





import unittest

from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


SCREAMING_SNAKE_CASE_						   =       get_tests_dir("""fixtures/test_sentencepiece.model""")
SCREAMING_SNAKE_CASE_						   =       get_tests_dir("""fixtures/test_sentencepiece_bpe.model""")

SCREAMING_SNAKE_CASE_						   =       """pt""" if is_torch_available() else """tf"""

@require_sentencepiece
@require_tokenizers
class 		UpperCamelCase__ (      lowerCAmelCase_							,      unittest.TestCase   ):



     '''simple docstring'''

     __snake_case    :	Tuple			=			CamembertTokenizer
     __snake_case    :	Tuple			=			CamembertTokenizerFast
     __snake_case    :	int			=			True
     __snake_case    :	Union[str, Any]			=			True






     def 				SCREAMING_SNAKE_CASE__  (							self						:    Dict       )     ->		Optional[Any]:




           '''simple docstring'''


           super().setUp()

           # We have a SentencePiece fixture for testing
           SCREAMING_SNAKE_CASE		=						CamembertTokenizer(lowerCamelCase__       )
           tokenizer.save_pretrained(self.tmpdirname       )






     def 				SCREAMING_SNAKE_CASE__  (							self						:    List[str]       )     ->		str:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						"""<pad>"""
           SCREAMING_SNAKE_CASE		=						1

           self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCamelCase__       )						,lowerCamelCase__       )
           self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCamelCase__       )						,lowerCamelCase__       )






     def 				SCREAMING_SNAKE_CASE__  (							self						:    List[str]       )     ->		Dict:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						list(self.get_tokenizer().get_vocab().keys()       )

           self.assertEqual(vocab_keys[0]						,"""<s>NOTUSED"""       )
           self.assertEqual(vocab_keys[1]						,"""<pad>"""       )
           self.assertEqual(vocab_keys[-1]						,"""<mask>"""       )
           self.assertEqual(len(lowerCamelCase__       )						,1004       )






     def 				SCREAMING_SNAKE_CASE__  (							self						:    Optional[Any]       )     ->		List[Any]:




           '''simple docstring'''


           self.assertEqual(self.get_tokenizer().vocab_size						,1005       )






     def 				SCREAMING_SNAKE_CASE__  (							self						:    Dict       )     ->		Dict:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						CamembertTokenizer(lowerCamelCase__       )
           tokenizer.save_pretrained(self.tmpdirname       )
           SCREAMING_SNAKE_CASE		=						CamembertTokenizerFast.from_pretrained(self.tmpdirname       )

           SCREAMING_SNAKE_CASE		=						"""I was born in 92000, and this is falsé."""

           SCREAMING_SNAKE_CASE		=						tokenizer.encode(lowerCamelCase__       )
           SCREAMING_SNAKE_CASE		=						rust_tokenizer.encode(lowerCamelCase__       )
           self.assertListEqual(lowerCamelCase__						,lowerCamelCase__       )

           SCREAMING_SNAKE_CASE		=						tokenizer.encode(lowerCamelCase__						,add_special_tokens=lowerCamelCase__       )
           SCREAMING_SNAKE_CASE		=						rust_tokenizer.encode(lowerCamelCase__						,add_special_tokens=lowerCamelCase__       )
           self.assertListEqual(lowerCamelCase__						,lowerCamelCase__       )

           # <unk> tokens are not the same for `rust` than for `slow`.
           # Because spm gives back raw token instead of `unk` in EncodeAsPieces
           # tokens = tokenizer.tokenize(sequence)
           SCREAMING_SNAKE_CASE		=						tokenizer.convert_ids_to_tokens(lowerCamelCase__       )
           SCREAMING_SNAKE_CASE		=						rust_tokenizer.tokenize(lowerCamelCase__       )
           self.assertListEqual(lowerCamelCase__						,lowerCamelCase__       )






     def 				SCREAMING_SNAKE_CASE__  (							self						:    Optional[Any]       )     ->		Optional[int]:




           '''simple docstring'''


           if not self.test_rust_tokenizer:
                 return

           SCREAMING_SNAKE_CASE		=						self.get_tokenizer()
           SCREAMING_SNAKE_CASE		=						self.get_rust_tokenizer()

           SCREAMING_SNAKE_CASE		=						"""I was born in 92000, and this is falsé."""

