code: def test_get_or_create_conda_env_capture_output_mode(tmp_path):
      conda_yaml_file = tmp_path / "conda.yaml"
      conda_yaml_file.write_text(
          """
  channels:
  - conda-forge
  dependencies:
  - pip:
    - scikit-learn==99.99.99
  """
      )
      with pytest.raises(
          ShellCommandException,
          match="Could not find a version that satisfies the requirement scikit-learn==99.99.99",
      ):
          get_or_create_conda_env(
              str(conda_yaml_file), capture_output=True
          )
  
imports: import json
  import os
  import shutil
  import subprocess
  import uuid
  from unittest import mock
  import git
  import pytest
  import yaml
  from databricks_cli.configure.provider import DatabricksConfig
  import mlflow
  from mlflow import MlflowClient
  from mlflow.entities import RunStatus, SourceType, ViewType
  from mlflow.environment_variables import MLFLOW_CONDA_CREATE_ENV_CMD, MLFLOW_CONDA_HOME
  from mlflow.exceptions import ExecutionException, MlflowException
  from mlflow.projects import _parse_kubernetes_config, _resolve_experiment_id
  from mlflow.store.tracking.file_store import FileStore
  from mlflow.utils import PYTHON_VERSION
  from mlflow.utils.conda import CONDA_EXE, get_or_create_conda_env
  from mlflow.utils.mlflow_tags import LEGACY_MLFLOW_GIT_BRANCH_NAME, LEGACY_MLFLOW_GIT_REPO_URL, MLFLOW_GIT_BRANCH, MLFLOW_GIT_REPO_URL, MLFLOW_PARENT_RUN_ID, MLFLOW_PROJECT_BACKEND, MLFLOW_PROJECT_ENTRY_POINT, MLFLOW_PROJECT_ENV, MLFLOW_SOURCE_NAME, MLFLOW_SOURCE_TYPE, MLFLOW_USER
  from mlflow.utils.process import ShellCommandException
  from tests.projects.utils import TEST_PROJECT_DIR, TEST_PROJECT_NAME, validate_exit_status
label_desc: Use image node_id 25 for calling a global function with example usage: test_get_or_create_conda_env_capture_output_mode(tmp_path) without return types