NPYCache

class hybrid_learning.datasets.caching.NPYCache(cache_root=None)

Bases: FileCache

File cache that uses numpy saving and loading mechanism to cache torch.Tensor objects. Cannot use sparse tensor representation for saving for now. For further details see super class.

Public Data Attributes:

FILE_ENDING

The file ending to append to descriptors to get the file path.

Inherited from : py: class:FileCache

FILE_ENDING

The file ending to append to descriptors to get the file path.

Public Methods:

put_file(filepath, obj)	Save obj to filepath using numpy.save().
load_file(filepath)	Load obj from filepath using numpy.load().

Inherited from : py: class:FileCache

put(descriptor, obj)	Store obj under the cache root using put_file().
load(descriptor)	Load object from file descriptor + FILE_ENDING under cache root.
clear()	Remove all files from cache root.
descriptors()	Provide paths of all cached files with ending stripped and relative to cache root.
descriptor_to_fp(descriptor)	Return the file path of the cache file for a given descriptor.
put_file(filepath, obj)	Save obj to filepath using numpy.save().
load_file(filepath)	Load obj from filepath using numpy.load().

Inherited from : py: class:Cache

put(descriptor, obj)	Store obj under the cache root using put_file().
load(descriptor)	Load object from file descriptor + FILE_ENDING under cache root.
put_batch(descriptors, objs)	Store a batch of objs in this cache using according descriptors.
load_batch(descriptors[, return_none_if])	Load a batch of objects.
clear()	Remove all files from cache root.
descriptors()	Provide paths of all cached files with ending stripped and relative to cache root.
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:

Inherited from : py: class:FileCache

__init__([cache_root])	Init.
__repr__()	Return repr(self).

Inherited from : py: class:Cache

__repr__()	Return repr(self).
__add__(other)	Return a (cascaded) cache which will first lookup self then other with default sync mode.
__radd__(other)	Return a (cascaded) cache which will first lookup other then self with default sync mode.

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Parameters

cache_root (str) –

load_file(filepath)

Load obj from filepath using numpy.load().

Parameters

filepath (str) –

Return type

Tensor

put_file(filepath, obj)

Save obj to filepath using numpy.save().

Parameters

• filepath (str) –

• obj (Tensor) –

FILE_ENDING = '.npy'

The file ending to append to descriptors to get the file path. See FileCache.descriptor_to_fp(). This is the standard for numpy.save().