What's the difference to using joblibs Memory class similar to this implementation:
https://github.com/stanfordnlp/dspy/blob/main/dsp/modules/ca...
https://github.com/stanfordnlp/dspy/blob/main/dsp/modules/ca...
memory = joblib.memory.Memory(...)
@memory.cache
def slow_func(...):
...""" 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.