





import unittest

from datasets import load_dataset

from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class        SCREAMING_SNAKE_CASE__					(		UpperCamelCase__							,   unittest.TestCase ):
 __SCREAMING_SNAKE_CASE							=      None
 __SCREAMING_SNAKE_CASE							=      BloomTokenizerFast
 __SCREAMING_SNAKE_CASE							=      BloomTokenizerFast
 __SCREAMING_SNAKE_CASE							=      True
 __SCREAMING_SNAKE_CASE							=      False
 __SCREAMING_SNAKE_CASE							=      '''tokenizer_file'''
 __SCREAMING_SNAKE_CASE							=      {'''bos_token''': '''<s>''', '''eos_token''': '''</s>''', '''unk_token''': '''<unk>''', '''pad_token''': '''<pad>'''}



 def 							UpperCamelCase     (				self					):
        super().setUp()
        A__		   =		BloomTokenizerFast.from_pretrained('''bigscience/tokenizer'''					)
        tokenizer.save_pretrained(self.tmpdirname					)



 def 							UpperCamelCase     (				self,**__lowerCamelCase					):
        kwargs.update(self.special_tokens_map					)
        return BloomTokenizerFast.from_pretrained(self.tmpdirname,**__lowerCamelCase					)



 def 							UpperCamelCase     (				self					):
        A__		   =		self.get_rust_tokenizer()

        A__		   =		['''The quick brown fox</s>''', '''jumps over the lazy dog</s>''']
        A__		   =		[[2175, 2_3714, 7_3173, 14_4252, 2], [77, 13_2619, 3478, 368, 10_9586, 3_5433, 2]]

        A__		   =		tokenizer.batch_encode_plus(__lowerCamelCase					)['''input_ids''']
        self.assertListEqual(__lowerCamelCase,__lowerCamelCase					)

        A__		   =		tokenizer.batch_decode(__lowerCamelCase					)
        self.assertListEqual(__lowerCamelCase,__lowerCamelCase					)



 def 							UpperCamelCase     (				self,__lowerCamelCase=6					):
        for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
               with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"					):
                      A__		   =		self.rust_tokenizer_class.from_pretrained(__lowerCamelCase,**__lowerCamelCase					)
                      # tokenizer_r.pad_token = None # Hotfixing padding = None
                      # Simple input
                      A__		   =		'''This is a simple input'''
                      A__		   =		['''This is a simple input 1''', '''This is a simple input 2''']
                      A__		   =		('''This is a simple input''', '''This is a pair''')
                      A__		   =		[
                          ('''This is a simple input 1''', '''This is a simple input 2'''),
                          ('''This is a simple pair 1''', '''This is a simple pair 2'''),
                      ]

                      # Simple input tests
                      try:
                             tokenizer_r.encode(__lowerCamelCase,max_length=__lowerCamelCase					)
                             tokenizer_r.encode_plus(__lowerCamelCase,max_length=__lowerCamelCase					)

                             tokenizer_r.batch_encode_plus(__lowerCamelCase,max_length=__lowerCamelCase					)
                             tokenizer_r.encode(__lowerCamelCase,max_length=__lowerCamelCase					)
                             tokenizer_r.batch_encode_plus(__lowerCamelCase,max_length=__lowerCamelCase					)
                      except ValueError:
                             self.fail('''Bloom Tokenizer should be able to deal with padding'''					)

                      A__		   =		None  # Hotfixing padding = None
                      self.assertRaises(__lowerCamelCase,tokenizer_r.encode,__lowerCamelCase,max_length=__lowerCamelCase,padding='''max_length'''					)

                      # Simple input
                      self.assertRaises(__lowerCamelCase,tokenizer_r.encode_plus,__lowerCamelCase,max_length=__lowerCamelCase,padding='''max_length'''					)

                      # Simple input
                      self.assertRaises(
                          __lowerCamelCase,tokenizer_r.batch_encode_plus,__lowerCamelCase,max_length=__lowerCamelCase,padding='''max_length''',)

                      # Pair input
                      self.assertRaises(__lowerCamelCase,tokenizer_r.encode,__lowerCamelCase,max_length=__lowerCamelCase,padding='''max_length'''					)

                      # Pair input
                      self.assertRaises(__lowerCamelCase,tokenizer_r.encode_plus,__lowerCamelCase,max_length=__lowerCamelCase,padding='''max_length'''					)

