sklearn.utils.Memory¶
Warning
DEPRECATED
-
class
sklearn.utils.Memory(**kwargs)[source]¶ - Attributes
- cachedir
Methods
cache(self[, func, ignore, verbose, mmap_mode])Decorates the given function func to only compute its return value for input arguments not cached on disk.
clear(self[, warn])Erase the complete cache directory.
eval(self, func, \*args, \*\*kwargs)Eval function func with arguments
*argsand**kwargs, in the context of the memory.format(self, obj[, indent])Return the formatted representation of the object.
reduce_size(self)Remove cache elements to make cache size fit in
bytes_limit.debug
warn
-
__init__(*args, **kwargs)[source]¶ DEPRECATED: deprecated in version 0.20.1 to be removed in version 0.23. Please import this functionality directly from joblib, which can be installed with: pip install joblib.
-
cache(self, func=None, ignore=None, verbose=None, mmap_mode=False)[source]¶ Decorates the given function func to only compute its return value for input arguments not cached on disk.
- Parameters
- func: callable, optional
The function to be decorated
- ignore: list of strings
A list of arguments name to ignore in the hashing
- verbose: integer, optional
The verbosity mode of the function. By default that of the memory object is used.
- mmap_mode: {None, ‘r+’, ‘r’, ‘w+’, ‘c’}, optional
The memmapping mode used when loading from cache numpy arrays. See numpy.load for the meaning of the arguments. By default that of the memory object is used.
- Returns
- decorated_func: MemorizedFunc object
The returned object is a MemorizedFunc object, that is callable (behaves like a function), but offers extra methods for cache lookup and management. See the documentation for
joblib.memory.MemorizedFunc.