=redownload,
                  **kwargs,
              )
              .get_public_data()
              .preprocess_network_traffic()
              .get_tsdata(
                  dt_col="StartTime", target_col=["AvgRate", "total"]
              )
          )
      elif name.lower().strip() == "aiops":
          return (
              PublicDataset(
                  name="AIOps",
                  path=path,
                  redownload=redownload,
                  **kwargs,
              )
              .get_public_data()
              .preprocess_AIOps()
              .get_tsdata(dt_col="time_step", target_col=["cpu_usage"])
          )
      elif name.lower().strip() == "fsi":
          return (
              PublicDataset(
                  name="fsi", path=path, redownload=redownload, **kwargs
              )
              .get_public_data()
              .preprocess_fsi()
              .get_tsdata(dt_col="ds", target_col=["y"])
          )
      elif name.lower().strip() == "nyc_taxi":
          return (
              PublicDataset(
                  name="nyc_taxi",
                  path=path,
                  redownload=redownload,
                  **kwargs,
              )
              .get_public_data()
              .preprocess_nyc_taxi()
              .get_tsdata(dt_col="timestamp", target_col=["value"])
          )
      elif name.lower().strip() == "uci_electricity":
          return (
              PublicDataset(
                  name="uci_electricity",
                  path=path,
                  redownload=redownload,
                  **kwargs,
              )
              .get_public_data()
              .preprocess_uci_electricity()
              .get_tsdata(
                  dt_col="timestamp", target_col=["value"], id_col="id"
              )
          )
      elif name.lower().strip() == "uci_electricity_wide":
          target = []
          for i in range(370):
              target.append("MT_" + str(i + 1).zfill(3))
          return (
              PublicDataset(
                  name="uci_electricity_wide",
                  path=path,
                  redownload=redownload,
                  **kwargs,
              )
              .get_public_data()
              .preprocess_uci_electricity_wide()
              .get_tsdata(dt_col="timestamp", target_col=target)
          )
      elif name.lower().strip() == "tsinghua_electricity":
          target = []
          for i in range(0, 320):
              target.append(str(i))
          target.append("OT")
          dataset = (
              PublicDataset(
                  name="tsinghua_electricity",
                  path=path,
                  redownload=False,
                  **kwargs,
              )
              .preprocess_tsinghua_electricity()
              .get_tsdata(dt_col="date", target_col=target)
          )
          return dataset
  
      else:
          invalidInputError(
              False,
              "Only network_traffic, AIOps, fsi, nyc_taxi, uci_electricity"
              " uci_electricity_wide "
              f"are supported in Chronos built-in dataset, while get {name}.",
          )
  
imports: import numpy
  import pandas
  import time
  from bigdl.chronos.data.utils.public_dataset import PublicDataset
  from bigdl.chronos.data.tsdataset import TSDataset
label_desc: Use image node_id 1 for calling a global function with example usage: get_public_dataset(name, path, redownload) and returns: PublicDataset, PublicDataset, PublicDataset, PublicDataset, PublicDataset, PublicDataset, dataset