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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
#
# 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.
import six
import types
from difflib import SequenceMatcher
from . import backbone
def get_architectures():
"""
get all of model architectures
"""
names = []
for k, v in backbone.__dict__.items():
if isinstance(v, (types.FunctionType, six.class_types)):
names.append(k)
return names
def get_blacklist_model_in_static_mode():
from ppcls.arch.backbone import distilled_vision_transformer
from ppcls.arch.backbone import vision_transformer
blacklist = distilled_vision_transformer.__all__ + vision_transformer.__all__
return blacklist
def similar_architectures(name='', names=[], thresh=0.1, topk=10):
"""
inferred similar architectures
"""
scores = []
for idx, n in enumerate(names):
if n.startswith('__'):
continue
score = SequenceMatcher(None, n.lower(), name.lower()).quick_ratio()
if score > thresh:
scores.append((idx, score))
scores.sort(key=lambda x: x[1], reverse=True)
similar_names = [names[s[0]] for s in scores[:min(topk, len(scores))]]
return similar_names