code: def __init__(
      self,
      model_file,
      model_type,
      path,
      extra_prediction_args,
      relevant_columns,
  ):
      self.model_file = model_file
      self.model_type = model_type
      self.path = path
      self.extra_prediction_args = (
          extra_prediction_args
          if extra_prediction_args is not None
          else []
      )
      self.relevant_columns = relevant_columns
      self.genmodel_jar_path = os.path.join(path, "h2o-genmodel.jar")
  
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 1 to create a new _H2OModelWrapper object  with example: obj = _H2OModelWrapper(model_file, model_type, path, extra_prediction_args, relevant_columns)