code: def _execute_in_virtualenv(
      activate_cmd,
      command,
      install_mlflow,
      command_env=None,
      synchronous=True,
      capture_output=False,
      env_root_dir=None,
      **kwargs,
  ):
      """Runs a command in a specified virtualenv environment.
  
      Args:
          activate_cmd: Command to activate the virtualenv environment.
          command: Command to run in the virtualenv environment.
          install_mlflow: Flag to determine whether to install mlflow in the virtualenv
              environment.
          command_env: Environment variables passed to a process running the command.
          synchronous: Set the `synchronous` argument when calling `_exec_cmd`.
          capture_output: Set the `capture_output` argument when calling `_exec_cmd`.
          env_root_dir: See doc of PyFuncBackend constructor argument `env_root_dir`.
          kwargs: Set the `kwargs` argument when calling `_exec_cmd`.
  
      """
      if command_env is None:
          command_env = os.environ.copy()
  
      if env_root_dir is not None:
          command_env = {
              **command_env,
              **_get_virtualenv_extra_env_vars(env_root_dir),
          }
  
      pre_command = [activate_cmd]
      if install_mlflow:
          pre_command.append(_get_pip_install_mlflow())
  
      cmd = _join_commands(*pre_command, command)
      _logger.info("Running command: %s", " ".join(cmd))
      return _exec_cmd(
          cmd,
          capture_output=capture_output,
          env=command_env,
          synchronous=synchronous,
          **kwargs,
      )
  
imports: import logging
  import os
  import re
  import shutil
  import sys
  import tempfile
  import uuid
  from pathlib import Path
  from packaging.version import Version
  import mlflow
  from mlflow.environment_variables import MLFLOW_ENV_ROOT
  from mlflow.exceptions import MlflowException
  from mlflow.models.model import MLMODEL_FILE_NAME, Model
  from mlflow.utils.conda import _PIP_CACHE_DIR
  from mlflow.utils.databricks_utils import is_in_databricks_runtime
  from mlflow.utils.environment import _CONDA_ENV_FILE_NAME, _PYTHON_ENV_FILE_NAME, _REQUIREMENTS_FILE_NAME, _get_mlflow_env_name, _get_pip_install_mlflow, _PythonEnv
  from mlflow.utils.file_utils import remove_on_error
  from mlflow.utils.process import _IS_UNIX, _exec_cmd, _join_commands
  from mlflow.utils.requirements_utils import _parse_requirements
label_desc: Use image node_id 17 for calling a global function with example usage: _execute_in_virtualenv(activate_cmd, command, install_mlflow, command_env, synchronous, capture_output, env_root_dir) and returns: _exec_cmd