code: def get_input_example(
      h2o_model, number_of_records=5, relevant_columns_only=True
  ):
      """
      Creates an example Pandas dataset from the training dataset of H2O binary model.
  
      :param h2o_model: An H2O binary model.
      :param number_of_records: A number of records that will be extracted from the training dataset.
      :param relevant_columns_only: A flag indicating whether the output dataset should contain
                                    only columns required by the model.  Defaults to ``True``.
      :return: Pandas dataset made from the training dataset of H2O binary model
      """
  
      import h2o
  
      frame = h2o.get_frame(
          h2o_model.actual_params["training_frame"]
      ).head(number_of_records)
      result = frame.as_data_frame()
      if relevant_columns_only:
          relevant_columns = _get_relevant_columns(h2o_model)
          input_columns = [
              col for col in frame.col_names if col in relevant_columns
          ]
          return result[input_columns]
      else:
          return result
  
imports: import logging
  import os
  import tempfile
  import pandas
  import subprocess
  import sys
  import yaml
  import mlflow
  from mlflow import pyfunc
  from mlflow.models import Model
  from mlflow.models.model import MLMODEL_FILE_NAME
  from mlflow.models.utils import _save_example
  from mlflow.models import ModelSignature, ModelInputExample
  from mlflow.utils.environment import _CONDA_ENV_FILE_NAME, _CONSTRAINTS_FILE_NAME, _PYTHON_ENV_FILE_NAME, _REQUIREMENTS_FILE_NAME, _mlflow_conda_env, _process_conda_env, _process_pip_requirements, _PythonEnv, _validate_env_arguments
  from mlflow.utils.file_utils import write_to
  from mlflow.utils.model_utils import _get_flavor_configuration, _validate_and_copy_code_paths, _validate_and_prepare_target_save_path
  from mlflow.tracking.artifact_utils import _download_artifact_from_uri
  from mlflow.utils.requirements_utils import _get_pinned_requirement
label_desc: Use image node_id 5 for calling a global function with example usage: get_input_example(h2o_model, number_of_records, relevant_columns_only) and returns: result, result