




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


UpperCamelCase								=					get_tests_dir('fixtures/test_sentencepiece.model')
UpperCamelCase								=					get_tests_dir('fixtures/test_sentencepiece_bpe.model')

UpperCamelCase								=					'pt' if is_torch_available() else 'tf'





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




    """simple docstring"""

    snake_case__ =				CamembertTokenizer
    snake_case__ =				CamembertTokenizerFast
    snake_case__ =				True
    snake_case__ =				True


    def        a				(	self					:					Tuple       )				->	Tuple:
         super().setUp()

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


    def        a				(	self					:					Tuple       )				->	int:
         lowerCAmelCase__          =			"<pad>"
         lowerCAmelCase__          =			1

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


    def        a				(	self					:					Optional[Any]       )				->	Optional[int]:
         lowerCAmelCase__          =			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(SCREAMING_SNAKE_CASE__       )       ,     1_004       )


    def        a				(	self					:					List[Any]       )				->	List[str]:
         self.assertEqual(self.get_tokenizer().vocab_size       ,     1_005       )


    def        a				(	self					:					Tuple       )				->	str:
         lowerCAmelCase__          =			CamembertTokenizer(SCREAMING_SNAKE_CASE__       )
         tokenizer.save_pretrained(self.tmpdirname       )
         lowerCAmelCase__          =			CamembertTokenizerFast.from_pretrained(self.tmpdirname       )

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

         lowerCAmelCase__          =			tokenizer.encode(SCREAMING_SNAKE_CASE__       )
         lowerCAmelCase__          =			rust_tokenizer.encode(SCREAMING_SNAKE_CASE__       )
         self.assertListEqual(SCREAMING_SNAKE_CASE__       ,     SCREAMING_SNAKE_CASE__       )

         lowerCAmelCase__          =			tokenizer.encode(SCREAMING_SNAKE_CASE__       ,     add_special_tokens=SCREAMING_SNAKE_CASE__       )
         lowerCAmelCase__          =			rust_tokenizer.encode(SCREAMING_SNAKE_CASE__       ,     add_special_tokens=SCREAMING_SNAKE_CASE__       )
         self.assertListEqual(SCREAMING_SNAKE_CASE__       ,     SCREAMING_SNAKE_CASE__       )

         # <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)
         lowerCAmelCase__          =			tokenizer.convert_ids_to_tokens(SCREAMING_SNAKE_CASE__       )
         lowerCAmelCase__          =			rust_tokenizer.tokenize(SCREAMING_SNAKE_CASE__       )
         self.assertListEqual(SCREAMING_SNAKE_CASE__       ,     SCREAMING_SNAKE_CASE__       )


    def        a				(	self					:					int       )				->	List[Any]:
         if not self.test_rust_tokenizer:
              return

         lowerCAmelCase__          =			self.get_tokenizer()
         lowerCAmelCase__          =			self.get_rust_tokenizer()

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

         lowerCAmelCase__          =			tokenizer.tokenize(SCREAMING_SNAKE_CASE__       )
         lowerCAmelCase__          =			rust_tokenizer.tokenize(SCREAMING_SNAKE_CASE__       )
         self.assertListEqual(SCREAMING_SNAKE_CASE__       ,     SCREAMING_SNAKE_CASE__       )

         lowerCAmelCase__          =			tokenizer.encode(SCREAMING_SNAKE_CASE__       ,     add_special_tokens=SCREAMING_SNAKE_CASE__       )
         lowerCAmelCase__          =			rust_tokenizer.encode(SCREAMING_SNAKE_CASE__       ,     add_special_tokens=SCREAMING_SNAKE_CASE__       )
         self.assertListEqual(SCREAMING_SNAKE_CASE__       ,     SCREAMING_SNAKE_CASE__       )

         lowerCAmelCase__          =			self.get_rust_tokenizer()
         lowerCAmelCase__          =			tokenizer.encode(SCREAMING_SNAKE_CASE__       )
         lowerCAmelCase__          =			rust_tokenizer.encode(SCREAMING_SNAKE_CASE__       )
         self.assertListEqual(SCREAMING_SNAKE_CASE__       ,     SCREAMING_SNAKE_CASE__       )


