code: def get_params(h2o_model):
      """
      Extracts training parameters for the H2O binary model.
  
      :param h2o_model: An H2O binary model.
      :return: A dictionary of parameters that were used for training the model.
      """
  
      def is_valid(key):
          return (
              key != "model_id"
              and not key.endswith("_frame")
              and not key.startswith("keep_cross_validation_")
          )
  
      return {
          key: val
          for key, val in h2o_model.actual_params.items()
          if is_valid(key)
      }
  
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 3 for calling a global function with example usage: get_params(h2o_model) and returns: unknown, unknown