code: def get_test_configurable_parameters(
      dataset_path: Optional[str] = None,
      model_name: Optional[str] = None,
      config_path: Optional[Union[Path, str]] = None,
      weight_file: Optional[str] = None,
      config_filename: Optional[str] = "config",
      config_file_extension: Optional[str] = "yaml",
  ) -> Union[DictConfig, ListConfig]:
      """Get configurable parameters for testing.
  
      Args:
          datset_path: Optional[Path]: Path to dataset
          model_name: Optional[str]:  (Default value = None)
          config_path: Optional[Union[Path, str]]:  (Default value = None)
          weight_file: Path to the weight file
          config_filename: Optional[str]:  (Default value = "config")
          config_file_extension: Optional[str]:  (Default value = "yaml")
  
      Returns:
          Union[DictConfig, ListConfig]: Configurable parameters in DictConfig object.
      """
  
      config = get_configurable_parameters(
          model_name,
          config_path,
          weight_file,
          config_filename,
          config_file_extension,
      )
  
      # Update path to match the dataset path in the test image/runner
      config.dataset.path = (
          get_dataset_path() if dataset_path is None else dataset_path
      )
  
      return config
  
imports: from pathlib import Path
  from typing import Optional, Union
  from omegaconf import DictConfig, ListConfig
  from anomalib.config import get_configurable_parameters
  from .dataset import get_dataset_path
label_desc: Use image node_id 1 for calling a global function with example usage: get_test_configurable_parameters(dataset_path, model_name, config_path, weight_file, config_filename, config_file_extension) and returns: config