






"""simple docstring"""

from collections import defaultdict
from pathlib import Path

import pandas as pd
from rouge_cli import calculate_rouge_path

from utils import calculate_rouge


lowercase__					:						int												=			[
    "Prosecutor: \"No videos were used in the crash investigation\" German papers say they saw a cell phone video of the"
    " final seconds on board Flight 9525. The Germanwings co-pilot says he had a \"previous episode of severe"
    " depression\" German airline confirms it knew of Andreas Lubitz's depression years before he took control.",
    "The Palestinian Authority officially becomes the 123rd member of the International Criminal Court. The formal"
    " accession was marked with a ceremony at The Hague, in the Netherlands. The Palestinians signed the ICC's"
    " founding Rome Statute in January. Israel and the United States opposed the Palestinians' efforts to join the"
    " body.",
    "Amnesty International releases its annual report on the death penalty. The report catalogs the use of"
    " state-sanctioned killing as a punitive measure across the globe. At least 607 people were executed around the"
    " world in 2014, compared to 778 in 2013. The U.S. remains one of the worst offenders for imposing capital"
    " punishment.",
]

lowercase__					:						str												=			[
    "Marseille prosecutor says \"so far no videos were used in the crash investigation\" despite media reports ."
    " Journalists at Bild and Paris Match are \"very confident\" the video clip is real, an editor says . Andreas Lubitz"
    " had informed his Lufthansa training school of an episode of severe depression, airline says .",
    "Membership gives the ICC jurisdiction over alleged crimes committed in Palestinian territories since last June ."
    " Israel and the United States opposed the move, which could open the door to war crimes investigations against"
    " Israelis .",
    "Amnesty's annual death penalty report catalogs encouraging signs, but setbacks in numbers of those sentenced to"
    " death . Organization claims that governments around the world are using the threat of terrorism to advance"
    " executions . The number of executions worldwide has gone down by almost 22% compared with 2013, but death"
    " sentences up by 28% .",
]




def __lowercase    (							):
    snake_case_				:  List[Any]       =			calculate_rouge(SCREAMING_SNAKE_CASE_	,    SCREAMING_SNAKE_CASE_	,    bootstrap_aggregation=SCREAMING_SNAKE_CASE_	,    rouge_keys=['''rouge2''', '''rougeL''']					)
    assert isinstance(SCREAMING_SNAKE_CASE_	,    SCREAMING_SNAKE_CASE_					)
    snake_case_				:  str       =			calculate_rouge(SCREAMING_SNAKE_CASE_	,    SCREAMING_SNAKE_CASE_	,    bootstrap_aggregation=SCREAMING_SNAKE_CASE_	,    rouge_keys=['''rouge2''']					)
    assert (
        pd.DataFrame(no_aggregation['''rouge2''']					).fmeasure.mean()
        == pd.DataFrame(no_aggregation_just_ra['''rouge2''']					).fmeasure.mean()
    )




def __lowercase    (							):
    snake_case_				:  Optional[int]       =			'''rougeLsum'''
    snake_case_				:  Any       =			calculate_rouge(SCREAMING_SNAKE_CASE_	,    SCREAMING_SNAKE_CASE_	,    newline_sep=SCREAMING_SNAKE_CASE_	,    rouge_keys=[k]					)[k]
    snake_case_				:  Optional[Any]       =			calculate_rouge(SCREAMING_SNAKE_CASE_	,    SCREAMING_SNAKE_CASE_	,    newline_sep=SCREAMING_SNAKE_CASE_	,    rouge_keys=[k]					)[k]
    assert score > score_no_sep




def __lowercase    (							):
    snake_case_				:  Optional[int]       =			['''rouge1''', '''rouge2''', '''rougeL''']
    snake_case_				:  List[Any]       =			calculate_rouge(SCREAMING_SNAKE_CASE_	,    SCREAMING_SNAKE_CASE_	,    newline_sep=SCREAMING_SNAKE_CASE_	,    rouge_keys=SCREAMING_SNAKE_CASE_					)
    snake_case_				:  Any       =			calculate_rouge(SCREAMING_SNAKE_CASE_	,    SCREAMING_SNAKE_CASE_	,    newline_sep=SCREAMING_SNAKE_CASE_	,    rouge_keys=SCREAMING_SNAKE_CASE_					)
    assert score_sep == score_no_sep




