code: def forecast_cli(
      model_path: str,
      dataset: Union[str, dict, pd.DataFrame] = None,
      data_format: Optional[str] = None,
      horizon: int = 1,
      output_directory: Optional[str] = None,
      output_format: str = "parquet",
      callbacks: List[Callback] = None,
      backend: Union[Backend, str] = None,
      logging_level: int = logging.INFO,
      **kwargs,
  ) -> None:
      """Loads pre-trained model to forecast on the provided dataset.
  
      # Inputs
  
      :param model_path: (str) filepath to pre-trained model.
      :param dataset: (Union[str, dict, pandas.DataFrame], default: `None`)
          source containing the entire dataset to be used in the prediction.
      :param data_format: (str, default: `None`) format to interpret data
          sources. Will be inferred automatically if not specified.
      :param horizon: How many samples into the future to forecast.
      :param output_directory: (str, default: `'results'`) the directory that
          will contain the forecasted values.
      :param output_format: (str) format of the output dataset.
      :param callbacks: (list, default: `None`) a list of
          `ludwig.callbacks.Callback` objects that provide hooks into the
          Ludwig pipeline.
      :param backend: (Union[Backend, str]) `Backend` or string name
          of backend to use to execute preprocessing / training steps.
      :param logging_level: (int) Log level that will be sent to stderr.
  
      # Returns
  
      :return: ('None')
      """
      model = LudwigModel.load(
          model_path,
          logging_level=logging_level,
          backend=backend,
          callbacks=callbacks,
      )
      model.forecast(
          dataset=dataset,
          data_format=data_format,
          horizon=horizon,
          output_directory=output_directory,
          output_format=output_format,
      )
  
file_path: ludwig/ludwig/forecast.py
imports: import argparse
  import logging
  import sys
  from typing import List, Optional, Union
  import pandas
  from ludwig.api import LudwigModel
  from ludwig.backend import ALL_BACKENDS, Backend, initialize_backend
  from ludwig.callbacks import Callback
  from ludwig.contrib import add_contrib_callback_args
  from ludwig.globals import LUDWIG_VERSION
  from ludwig.utils.print_utils import get_logging_level_registry, print_ludwig
label_desc: Use image node_id 1 for calling a global function with example usage: forecast_cli(model_path, dataset, data_format, horizon, output_directory, output_format, callbacks, backend, logging_level) without return types