    @slow
    def        a				(	self					:					Tuple       )				->	Union[str, Any]:
         # fmt: off
         lowerCAmelCase__          =			{"input_ids": [[5, 54, 7_196, 297, 30, 23, 776, 18, 11, 3_215, 3_705, 8_252, 22, 3_164, 1_181, 2_116, 29, 16, 813, 25, 791, 3_314, 20, 3_446, 38, 27_575, 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, 9_088, 20, 1_517, 8, 22_804, 18_818, 10, 38, 629, 607, 607, 142, 19, 7_196, 867, 56, 10_326, 24, 2_267, 20, 416, 5_072, 15_612, 233, 734, 7, 2_399, 27, 16, 3_015, 1_649, 7, 24, 20, 4_338, 2_399, 27, 13, 3_400, 14, 13, 6_189, 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.
         lowerCAmelCase__          =			[
             "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=SCREAMING_SNAKE_CASE__       ,     model_name="camembert-base"       ,     revision="3a0641d9a1aeb7e848a74299e7e4c4bca216b4cf"       ,     sequences=SCREAMING_SNAKE_CASE__       ,     )






import argparse
from collections import defaultdict



def 							_A       (						lowerCAmelCase_					: Dict       ,    lowerCAmelCase_					: str       ,    lowerCAmelCase_					: Dict       ,    lowerCAmelCase_					: Dict       ,    lowerCAmelCase_					: int      ):
     """simple docstring"""

     lowerCAmelCase__          =			F'{file}_{class_name}_{test_name}'
     done_test[_id] += 1

     with open(lowerCAmelCase_       ,    "r"      ) as f:
          lowerCAmelCase__          =			f.readlines()

     lowerCAmelCase__          =			F'class {class_name}('
     lowerCAmelCase__          =			F'{4 * " "}def {test_name}('
     lowerCAmelCase__          =			F'{8 * " "}{correct_line.split()[0]}'
     lowerCAmelCase__          =			F'{16 * " "}{correct_line.split()[0]}'
     lowerCAmelCase__          =			False
     lowerCAmelCase__          =			False
     lowerCAmelCase__          =			False
     lowerCAmelCase__          =			False
     lowerCAmelCase__          =			0
     lowerCAmelCase__          =			0

     lowerCAmelCase__          =			[]
     for line in lines:
          if line.startswith(lowerCAmelCase_      ):
               lowerCAmelCase__          =			True
          elif in_class and line.startswith(lowerCAmelCase_      ):
               lowerCAmelCase__          =			True
          elif in_class and in_func and (line.startswith(lowerCAmelCase_      ) or line.startswith(lowerCAmelCase_      )):
               lowerCAmelCase__          =			len(line.split(correct_line.split()[0]      )[0]      )
               count += 1

               if count == done_test[_id]:
                    lowerCAmelCase__          =			True

          if in_class and in_func and in_line:
               if ")" not in line:
                    continue
               else:
                    lowerCAmelCase__          =			True

          if in_class and in_func and in_line and insert_line:
               new_lines.append(F'{spaces * " "}{correct_line}'      )
               lowerCAmelCase__          =			lowerCAmelCase__          =			lowerCAmelCase__          =			lowerCAmelCase__          =			False
          else:
               new_lines.append(lowerCAmelCase_      )

     with open(lowerCAmelCase_       ,    "w"      ) as f:
          for line in new_lines:
               f.write(lowerCAmelCase_      )



def 							_A       (						lowerCAmelCase_					: List[str]       ,    lowerCAmelCase_					: Any=None      ):
     """simple docstring"""

     if fail is not None:
          with open(lowerCAmelCase_       ,    "r"      ) as f:
               lowerCAmelCase__          =			{l.strip() for l in f.readlines()}
     else:
          lowerCAmelCase__          =			None

     with open(lowerCAmelCase_       ,    "r"      ) as f:
          lowerCAmelCase__          =			f.readlines()

     lowerCAmelCase__          =			defaultdict(lowerCAmelCase_      )
     for line in correct_lines:
          lowerCAmelCase__     ,		lowerCAmelCase__     ,		lowerCAmelCase__     ,		lowerCAmelCase__          =			line.split(";"      )
          if test_failures is None or "::".join([file, class_name, test_name]      ) in test_failures:
               overwrite_file(lowerCAmelCase_       ,    lowerCAmelCase_       ,    lowerCAmelCase_       ,    lowerCAmelCase_       ,    lowerCAmelCase_      )


if __name__ == "__main__":
     UpperCamelCase								=					argparse.ArgumentParser()
     parser.add_argument('--correct_filename', help='filename of tests with expected result')
     parser.add_argument('--fail_filename', help='filename of test failures', type=str, default=None)
     UpperCamelCase								=					parser.parse_args()

     main(args.correct_filename, args.fail_filename)
