3 ms·

What's the difference to using joblibs Memory class similar to this implementation: https://github.com/stanfordnlp/dspy/blob/main/dsp/modules/cache_utils.py ht

• khaledh 3y ago
  I was going to mention this as well. It's fairly similar: memory = joblib.memory.Memory(...) @memory.cache def slow_func(...): ...
  • rassibassi 3y ago
    The diskcache docs state: """ Caching Libraries joblib.Memory provides caching functions and works by explicitly saving the inputs and outputs to files. It is designed to work with non-hashable and potentially large input and output data types such as numpy arrays. """ From https://pypi.org/project/diskcache/ https://pypi.org/project/diskcache/
    • williamzeng0 3y ago
      This is great! I see it also supports an 'ignore' parameter.