def test_chunk_embeds(self):
pdf = get_sample_pdf()
res = nlu.load('embed_chunk',
verbose=True).predict("What a wondful day!")
print(res)
res = nlu.load('en.embed_chunk', verbose=True).predict(pdf)
print(res)
def test_ngram(self):
pdf = get_sample_pdf()
# res = nlu.load('ngram',verbose=True).predict(pdf )
pipe = nlu.load('ngram',verbose=True)
# print(res['ngrams'])
print("PIPE", pipe)
res = nlu.load('en.ngram',verbose=True).predict(pdf)
print(res['ngrams'])
def test_pdf_column_prediction(self):
pdf = get_sample_pdf()
res = nlu.load('sentiment',
verbose=True).predict(pdf['text'],
output_level='sentence')
# res = nlu.load('bert',verbose=True).predict('@Your life is the sum of a remainder of an unbalanced equation inherent to the programming of the matrix. You are the eventuality of an anomaly, which despite my sincerest efforts I have been unable to eliminate from what is otherwise a harmony of mathematical precision. While it remains a burden assiduously avoided, it is not unexpected, and thus not beyond a measure of control. Which has led you, inexorably, here.', output_level='sentence')
print(res)
print(res['sentiment'])
print(res.dtypes)
def test_xx_bert(self):
pdf = get_sample_pdf()
res = nlu.load('xx.embed_sentence',verbose=True).predict(pdf )
print(res)
def test_e2e(self):
pdf = get_sample_pdf()
res = nlu.load('en.classify.e2e',verbose=True).predict(pdf )
print(res)
def test_embed_sentence_bert(self):
pdf = get_sample_pdf()
res = nlu.load('en.embed_sentence.biobert.pubmed_base_cased',verbose=True).predict(pdf )
print(res)
def test_embed_sentence_bert(self):
pdf = get_sample_pdf()
res = nlu.load('en.embed_sentence.small_bert_L2_128',verbose=True).predict(pdf )
print(res)
def test_electra(self):
pdf = get_sample_pdf()
res = nlu.load('en.embed.electra',verbose=True).predict(pdf )
print(res)
def test_auto_sentence_embed_elmo(self): # TODO WIP
pdf = get_sample_pdf()
res = nlu.load('embed_sentence.elmo',verbose=True).predict(pdf )
print(res)
def test_text_matcher(self):
pdf = get_sample_pdf()
res = nlu.load('match.text',verbose=True).predict(pdf )
print(res)
def test_norm(self):
pdf = get_sample_pdf()
res = nlu.load('norm',verbose=True).predict(pdf, output_positions=True )
print(res)
def test_stem(self):
pdf = get_sample_pdf()
res = nlu.load('stem',verbose=True).predict(pdf )
print(res)
res = nlu.load('en.stem',verbose=True).predict(pdf)
print(res)
