def cache_manager(mocker, test_data):
mocker.patch.object(CacheDataManager, "read_data_cache", return_value=test_data.data)
cache = CacheManager()
return cache
def get_cache_manager(self):
return CacheManager()
- Cross-language (**Python**, **Lua/Torch7**, **Matlab**).
- Easily extensible to other languages that support ``HDF5`` files format.
- Concurrent/parallel data access thanks to ``HDF5``.
- Contains a diverse (and growing!) list of popular datasets for machine-, deep-learning tasks
(*object detection*, *action recognition*, *human pose estimation*, etc.)
"""
import pkg_resources
# API methods
from dbcollection.core.api.download import download
from dbcollection.core.api.process import process
from dbcollection.core.api.load import load
from dbcollection.core.api.add import add
from dbcollection.core.api.remove import remove
from dbcollection.core.api.cache import cache
from dbcollection.core.api.info import info
from dbcollection.core.api.metadata import fetch_list_datasets
# load the cache file
from dbcollection.core.manager import CacheManager
cache_manager = CacheManager()
# package version
__version__ = pkg_resources.get_distribution('dbcollection').version
# load information about the available datasets for download
available_datasets_list = fetch_list_datasets()