def __init__(self, state={}):
if 'nearest_neighbors_model' not in state:
state['nearest_neighbors_model'] = None
assert (isinstance(state['nearest_neighbors_model'],
_gl.nearest_neighbors.NearestNeighborsModel))
self.__proxy__ = _PythonProxy(state)
def __init__(self, state={}):
if 'nearest_neighbors_model' not in state:
state['nearest_neighbors_model'] = None
if state['nearest_neighbors_model'] and not isinstance(state['nearest_neighbors_model'],
_gl.nearest_neighbors._nearest_neighbors.NearestNeighborsModel):
raise TypeError("The internal nearest neighbors model for LocalOutlierFactorModel is not correct.")
self.__proxy__ = _PythonProxy(state)
def _setup(self):
"""
Sets up the model; common between __init__ and load.
"""
self.__proxy__ = _PythonProxy()
#Try importing spacy
if SpacyTransformer._nlp is None:
SpacyTransformer._nlp = _import_spacy()
def __init__(self, state={}):
if 'nearest_neighbors_model' in state:
model = state['nearest_neighbors_model']
else:
model = None
assert (isinstance(model, _gl.nearest_neighbors.NearestNeighborsModel))
if model.get("distance") == "dot_product":
raise _ToolkitError("%s is not a supported distance function for " \
"the NearestNeighborAutoTagger. Use %s " \
"instead." % ("dot_product", "cosine"))
if model.get("distance") == "transformed_dot_product":
raise _ToolkitError("%s is not a supported distance function for " \
"the NearestNeighborAutoTagger. Use %s " \
"instead." % ("transformed_dot_product", "cosine"))
self.__proxy__ = _PythonProxy(state)
def _setup(self):
self.__proxy__ = _PythonProxy()
def _setup(self):
"""
Sets stuff up.
"""
self.__proxy__ = _PythonProxy()
def __init__(self, state=None):
if state is None:
state = {}
self.__proxy__ = _PythonProxy(state)
def __init__(self, state):
self.__proxy__ = _PythonProxy(state)