code: def get_cache_path(
      self,
      dataset: Optional[CacheableDataset],
      key: str,
      tag: str,
      ext: Optional[str] = None,
  ) -> str:
      if self._cache_dir is None and dataset is not None:
          # Use the input dataset filename (minus the extension) as the cache path
          stem = dataset.get_cache_path()
      else:
          # To avoid collisions across different directories, we use the unique checksum
          # as the cache path
          stem = alphanum(key)
  
      ext = ext or self.data_format
      cache_fname = f"{stem}.{tag}.{ext}"
      return os.path.join(
          self.get_cache_directory(dataset), cache_fname
      )
  
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 4 for calling the CacheManager obj's underlying member method code with example usage: obj.get_cache_path(dataset, key, tag, ext) and returns: os