class_docstr: Flavor backend implementation for the generic python models.
code: def generate_dockerfile(
      self,
      model_uri,
      output_path="mlflow-dockerfile",
      install_mlflow=False,
      mlflow_home=None,
      enable_mlserver=False,
  ):
      copy_model_into_container = (
          self.copy_model_into_container_wrapper(
              model_uri, install_mlflow, enable_mlserver
          )
      )
      pyfunc_entrypoint = _pyfunc_entrypoint(
          self._env_manager, model_uri, install_mlflow, enable_mlserver
      )
  
      mlflow_home = (
          os.path.abspath(mlflow_home) if mlflow_home else None
      )
  
      is_conda = self._env_manager == _EnvManager.CONDA
      setup_miniconda = ""
      setup_pyenv_and_virtualenv = ""
  
      if is_conda:
          setup_miniconda = SETUP_MINICONDA
      else:
          setup_pyenv_and_virtualenv = SETUP_PYENV_AND_VIRTUALENV
  
      os.makedirs(output_path, exist_ok=True)
  
      _logger.debug(
          "Created all folders in path",
          extra={"output_directory": output_path},
      )
      install_mlflow = _get_mlflow_install_step(
          output_path, mlflow_home
      )
  
      custom_setup_steps = copy_model_into_container(output_path)
  
      dockerfile_text = _generate_dockerfile_content(
          setup_miniconda=setup_miniconda,
          setup_pyenv_and_virtualenv=setup_pyenv_and_virtualenv,
          install_mlflow=install_mlflow,
          custom_setup_steps=custom_setup_steps,
          entrypoint=pyfunc_entrypoint,
      )
      _logger.debug(
          "generated dockerfile text",
          extra={"dockerfile": dockerfile_text},
      )
  
      with open(
          os.path.join(output_path, "Dockerfile"), "w"
      ) as dockerfile:
          dockerfile.write(dockerfile_text)
  
imports: import ctypes
  import logging
  import os
  import pathlib
  import posixpath
  import shlex
  import signal
  import subprocess
  import sys
  import warnings
  from pathlib import Path
  from mlflow.environment_variables import MLFLOW_DISABLE_ENV_CREATION
  from mlflow.exceptions import MlflowException
  from mlflow.models import FlavorBackend
  from mlflow.models.container import ENABLE_MLSERVER
  from mlflow.models.docker_utils import SETUP_MINICONDA, SETUP_PYENV_AND_VIRTUALENV, _build_image, _generate_dockerfile_content, _get_mlflow_install_step
  from mlflow.pyfunc import ENV, _extract_conda_env, _mlflow_pyfunc_backend_predict, mlserver, scoring_server
  from mlflow.tracking.artifact_utils import _download_artifact_from_uri
  from mlflow.utils import env_manager
  from mlflow.utils.conda import get_conda_bin_executable, get_or_create_conda_env
  from mlflow.utils.environment import Environment
  from mlflow.utils.file_utils import get_or_create_nfs_tmp_dir, get_or_create_tmp_dir, path_to_local_file_uri
  from mlflow.utils.nfs_on_spark import get_nfs_cache_root_dir
  from mlflow.utils.process import ShellCommandException, cache_return_value_per_process
  from mlflow.utils.virtualenv import _get_or_create_virtualenv, _get_pip_install_mlflow
  from mlflow.version import VERSION
label_desc: Use image node_id 7 for calling the PyFuncBackend obj's underlying member method code with example usage: obj.generate_dockerfile(model_uri, output_path, install_mlflow, mlflow_home, enable_mlserver) without return types