# Copyright 2019-2022 The ASReview Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from asreview.utils import _model_class_from_entry_point
from asreview.utils import list_model_names
[docs]def get_feature_class(name):
"""Get class of feature extraction from string.
Arguments
---------
name: str
Name of the feature model, e.g. 'doc2vec', 'tfidf' or 'embedding-lstm'.
Returns
-------
BaseFeatureExtraction:
Class corresponding to the name.
"""
return _model_class_from_entry_point(name, "asreview.models.feature_extraction")
[docs]def get_feature_model(name, *args, random_state=None, **kwargs):
"""Get an instance of a feature extraction model from a string.
Arguments
---------
name: str
Name of the feature extraction model.
*args:
Arguments for the feature extraction model.
**kwargs:
Keyword arguments for thefeature extraction model.
Returns
-------
BaseFeatureExtraction:
Initialized instance of feature extraction algorithm.
"""
model_class = get_feature_class(name)
try:
return model_class(*args, random_state=random_state, **kwargs)
except TypeError:
return model_class(*args, **kwargs)