def __lowercase    (							):
    snake_case_				:  Optional[Any]       =			[
        '''Her older sister, Margot Frank, died in 1945, a month earlier than previously thought.''',
        '''Marseille prosecutor says \"so far no videos were used in the crash investigation\" despite media reports .''',
    ]
    snake_case_				:  Tuple       =			[
        '''Margot Frank, died in 1945, a month earlier than previously thought.''',
        '''Prosecutor: \"No videos were used in the crash investigation\" German papers say they saw a cell phone video of'''
        ''' the final seconds on board Flight 9525.''',
    ]
    assert calculate_rouge(SCREAMING_SNAKE_CASE_	,    SCREAMING_SNAKE_CASE_	,    newline_sep=SCREAMING_SNAKE_CASE_					) == calculate_rouge(SCREAMING_SNAKE_CASE_	,    SCREAMING_SNAKE_CASE_	,    newline_sep=SCREAMING_SNAKE_CASE_					)




def __lowercase    (							):
    snake_case_				:  Dict       =			[
        '''\" \"a person who has such a video needs to immediately give it to the investigators,\" prosecutor says .<n> \"it is a very disturbing scene,\" editor-in-chief of bild online tells \"erin burnett: outfront\" '''
    ]
    snake_case_				:  List[Any]       =			[
        ''' Marseille prosecutor says \"so far no videos were used in the crash investigation\" despite media reports . Journalists at Bild and Paris Match are \"very confident\" the video clip is real, an editor says . Andreas Lubitz had informed his Lufthansa training school of an episode of severe depression, airline says .'''
    ]

    snake_case_				:  Optional[int]       =			calculate_rouge(SCREAMING_SNAKE_CASE_	,    SCREAMING_SNAKE_CASE_	,    rouge_keys=['''rougeLsum''']	,    newline_sep=SCREAMING_SNAKE_CASE_					)['''rougeLsum''']
    snake_case_				:  str       =			calculate_rouge(SCREAMING_SNAKE_CASE_	,    SCREAMING_SNAKE_CASE_	,    rouge_keys=['''rougeLsum''']					)['''rougeLsum''']
    assert new_score > prev_score






def __lowercase    (							):
    snake_case_				:  List[str]       =			Path('''examples/seq2seq/test_data/wmt_en_ro'''					)
    snake_case_				:  Optional[int]       =			calculate_rouge_path(data_dir.joinpath('''test.source'''					)	,    data_dir.joinpath('''test.target'''					)					)
    assert isinstance(SCREAMING_SNAKE_CASE_	,    SCREAMING_SNAKE_CASE_					)
    snake_case_				:  str       =			calculate_rouge_path(
        data_dir.joinpath('''test.source'''					)	,    data_dir.joinpath('''test.target'''					)	,    bootstrap_aggregation=SCREAMING_SNAKE_CASE_					)
    assert isinstance(SCREAMING_SNAKE_CASE_	,    SCREAMING_SNAKE_CASE_					)










"""simple docstring"""

import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError

from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils import TOKEN, USER, get_tests_dir, is_staging_test


sys.path.append(str(Path(__file__).parent.parent / '''utils'''))

from test_module.custom_feature_extraction import CustomFeatureExtractor  # noqa E402


lowercase__					:						Any												=			get_tests_dir('''fixtures''')




class  _UpperCAmelCase (    unittest.TestCase):

 def 		_snake_case      (  self	: Tuple       ):
     # A mock response for an HTTP head request to emulate server down
     snake_case_				:  str       =			mock.Mock()
     snake_case_				:  Optional[Any]       =			500
     snake_case_				:  str       =			{}
     snake_case_				:  Optional[int]       =			HTTPError
     snake_case_				:  Tuple       =			{}

     # Download this model to make sure it's in the cache.
     snake_case_				:  List[str]       =			WavaVecaFeatureExtractor.from_pretrained('''hf-internal-testing/tiny-random-wav2vec2'''       )
     # Under the mock environment we get a 500 error when trying to reach the model.
     with mock.patch('''requests.Session.request'''						,  return_value=lowercase_       ) as mock_head:
         snake_case_				:  int       =			WavaVecaFeatureExtractor.from_pretrained('''hf-internal-testing/tiny-random-wav2vec2'''       )
         # This check we did call the fake head request
         mock_head.assert_called()






 def 		_snake_case      (  self	: Union[str, Any]       ):
     # This test is for deprecated behavior and can be removed in v5
     snake_case_				:  str       =			WavaVecaFeatureExtractor.from_pretrained(
         '''https://huggingface.co/hf-internal-testing/tiny-random-wav2vec2/resolve/main/preprocessor_config.json'''       )





