def get_retriever(cls, args):
selector = args['retriever_selector']
if str(selector) in cls._selector_to_dr:
dr = cls._selector_to_dr[str(selector)]
else:
dr = Retriever.objects.get(**selector)
cls._selector_to_dr[str(selector)] = dr
retriever_pk = dr.pk
if retriever_pk not in cls._visual_retriever:
cls._retriever_object[retriever_pk] = dr
if dr.algorithm == Retriever.EXACT and dr.approximator_shasum and dr.approximator_shasum.strip(
):
approximator, da = Approximators.get_trained_model({
"trainedmodel_selector": {
"shasum": dr.approximator_shasum
}
})
da.ensure()
approximator.load()
cls._visual_retriever[
retriever_pk] = retriever.SimpleRetriever(
name=dr.name, approximator=approximator)
elif dr.algorithm == Retriever.EXACT:
cls._visual_retriever[
retriever_pk] = retriever.SimpleRetriever(name=dr.name)
elif dr.algorithm == Retriever.FAISS and dr.approximator_shasum is None:
_, di = Indexers.get_trained_model(
{"trainedmodel_selector": {
"shasum": dr.indexer_shasum
}})
cls._visual_retriever[
retriever_pk] = retriever.FaissFlatRetriever(
name=dr.name, components=di.arguments['components'])
elif dr.algorithm == Retriever.FAISS:
approximator, da = Approximators.get_trained_model({
"trainedmodel_selector": {
"shasum": dr.approximator_shasum
}
})
da.ensure()
approximator.load()
cls._visual_retriever[
retriever_pk] = retriever.FaissApproximateRetriever(
name=dr.name, approximator=approximator)
elif dr.algorithm == Retriever.LOPQ:
approximator, da = Approximators.get_trained_model({
"trainedmodel_selector": {
"shasum": dr.approximator_shasum
}
})
da.ensure()
approximator.load()
cls._visual_retriever[retriever_pk] = retriever.LOPQRetriever(
name=dr.name, approximator=approximator)
else:
raise ValueError("{} not valid retriever algorithm".format(
dr.algorithm))
return cls._visual_retriever[retriever_pk], cls._retriever_object[
retriever_pk]
def get_retriever(cls, retriever_pk):
if retriever_pk not in cls._visual_retriever:
dr = Retriever.objects.get(pk=retriever_pk)
cls._retriever_object[retriever_pk] = dr
if dr.algorithm == Retriever.EXACT and dr.approximator_shasum and dr.approximator_shasum.strip():
approximator, da = Approximators.get_approximator_by_shasum(dr.approximator_shasum)
da.ensure()
approximator.load()
cls._visual_retriever[retriever_pk] = retriever.BaseRetriever(name=dr.name, approximator=approximator)
elif dr.algorithm == Retriever.EXACT:
cls._visual_retriever[retriever_pk] = retriever.BaseRetriever(name=dr.name)
elif dr.algorithm == Retriever.FAISS and dr.approximator_shasum is None:
di = Indexers.get_indexer_by_shasum(dr.indexer_shasum)
cls._visual_retriever[retriever_pk] = retriever.FaissFlatRetriever(name=dr.name,
components=di.arguments[
'components'])
elif dr.algorithm == Retriever.FAISS:
approximator, da = Approximators.get_approximator_by_shasum(dr.approximator_shasum)
da.ensure()
approximator.load()
cls._visual_retriever[retriever_pk] = retriever.FaissApproximateRetriever(name=dr.name,
approximator=approximator)
elif dr.algorithm == Retriever.LOPQ:
approximator, da = Approximators.get_approximator_by_shasum(dr.approximator_shasum)
da.ensure()
approximator.load()
cls._visual_retriever[retriever_pk] = retriever.LOPQRetriever(name=dr.name,
approximator=approximator)
else:
raise ValueError("{} not valid retriever algorithm".format(dr.algorithm))
return cls._visual_retriever[retriever_pk], cls._retriever_object[retriever_pk]