class CacheManager(object):
"""The librosa cache manager class wraps joblib.Memory
with a __call__ attribute, so that it may act as a function.
Additionally, it provides a caching level filter, so that
different functions can be cached or not depending on the user's
preference for speed vs. storage usage.
"""
def __init__(self, *args, **kwargs):
level = kwargs.pop("level", 10)
# Initialize the memory object
self.memory = Memory(*args, **kwargs)
# The level parameter controls which data we cache
# smaller numbers mean less caching
self.level = level
def __call__(self, level):
"""Example usage:
@cache(level=2)
def semi_important_function(some_arguments):
...
"""
def wrapper(function):
"""Decorator function. Adds an input/output cache to
the specified function."""
if self.memory.location is not None and self.level >= level:
return _decorator_apply(self.memory.cache, function)
else:
return function
return wrapper
def clear(self, *args, **kwargs):
return self.memory.clear(*args, **kwargs)
def eval(self, *args, **kwargs):
return self.memory.eval(*args, **kwargs)
def format(self, *args, **kwargs):
return self.memory.format(*args, **kwargs)
def reduce_size(self, *args, **kwargs):
return self.memory.reduce_size(*args, **kwargs)
def warn(self, *args, **kwargs):
return self.memory.warn(*args, **kwargs)
class CacheManager(object):
'''The librosa cache manager class wraps joblib.Memory
with a __call__ attribute, so that it may act as a function.
Additionally, it provides a caching level filter, so that
different functions can be cached or not depending on the user's
preference for speed vs. storage usage.
'''
def __init__(self, *args, **kwargs):
level = kwargs.pop('level', 10)
# Initialize the memory object
self.memory = Memory(*args, **kwargs)
# The level parameter controls which data we cache
# smaller numbers mean less caching
self.level = level
def __call__(self, level):
'''Example usage:
@cache(level=2)
def semi_important_function(some_arguments):
...
'''
def wrapper(function):
'''Decorator function. Adds an input/output cache to
the specified function.'''
from decorator import FunctionMaker
def decorator_apply(dec, func):
"""Decorate a function by preserving the signature even if dec
is not a signature-preserving decorator.
This recipe is derived from
http://micheles.googlecode.com/hg/decorator/documentation.html#id14
"""
return FunctionMaker.create(func,
'return decorated(%(signature)s)',
dict(decorated=dec(func)),
__wrapped__=func)
if self.memory.location is not None and self.level >= level:
return decorator_apply(self.memory.cache, function)
else:
return function
return wrapper
def clear(self, *args, **kwargs):
return self.memory.clear(*args, **kwargs)
def eval(self, *args, **kwargs):
return self.memory.eval(*args, **kwargs)
def format(self, *args, **kwargs):
return self.memory.format(*args, **kwargs)
def reduce_size(self, *args, **kwargs):
return self.memory.reduce_size(*args, **kwargs)
def warn(self, *args, **kwargs):
return self.memory.warn(*args, **kwargs)
class CacheManager(object):
'''The librosa cache manager class wraps joblib.Memory
with a __call__ attribute, so that it may act as a function.
Additionally, it provides a caching level filter, so that
different functions can be cached or not depending on the user's
preference for speed vs. storage usage.
'''
def __init__(self, *args, **kwargs):
level = kwargs.pop('level', 10)
# Initialize the memory object
self.memory = Memory(*args, **kwargs)
# The level parameter controls which data we cache
# smaller numbers mean less caching
self.level = level
def __call__(self, level):
'''Example usage:
@cache(level=2)
def semi_important_function(some_arguments):
...
'''
def wrapper(function):
'''Decorator function. Adds an input/output cache to
the specified function.'''
from decorator import FunctionMaker
def decorator_apply(dec, func):
"""Decorate a function by preserving the signature even if dec
is not a signature-preserving decorator.
This recipe is derived from
http://micheles.googlecode.com/hg/decorator/documentation.html#id14
"""
return FunctionMaker.create(
func, 'return decorated(%(signature)s)',
dict(decorated=dec(func)), __wrapped__=func)
if self.memory.location is not None and self.level >= level:
return decorator_apply(self.memory.cache, function)
else:
return function
return wrapper
def clear(self, *args, **kwargs):
return self.memory.clear(*args, **kwargs)
def eval(self, *args, **kwargs):
return self.memory.eval(*args, **kwargs)
def format(self, *args, **kwargs):
return self.memory.format(*args, **kwargs)
def reduce_size(self, *args, **kwargs):
return self.memory.reduce_size(*args, **kwargs)
def warn(self, *args, **kwargs):
return self.memory.warn(*args, **kwargs)