def load_model(self):
"""
Load a btree index from the configured cache element. This only occurs
if there is a cache element configured and there are bytes there to
read.
"""
with self._model_lock:
if self.cache_element and not self.cache_element.is_empty():
self._log.debug("Loading model from cache: %s",
self.cache_element)
buff = BytesIO(self.cache_element.get_bytes())
# noinspection PyTypeChecker
with np.load(buff, allow_pickle=True) as cache:
tail = tuple(cache['tail'])
s = [
cache['data_arr'], cache['idx_array_arr'],
cache['node_data_arr'], cache['node_bounds_arr']
]
s.extend(tail)
s[11] = DistanceMetric.get_metric('hamming')
s = tuple(s)
# noinspection PyTypeChecker
#: :type: sklearn.neighbors.BallTree
self.bt = BallTree.__new__(BallTree)
self.bt.__setstate__(s)
self._log.debug("Loading mode: Done")
def load_model(self):
if self.file_cache and os.path.isfile(self.file_cache):
self._log.debug("Loading mode: %s", self.file_cache)
with numpy.load(self.file_cache) as cache:
tail = tuple(cache['tail'])
s = (cache['data_arr'], cache['idx_array_arr'],
cache['node_data_arr'], cache['node_bounds_arr']) +\
tail + (DistanceMetric.get_metric('hamming'),)
#: :type: sklearn.neighbors.BallTree
self.bt = BallTree.__new__(BallTree)
self.bt.__setstate__(s)
self._log.debug("Loading mode: Done")
def load_model(self):
if self.file_cache and os.path.isfile(self.file_cache):
self._log.debug("Loading mode: %s", self.file_cache)
with numpy.load(self.file_cache) as cache:
tail = tuple(cache['tail'])
s = (cache['data_arr'], cache['idx_array_arr'],
cache['node_data_arr'], cache['node_bounds_arr']) +\
tail + (DistanceMetric.get_metric('hamming'),)
#: :type: sklearn.neighbors.BallTree
self.bt = BallTree.__new__(BallTree)
self.bt.__setstate__(s)
self._log.debug("Loading mode: Done")
def load_model(self):
"""
Load a btree index from the configured cache element. This only occurs
if there is a cache element configured and there are bytes there to
read.
"""
if self.cache_element and not self.cache_element.is_empty():
self._log.debug("Loading model from cache: %s", self.cache_element)
buff = StringIO(self.cache_element.get_bytes())
with numpy.load(buff) as cache:
tail = tuple(cache['tail'])
s = (cache['data_arr'], cache['idx_array_arr'],
cache['node_data_arr'], cache['node_bounds_arr']) +\
tail + (DistanceMetric.get_metric('hamming'),)
#: :type: sklearn.neighbors.BallTree
self.bt = BallTree.__new__(BallTree)
self.bt.__setstate__(s)
self._log.debug("Loading mode: Done")
