CacheDict
- class hybrid_learning.datasets.caching.CacheDict(cache_dict, return_none_if='any')[source]
Bases:
CacheTupleCache the values of dicts using different caches. Under the hood this is a
CacheTuplematching keys to caches.Public Data Attributes:
The dictionary of caches used.
Public Methods:
load(descriptor)Load a cached dict.
put(descriptor, obj)Cache a dict.
Inherited from : py: class:CacheTuple
load(descriptor)Load a cached dict.
put(descriptor, obj)Cache a dict.
clear()Clear all caches in the tuple.
descriptors()Return all descriptors that occur in any of the given caches.
Inherited from : py: class:Cache
put(descriptor, obj)Cache a dict.
load(descriptor)Load a cached dict.
put_batch(descriptors, objs)Store a batch of
objsin this cache using accordingdescriptors.load_batch(descriptors[, return_none_if])Load a batch of objects.
clear()Clear all caches in the tuple.
descriptors()Return all descriptors that occur in any of the given caches.
as_dict()Return a dict with all cached descriptors and objects.
wrap(getitem[, descriptor_map])Add this cache to the deterministic function
getitem(which should have no side effects).Special Methods:
__init__(cache_dict[, return_none_if])Init.
__repr__()Return repr(self).
Inherited from : py: class:CacheTuple
__init__(cache_dict[, return_none_if])Init.
__repr__()Return repr(self).
Inherited from : py: class:Cache
__repr__()Return repr(self).
__add__(other)Return a (cascaded) cache which will first lookup
selfthenotherwith default sync mode.__radd__(other)Return a (cascaded) cache which will first lookup
otherthenselfwith default sync mode.