class_docstr: Flavor backend implementation for the generic python models.
code: def prepare_env(
      self,
      model_uri,
      capture_output=False,
      pip_requirements_override=None,
  ):
      if self._environment is not None:
          return self._environment
  
      @cache_return_value_per_process
      def _get_or_create_env_root_dir(should_use_nfs):
          if should_use_nfs:
              root_tmp_dir = get_or_create_nfs_tmp_dir()
          else:
              root_tmp_dir = get_or_create_tmp_dir()
  
          env_root_dir = os.path.join(root_tmp_dir, "envs")
          os.makedirs(env_root_dir, exist_ok=True)
          return env_root_dir
  
      local_path = _download_artifact_from_uri(model_uri)
      if self._create_env_root_dir:
          if self._env_root_dir is not None:
              raise Exception(
                  "env_root_dir can not be set when create_env_root_dir=True"
              )
          nfs_root_dir = get_nfs_cache_root_dir()
          env_root_dir = _get_or_create_env_root_dir(
              nfs_root_dir is not None
          )
      else:
          env_root_dir = self._env_root_dir
  
      if self._env_manager == _EnvManager.VIRTUALENV:
          activate_cmd = _get_or_create_virtualenv(
              local_path,
              self._env_id,
              env_root_dir=env_root_dir,
              capture_output=capture_output,
              pip_requirements_override=pip_requirements_override,
          )
          self._environment = Environment(activate_cmd)
      elif self._env_manager == _EnvManager.CONDA:
          conda_env_path = os.path.join(
              local_path, _extract_conda_env(self._config[ENV])
          )
          self._environment = get_or_create_conda_env(
              conda_env_path,
              env_id=self._env_id,
              capture_output=capture_output,
              env_root_dir=env_root_dir,
              pip_requirements_override=pip_requirements_override,
          )
  
      elif self._env_manager == _EnvManager.LOCAL:
          raise Exception(
              "Prepare env should not be called with local env manager!"
          )
      else:
          raise Exception(
              f"Unexpected env manager value '{self._env_manager}'"
          )
  
      if self._install_mlflow:
          self._environment.execute(_get_pip_install_mlflow())
      else:
          self._environment.execute('python -c ""')
  
      return self._environment
  
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 2 for calling the PyFuncBackend obj's underlying member method code with example usage: obj.prepare_env(model_uri, capture_output, pip_requirements_override) and returns: self, self, env_root_dir