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Added 3.4.1 tests
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import unittest
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import nlu
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import sys
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class Test341(unittest.TestCase):
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def test_341_models(self):
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import pandas as pd
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te = [
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'en.embed.longformer.clinical',
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'en.classify.emotion.bert',
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'en.classify.typos.distilbert',
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'de.classify.news_sentiment.bert',
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'xx.embed.albert.indic',
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'xx.ner.masakhaner',
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'fr.embed.word2vec_wiki_1000',
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'fr.embed.word2vec_wac_200',
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'fr.embed.w2v_cc_300d',
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'vi.embed.distilbert.cased',
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]
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fails = []
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for t in te:
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try:
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print(f'Testing spell = {t}')
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pipe = nlu.load(t, verbose=True)
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df = pipe.predict(['Peter love pancaces. I hate Mondays', 'I love Fridays'])
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for c in df.columns: print(df[c])
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except Exception as err:
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print(f'Failure for spell = {t} ', err)
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e = sys.exc_info()
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print(e[0])
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print(e[1])
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fails.append(t)
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fail_string = "\n".join(fails)
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print(f'Done testing, failures = {fail_string}')
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if len(fails) > 0:
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raise Exception("Not all new spells completed successfully")
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def test_341_HC_models(self):
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import tests.secrets as sct
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SPARK_NLP_LICENSE = sct.SPARK_NLP_LICENSE
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AWS_ACCESS_KEY_ID = sct.AWS_ACCESS_KEY_ID
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AWS_SECRET_ACCESS_KEY = sct.AWS_SECRET_ACCESS_KEY
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JSL_SECRET = sct.JSL_SECRET
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nlu.auth(SPARK_NLP_LICENSE, AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, JSL_SECRET)
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te = [
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'en.med_ner.supplement_clinical',
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'en.resolve.rxnorm.augmented_re',
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'en.classify.gender.seq_biobert',
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'es.embed.sciwiki_300d',
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'en.classify.ade.seq_biobert',
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'en.classify.pico.seq_biobert',
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'en.classify.ade.seq_distilbert',
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'es.med_ner.deid.generic',
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'es.med_ner.deid.subentity',
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'en.relation.temporal_events_clinical',
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'en.relation.adverse_drug_events.clinical',
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'en.relation.adverse_drug_events.clinical.biobert',
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]
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sample_texts = ["""
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Antonio Pérez Juan, nacido en Cadiz, España. Aún no estaba vacunado, se infectó con Covid-19 el dia 14/03/2020 y tuvo que ir al Hospital. Fue tratado con anticuerpos monoclonales en la Clinica San Carlos..
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""",
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"""
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Datos del paciente. Nombre: Jose . Apellidos: Aranda Martinez. NHC: 2748903. NASS: 26 37482910.
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""",
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"""The patient was given metformin 500 mg, 2.5 mg of coumadin and then ibuprofen""",
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"""he patient was given metformin 400 mg, coumadin 5 mg, coumadin, amlodipine 10 MG""",
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"""To compare the results of recording enamel opacities using the TF and modified DDE indices.""",
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"""I felt a bit drowsy and had blurred vision after taking Aspirin.""",
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]
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fails = []
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succs = []
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for t in te:
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try:
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print(f'Testing spell = {t}')
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pipe = nlu.load(t, verbose=True)
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df = pipe.predict(sample_texts, drop_irrelevant_cols=False, metadata=True, )
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print(df.columns)
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for c in df.columns:
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print(df[c])
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succs.append(t)
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except Exception as err:
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print(f'Failure for spell = {t} ', err)
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fails.append(t)
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break
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fail_string = '\n'.join(fails)
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succ_string = '\n'.join(succs)
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print(f'Done testing, failures = {fail_string}')
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print(f'Done testing, successes = {succ_string}')
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if len(fails) > 0:
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raise Exception("Not all new spells completed successfully")
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if __name__ == '__main__':
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unittest.main()

tests/release_tests/341_release/__init__.py

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