@is_staging_test
class  _UpperCAmelCase (    unittest.TestCase):

 @classmethod
 def 		_snake_case      (  cls	: int       ):
     snake_case_				:  Dict       =			TOKEN
     HfFolder.save_token(lowercase_       )

 @classmethod
 def 		_snake_case      (  cls	: str       ):
     try:
         delete_repo(token=cls._token						,  repo_id='''test-feature-extractor'''       )
     except HTTPError:
         pass

     try:
         delete_repo(token=cls._token						,  repo_id='''valid_org/test-feature-extractor-org'''       )
     except HTTPError:
         pass

     try:
         delete_repo(token=cls._token						,  repo_id='''test-dynamic-feature-extractor'''       )
     except HTTPError:
         pass

 def 		_snake_case      (  self	: Any       ):
     snake_case_				:  int       =			WavaVecaFeatureExtractor.from_pretrained(lowercase_       )
     feature_extractor.push_to_hub('''test-feature-extractor'''						,  use_auth_token=self._token       )

     snake_case_				:  Optional[Any]       =			WavaVecaFeatureExtractor.from_pretrained(f"{USER}/test-feature-extractor"       )
     for k, v in feature_extractor.__dict__.items():
         self.assertEqual(lowercase_						,  getattr(lowercase_						,  lowercase_       )       )

     # Reset repo
     delete_repo(token=self._token						,  repo_id='''test-feature-extractor'''       )

     # Push to hub via save_pretrained
     with tempfile.TemporaryDirectory() as tmp_dir:
         feature_extractor.save_pretrained(
             lowercase_						,  repo_id='''test-feature-extractor'''						,  push_to_hub=lowercase_						,  use_auth_token=self._token       )

     snake_case_				:  Optional[int]       =			WavaVecaFeatureExtractor.from_pretrained(f"{USER}/test-feature-extractor"       )
     for k, v in feature_extractor.__dict__.items():
         self.assertEqual(lowercase_						,  getattr(lowercase_						,  lowercase_       )       )

 def 		_snake_case      (  self	: Dict       ):
     snake_case_				:  Union[str, Any]       =			WavaVecaFeatureExtractor.from_pretrained(lowercase_       )
     feature_extractor.push_to_hub('''valid_org/test-feature-extractor'''						,  use_auth_token=self._token       )

     snake_case_				:  Optional[int]       =			WavaVecaFeatureExtractor.from_pretrained('''valid_org/test-feature-extractor'''       )
     for k, v in feature_extractor.__dict__.items():
         self.assertEqual(lowercase_						,  getattr(lowercase_						,  lowercase_       )       )

     # Reset repo
     delete_repo(token=self._token						,  repo_id='''valid_org/test-feature-extractor'''       )

     # Push to hub via save_pretrained
     with tempfile.TemporaryDirectory() as tmp_dir:
         feature_extractor.save_pretrained(
             lowercase_						,  repo_id='''valid_org/test-feature-extractor-org'''						,  push_to_hub=lowercase_						,  use_auth_token=self._token       )

     snake_case_				:  int       =			WavaVecaFeatureExtractor.from_pretrained('''valid_org/test-feature-extractor-org'''       )
     for k, v in feature_extractor.__dict__.items():
         self.assertEqual(lowercase_						,  getattr(lowercase_						,  lowercase_       )       )






 def 		_snake_case      (  self	: str       ):
     CustomFeatureExtractor.register_for_auto_class()
     snake_case_				:  Optional[Any]       =			CustomFeatureExtractor.from_pretrained(lowercase_       )

     feature_extractor.push_to_hub('''test-dynamic-feature-extractor'''						,  use_auth_token=self._token       )

     # This has added the proper auto_map field to the config
     self.assertDictEqual(
         feature_extractor.auto_map						,  {'''AutoFeatureExtractor''': '''custom_feature_extraction.CustomFeatureExtractor'''}						,  )

     snake_case_				:  Any       =			AutoFeatureExtractor.from_pretrained(
         f"{USER}/test-dynamic-feature-extractor"						,  trust_remote_code=lowercase_       )
     # Can't make an isinstance check because the new_feature_extractor is from the CustomFeatureExtractor class of a dynamic module
     self.assertEqual(new_feature_extractor.__class__.__name__						,  '''CustomFeatureExtractor'''       )





