class_docstr: Wrapper class that creates a predict function such that
  predict(model_input: pd.DataFrame) -> model's output as pd.DataFrame (pandas DataFrame)
class_docstr_tok: ["Wrapper","class","that","creates","a","predict","function","such","that","predict","(","model_input",":","pd.DataFrame",")","-",">","model","'s","output","as","pd.DataFrame","(","pandas","DataFrame",")"]
docstr: :param python_model: An instance of a subclass of :class:`~PythonModel`.
  :param context: A :class:`~PythonModelContext` instance containing artifacts that
                  ``python_model`` may use when performing inference.
  :param signature: :class:`~ModelSignature` instance describing model input and output.
code: def __init__(self, python_model, context, signature):
      """
      :param python_model: An instance of a subclass of :class:`~PythonModel`.
      :param context: A :class:`~PythonModelContext` instance containing artifacts that
                      ``python_model`` may use when performing inference.
      :param signature: :class:`~ModelSignature` instance describing model input and output.
      """
      self.python_model = python_model
      self.context = context
      self.signature = signature
  
imports: import inspect
  import logging
  import os
  import shutil
  from abc import ABCMeta, abstractmethod
  from pathlib import Path
  from typing import Any, Dict, List, Optional
  import cloudpickle
  import yaml
  import mlflow.pyfunc
  import mlflow.utils
  from mlflow.exceptions import MlflowException
  from mlflow.models import Model
  from mlflow.models.model import MLMODEL_FILE_NAME
  from mlflow.models.signature import _extract_type_hints
  from mlflow.tracking.artifact_utils import _download_artifact_from_uri
  from mlflow.utils.annotations import experimental
  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
  from mlflow.utils.file_utils import TempDir, _copy_file_or_tree, get_total_file_size, write_to
  from mlflow.utils.model_utils import _get_flavor_configuration
  from mlflow.utils.requirements_utils import _get_pinned_requirement
label_desc: Use image node_id 1 to create a new _PythonModelPyfuncWrapper object  with example: obj = _PythonModelPyfuncWrapper(python_model, context, signature)