def test_spacy_featurizer_casing(spacy_nlp):
from rasa_nlu.featurizers import spacy_featurizer
# if this starts failing for the default model, we should think about
# removing the lower casing the spacy nlp component does when it
# retrieves vectors. For compressed spacy models (e.g. models
# ending in _sm) this test will most likely fail.
td = training_data.load_data('data/examples/rasa/demo-rasa.json')
for e in td.intent_examples:
doc = spacy_nlp(e.text)
doc_capitalized = spacy_nlp(e.text.capitalize())
vecs = spacy_featurizer.features_for_doc(doc)
vecs_capitalized = spacy_featurizer.features_for_doc(doc_capitalized)
assert np.allclose(vecs, vecs_capitalized, atol=1e-5), \
"Vectors are unequal for texts '{}' and '{}'".format(
e.text, e.text.capitalize())
def test_spacy_featurizer_casing(spacy_nlp):
from rasa_nlu.featurizers import spacy_featurizer
# if this starts failing for the default model, we should think about
# removing the lower casing the spacy nlp component does when it
# retrieves vectors. For compressed spacy models (e.g. models
# ending in _sm) this test will most likely fail.
td = training_data.load_data('data/examples/rasa/demo-rasa.json')
for e in td.intent_examples:
doc = spacy_nlp(e.text)
doc_capitalized = spacy_nlp(e.text.capitalize())
vecs = spacy_featurizer.features_for_doc(doc)
vecs_capitalized = spacy_featurizer.features_for_doc(doc_capitalized)
assert np.allclose(vecs, vecs_capitalized, atol=1e-5), \
"Vectors are unequal for texts '{}' and '{}'".format(
e.text, e.text.capitalize())
def test_spacy_featurizer(sentence, expected, spacy_nlp):
from rasa_nlu.featurizers import spacy_featurizer
doc = spacy_nlp(sentence)
vecs = spacy_featurizer.features_for_doc(doc)
assert np.allclose(doc.vector[:5], expected, atol=1e-5)
assert np.allclose(vecs, doc.vector, atol=1e-5)
def test_spacy_featurizer(sentence, expected, spacy_nlp):
from rasa_nlu.featurizers import spacy_featurizer
doc = spacy_nlp(sentence)
vecs = spacy_featurizer.features_for_doc(doc)
assert np.allclose(doc.vector[:5], expected, atol=1e-5)
assert np.allclose(vecs, doc.vector, atol=1e-5)
