# Path: swe_pipeline.py
# def run_tagging_and_lemmatization(options, sentence, models):
#     lemmas = []
#     ud_tags_list = []
#     suc_tags_list = models["suc_tagger"].tag(sentence)
#     suc_ne_list = []
# 
#     if options.lemmatized:
#         lemmas = [
#             models["lemmatizer"].predict(token, tag)
#             for token, tag in zip(sentence, suc_tags_list)
#         ]
#         ud_tags_list = models["ud_tagger"].tag(sentence, lemmas, suc_tags_list)
# 
#         if options.ner:
#             suc_ne_list = models["suc_ne_tagger"].tag(
#                 list(zip(sentence, lemmas, suc_tags_list))
#             )
# 
#     return lemmas, ud_tags_list, suc_tags_list, suc_ne_list


from swe_pipeline import run_tagging_and_lemmatization
from unittest.mock import patch, MagicMock
import unittest

class TestRunTokenization(unittest.TestCase):
    def _default_options(
        self, tagged=False, ner=False, parsed=False,

# Path: swe_pipeline.py
# def run_tagging_and_lemmatization(options, sentence, models):
#     lemmas = []
#     ud_tags_list = []
#     suc_tags_list = models["suc_tagger"].tag(sentence)
#     suc_ne_list = []
# 
#     if options.lemmatized:
#         lemmas = [
#             models["lemmatizer"].predict(token, tag)
#             for token, tag in zip(sentence, suc_tags_list)
#         ]
#         ud_tags_list = models["ud_tagger"].tag(sentence, lemmas, suc_tags_list)
# 
#         if options.ner:
#             suc_ne_list = models["suc_ne_tagger"].tag(
#                 list(zip(sentence, lemmas, suc_tags_list))
#             )
# 
#     return lemmas, ud_tags_list, suc_tags_list, suc_ne_list


# Path: tests/test_pipeline_run_tagging.py
from swe_pipeline import run_tagging_and_lemmatization
from unittest.mock import patch, MagicMock
import unittest


class TestRunTokenization(unittest.TestCase):
    def _default_options(
        self, tagged=False, ner=False, parsed=False,

        lemmatized=False, skip_tokenization=False