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unit test for KB serialization
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@ -442,11 +442,11 @@ if __name__ == "__main__":
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print()
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print("dumping kb1")
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print(KB_FILE, type(KB_FILE))
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kb1.dump(KB_FILE)
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# STEP 4 : read KB back in from file
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nlp3 = spacy.load('en_core_web_sm')
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kb3 = KnowledgeBase(vocab=my_vocab)
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print("loading kb3")
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@ -19,6 +19,7 @@ cdef class Candidate:
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cdef readonly KnowledgeBase kb
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cdef hash_t entity_hash
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cdef float entity_freq
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cdef hash_t alias_hash
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cdef float prior_prob
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@ -26,9 +26,10 @@ from libcpp.vector cimport vector
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cdef class Candidate:
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def __init__(self, KnowledgeBase kb, entity_hash, alias_hash, prior_prob):
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def __init__(self, KnowledgeBase kb, entity_hash, entity_freq, alias_hash, prior_prob):
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self.kb = kb
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self.entity_hash = entity_hash
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self.entity_freq = entity_freq
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self.alias_hash = alias_hash
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self.prior_prob = prior_prob
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@ -52,6 +53,10 @@ cdef class Candidate:
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"""RETURNS (unicode): ID of the original alias"""
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return self.kb.vocab.strings[self.alias_hash]
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@property
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def entity_freq(self):
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return self.entity_freq
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@property
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def prior_prob(self):
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return self.prior_prob
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@ -156,6 +161,7 @@ cdef class KnowledgeBase:
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return [Candidate(kb=self,
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entity_hash=self._entries[entry_index].entity_hash,
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entity_freq=self._entries[entry_index].prob,
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alias_hash=alias_hash,
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prior_prob=prob)
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for (entry_index, prob) in zip(alias_entry.entry_indices, alias_entry.probs)
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64
spacy/tests/serialize/test_serialize_kb.py
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64
spacy/tests/serialize/test_serialize_kb.py
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@ -0,0 +1,64 @@
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from ..util import make_tempdir
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from ...util import ensure_path
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from spacy.kb import KnowledgeBase
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def test_serialize_kb_disk(en_vocab):
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kb1 = KnowledgeBase(vocab=en_vocab)
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kb1.add_entity(entity="Q53", prob=0.33)
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kb1.add_entity(entity="Q17", prob=0.2)
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kb1.add_entity(entity="Q007", prob=0.7)
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kb1.add_entity(entity="Q44", prob=0.4)
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kb1.add_alias(alias="double07", entities=["Q17", "Q007"], probabilities=[0.1, 0.9])
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kb1.add_alias(alias="guy", entities=["Q53", "Q007", "Q17", "Q44"], probabilities=[0.3, 0.3, 0.2, 0.1])
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kb1.add_alias(alias="random", entities=["Q007"], probabilities=[1.0])
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# baseline assertions
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_check_kb(kb1)
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# dumping to file & loading back in
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with make_tempdir() as d:
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dir_path = ensure_path(d)
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if not dir_path.exists():
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dir_path.mkdir()
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file_path = dir_path / "kb"
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print(file_path, type(file_path))
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kb1.dump(str(file_path))
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kb2 = KnowledgeBase(vocab=en_vocab)
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kb2.load_bulk(str(file_path))
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# final assertions
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_check_kb(kb2)
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def _check_kb(kb):
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# check entities
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assert kb.get_size_entities() == 4
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for entity_string in ["Q53", "Q17", "Q007", "Q44"]:
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assert entity_string in kb.get_entity_strings()
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for entity_string in ["", "Q0"]:
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assert entity_string not in kb.get_entity_strings()
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# check aliases
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assert kb.get_size_aliases() == 3
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for alias_string in ["double07", "guy", "random"]:
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assert alias_string in kb.get_alias_strings()
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for alias_string in ["nothingness", "", "randomnoise"]:
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assert alias_string not in kb.get_alias_strings()
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# check candidates & probabilities
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candidates = sorted(kb.get_candidates("double07"), key=lambda x: x.entity_)
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assert len(candidates) == 2
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assert candidates[0].entity_ == "Q007"
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assert candidates[0].entity_freq < 0.701 and candidates[0].entity_freq > 0.699
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assert candidates[0].alias_ == "double07"
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assert candidates[0].prior_prob < 0.901 and candidates[0].prior_prob > 0.899
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assert candidates[1].entity_ == "Q17"
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assert candidates[1].entity_freq < 0.201 and candidates[1].entity_freq > 0.199
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assert candidates[1].alias_ == "double07"
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assert candidates[1].prior_prob < 0.101 and candidates[1].prior_prob > 0.099
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