from __future__ import unicode_literals

import pytest


@pytest.mark.models('en')
def test_beam_parse(EN):
    doc = EN(u'Australia is a country', disable=['ner'])
    ents = EN.entity(doc, beam_width=2)
    print(ents)

from __future__ import unicode_literals

import pytest
from ...language import Language
from ...pipeline import DependencyParser


@pytest.mark.models('en')
def test_beam_parse_en(EN):
    doc = EN(u'Australia is a country', disable=['ner'])
    ents = EN.entity(doc, beam_width=2)
    print(ents)


def test_beam_parse():
    nlp = Language()
    nlp.add_pipe(DependencyParser(nlp.vocab), name='parser')
    nlp.parser.add_label('nsubj')
    nlp.begin_training()

    doc = nlp.make_doc(u'Australia is a country')
    nlp.parser(doc, beam_width=2)

Add extra beam parsing test
Add extra beam parsing test

  from __future__ import unicode_literals
  
  import pytest
+ from ...language import Language
+ from ...pipeline import DependencyParser
  
  
  @pytest.mark.models('en')
- def test_beam_parse(EN):
+ def test_beam_parse_en(EN):
      doc = EN(u'Australia is a country', disable=['ner'])
      ents = EN.entity(doc, beam_width=2)
      print(ents)
  
+ 
+ def test_beam_parse():
+     nlp = Language()
+     nlp.add_pipe(DependencyParser(nlp.vocab), name='parser')
+     nlp.parser.add_label('nsubj')
+     nlp.begin_training()
+ 
+     doc = nlp.make_doc(u'Australia is a country')
+     nlp.parser(doc, beam_width=2)
+ 
Add extra beam parsing test
## Code Before:
from __future__ import unicode_literals

import pytest


@pytest.mark.models('en')
def test_beam_parse(EN):
    doc = EN(u'Australia is a country', disable=['ner'])
    ents = EN.entity(doc, beam_width=2)
    print(ents)

## Instruction:
Add extra beam parsing test
## Code After:
from __future__ import unicode_literals

import pytest
from ...language import Language
from ...pipeline import DependencyParser


@pytest.mark.models('en')
def test_beam_parse_en(EN):
    doc = EN(u'Australia is a country', disable=['ner'])
    ents = EN.entity(doc, beam_width=2)
    print(ents)


def test_beam_parse():
    nlp = Language()
    nlp.add_pipe(DependencyParser(nlp.vocab), name='parser')
    nlp.parser.add_label('nsubj')
    nlp.begin_training()

    doc = nlp.make_doc(u'Australia is a country')
    nlp.parser(doc, beam_width=2)
