code: def get_mock_init_trainer_params(
      overrides: Optional[Dict[str, Any]] = None,
  ) -> Callable[..., Dict[str, Any]]:
      """
      Order of trainer_params setting in unit test:
        - First call original function, which sets params from config
        - Then override some params to disable logger and checkpoint
        - Apply any test-specific overrides.
      """
  
      def mock_init_trainer_params(
          original: Callable[..., Dict[str, Any]],
      ) -> Dict[str, Any]:
          trainer_params = original()
  
          trainer_params["logger"] = False
          trainer_params["enable_checkpointing"] = False
          trainer_params["fast_dev_run"] = True
  
          if overrides:
              trainer_params.update(overrides)
  
          return trainer_params
  
      return mock_init_trainer_params
  
imports: import csv
  import os
  from functools import wraps
  from tempfile import TemporaryDirectory
  from typing import Any, Callable, Dict, List, Optional
  from unittest import mock
  import testslide
  import torch
  import torchvision.io
  from hydra import compose, initialize_config_module
  from hydra.utils import instantiate
  from omegaconf import OmegaConf
  from torchrecipes.core.base_train_app import BaseTrainApp, TrainOutput
label_desc: Use image node_id 6 for calling a global function with example usage: get_mock_init_trainer_params(overrides) and returns: mock_init_trainer_params, trainer_params