.deps/torch_harmonics/cache.py

# coding=utf-8

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import functools
from copy import deepcopy

# copying LRU cache decorator a la:
# https://stackoverflow.com/questions/54909357/how-to-get-functools-lru-cache-to-return-new-instances
def lru_cache(maxsize=20, typed=False, copy=False):
    """
    Least Recently Used (LRU) cache decorator with optional deep copying.
    
    This is a wrapper around functools.lru_cache that adds the ability to return
    deep copies of cached results to prevent unintended modifications to cached objects.
    
    Parameters
    -----------
    maxsize : int, optional
        Maximum number of items to cache, by default 20
    typed : bool, optional
        Whether to cache different types separately, by default False
    copy : bool, optional
        Whether to return deep copies of cached results, by default False
        
    Returns
    -------
    function
        Decorated function with LRU caching
        
    Example
    -------
    >>> @lru_cache(maxsize=10, copy=True)
    ... def expensive_function(x):
    ...     return [x, x*2, x*3]
    """
    def decorator(f):
        cached_func = functools.lru_cache(maxsize=maxsize, typed=typed)(f)
        def wrapper(*args, **kwargs):
            res = cached_func(*args, **kwargs)
            if copy:
                return deepcopy(res)
            else:
                return res
                
        return wrapper
    return decorator