code: def can_cache(self, skip_save_processed_input: bool) -> bool:
      return self._dataset_manager.can_cache(skip_save_processed_input)
  
imports: import logging
  import os
  from typing import Optional
  from ludwig.constants import CHECKSUM, META, TEST, TRAINING, VALIDATION
  from ludwig.data.cache.types import alphanum, CacheableDataset
  from ludwig.data.cache.util import calculate_checksum
  from ludwig.data.dataset.base import DatasetManager
  from ludwig.utils import data_utils
  from ludwig.utils.fs_utils import delete, path_exists
label_desc: Use image node_id 6 for calling the CacheManager obj's underlying member method code with example usage: obj.can_cache(skip_save_processed_input) and returns: self