           SCREAMING_SNAKE_CASE		=						tokenizer.tokenize(lowerCamelCase__       )
           SCREAMING_SNAKE_CASE		=						rust_tokenizer.tokenize(lowerCamelCase__       )
           self.assertListEqual(lowerCamelCase__						,lowerCamelCase__       )

           SCREAMING_SNAKE_CASE		=						tokenizer.encode(lowerCamelCase__						,add_special_tokens=lowerCamelCase__       )
           SCREAMING_SNAKE_CASE		=						rust_tokenizer.encode(lowerCamelCase__						,add_special_tokens=lowerCamelCase__       )
           self.assertListEqual(lowerCamelCase__						,lowerCamelCase__       )

           SCREAMING_SNAKE_CASE		=						self.get_rust_tokenizer()
           SCREAMING_SNAKE_CASE		=						tokenizer.encode(lowerCamelCase__       )
           SCREAMING_SNAKE_CASE		=						rust_tokenizer.encode(lowerCamelCase__       )
           self.assertListEqual(lowerCamelCase__						,lowerCamelCase__       )






     @slow
     def 				SCREAMING_SNAKE_CASE__  (							self						:    Union[str, Any]       )     ->		Union[str, Any]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						{"""input_ids""": [[5, 54, 7196, 297, 30, 23, 776, 18, 11, 3215, 3705, 8252, 22, 3164, 1181, 2116, 29, 16, 813, 25, 791, 3314, 20, 3446, 38, 27575, 120, 6, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [5, 468, 17, 11, 9088, 20, 1517, 8, 22804, 18818, 10, 38, 629, 607, 607, 142, 19, 7196, 867, 56, 10326, 24, 2267, 20, 416, 5072, 15612, 233, 734, 7, 2399, 27, 16, 3015, 1649, 7, 24, 20, 4338, 2399, 27, 13, 3400, 14, 13, 6189, 8, 930, 9, 6]], """attention_mask""": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
           # fmt: on

           # camembert is a french model. So we also use french texts.
           SCREAMING_SNAKE_CASE		=						[
               """Le transformeur est un modèle d'apprentissage profond introduit en 2017, """
               """utilisé principalement dans le domaine du traitement automatique des langues (TAL).""",
               """À l'instar des réseaux de neurones récurrents (RNN), les transformeurs sont conçus """
               """pour gérer des données séquentielles, telles que le langage naturel, pour des tâches """
               """telles que la traduction et la synthèse de texte.""",
           ]

           self.tokenizer_integration_test_util(
               expected_encoding=lowerCamelCase__						,model_name="""camembert-base"""						,revision="""3a0641d9a1aeb7e848a74299e7e4c4bca216b4cf"""						,sequences=lowerCamelCase__						,)









import os
from distutils.util import strtobool



def    __lowercase   (      _SCREAMING_SNAKE_CASE ,						_SCREAMING_SNAKE_CASE	) ->   Tuple:


      '''simple docstring'''


      for e in env_keys:
            SCREAMING_SNAKE_CASE		=						int(os.environ.get(_SCREAMING_SNAKE_CASE ,						-1	)	)
            if val >= 0:
                  return val
      return default



def    __lowercase   (      _SCREAMING_SNAKE_CASE ,						_SCREAMING_SNAKE_CASE=False	) ->   Optional[int]:


      '''simple docstring'''


      SCREAMING_SNAKE_CASE		=						os.environ.get(_SCREAMING_SNAKE_CASE ,						str(_SCREAMING_SNAKE_CASE	)	)
      return strtobool(_SCREAMING_SNAKE_CASE	) == 1  # As its name indicates `strtobool` actually returns an int...



def    __lowercase   (      _SCREAMING_SNAKE_CASE ,						_SCREAMING_SNAKE_CASE="no"	) ->   Any:


      '''simple docstring'''


      SCREAMING_SNAKE_CASE		=						os.environ.get(_SCREAMING_SNAKE_CASE ,						str(_SCREAMING_SNAKE_CASE	)	)
      return value