                      # Pair input
                      self.assertRaises(
                          __lowerCamelCase,tokenizer_r.batch_encode_plus,__lowerCamelCase,max_length=__lowerCamelCase,padding='''max_length''',)



 def 							UpperCamelCase     (				self					):
        A__		   =		self.get_rust_tokenizer()
        A__		   =		load_dataset('''xnli''','''all_languages''',split='''test''',streaming=__lowerCamelCase					)

        A__		   =		next(iter(__lowerCamelCase					)					)['''premise''']  # pick up one data
        A__		   =		list(sample_data.values()					)

        A__		   =		list(map(tokenizer.encode,__lowerCamelCase					)					)
        A__		   =		[tokenizer.decode(__lowerCamelCase,clean_up_tokenization_spaces=__lowerCamelCase					) for x in output_tokens]
        self.assertListEqual(__lowerCamelCase,__lowerCamelCase					)




 def 							UpperCamelCase     (				self					):
        # The test has to be overriden because BLOOM uses ALiBi positional embeddings that does not have
        # any sequence length constraints. This test of the parent class will fail since it relies on the
        # maximum sequence length of the positoonal embeddings.
        self.assertGreaterEqual(len(self.tokenizer_class.pretrained_vocab_files_map					),1					)
        self.assertGreaterEqual(len(list(self.tokenizer_class.pretrained_vocab_files_map.values()					)[0]					),1					)












import pytest

import datasets


# Import fixture modules as plugins
a__: Dict							   =						['tests.fixtures.files', 'tests.fixtures.hub', 'tests.fixtures.fsspec']


def       UpperCamelCase__(			UpperCamelCase__     :			List[Any]					,	UpperCamelCase__     :			Tuple    )->List[str]:
       # Mark tests as "unit" by default if not marked as "integration" (or already marked as "unit")
       for item in items:
              if any(marker in item.keywords for marker in ['''integration''', '''unit''']    ):
                     continue
              item.add_marker(pytest.mark.unit    )


def       UpperCamelCase__(			UpperCamelCase__     :			Dict    )->List[Any]:
       config.addinivalue_line('''markers'''					,	'''torchaudio_latest: mark test to run with torchaudio>=0.12'''    )


@pytest.fixture(autouse=UpperCamelCase__    )
def       UpperCamelCase__(			UpperCamelCase__     :			Optional[int]					,	UpperCamelCase__     :			int    )->Union[str, Any]:
       # test_hf_cache_home = tmp_path_factory.mktemp("cache")  # TODO: why a cache dir per test function does not work?
       A__		   =		tmp_path_factory.getbasetemp() / '''cache'''
       A__		   =		test_hf_cache_home / '''datasets'''
       A__		   =		test_hf_cache_home / '''metrics'''
       A__		   =		test_hf_cache_home / '''modules'''
       monkeypatch.setattr('''datasets.config.HF_DATASETS_CACHE'''					,	str(UpperCamelCase__    )    )
       monkeypatch.setattr('''datasets.config.HF_METRICS_CACHE'''					,	str(UpperCamelCase__    )    )
       monkeypatch.setattr('''datasets.config.HF_MODULES_CACHE'''					,	str(UpperCamelCase__    )    )
       A__		   =		test_hf_datasets_cache / '''downloads'''
       monkeypatch.setattr('''datasets.config.DOWNLOADED_DATASETS_PATH'''					,	str(UpperCamelCase__    )    )
       A__		   =		test_hf_datasets_cache / '''downloads''' / '''extracted'''
       monkeypatch.setattr('''datasets.config.EXTRACTED_DATASETS_PATH'''					,	str(UpperCamelCase__    )    )


@pytest.fixture(autouse=UpperCamelCase__					,	scope='''session'''    )
def       UpperCamelCase__(			)->int:
       datasets.disable_progress_bar()


@pytest.fixture(autouse=UpperCamelCase__    )
def       UpperCamelCase__(			UpperCamelCase__     :			str    )->Tuple:
       # don't take tests into account when counting downloads
       monkeypatch.setattr('''datasets.config.HF_UPDATE_DOWNLOAD_COUNTS'''					,	UpperCamelCase__    )


@pytest.fixture
def       UpperCamelCase__(			UpperCamelCase__     :			List[Any]    )->Optional[Any]:
       # Required to suppress RemovedIn20Warning when feature(s) are not compatible with SQLAlchemy 2.0
       # To be removed once SQLAlchemy 2.0 supported
       monkeypatch.setattr('''sqlalchemy.util.deprecations.SILENCE_UBER_WARNING'''					,	UpperCamelCase__    )





