




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_  (						A_,       unittest.TestCase							):
    lowercase__						 =				CamembertTokenizer
    lowercase__						 =				CamembertTokenizerFast
    lowercase__						 =				True
    lowercase__						 =				True




    def 							__magic_name__							(   self						:	Dict				)				->							str:




     '''simple docstring'''

     super().setUp()

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




    def 							__magic_name__							(   self						:	List[str]				)				->							List[Any]:




     '''simple docstring'''

     A__	=    "<pad>"
     A__	=    1

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




    def 							__magic_name__							(   self						:	str				)				->							Dict:




     '''simple docstring'''

     A__	=    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(snake_case_				)     ,			1_004				)




    def 							__magic_name__							(   self						:	List[str]				)				->							int:




     '''simple docstring'''

     self.assertEqual(self.get_tokenizer().vocab_size     ,			1_005				)




    def 							__magic_name__							(   self						:	Union[str, Any]				)				->							Any:




     '''simple docstring'''

     A__	=    CamembertTokenizer(snake_case_				)
     tokenizer.save_pretrained(self.tmpdirname				)
     A__	=    CamembertTokenizerFast.from_pretrained(self.tmpdirname				)

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

     A__	=    tokenizer.encode(snake_case_				)
     A__	=    rust_tokenizer.encode(snake_case_				)
     self.assertListEqual(snake_case_     ,			snake_case_				)

     A__	=    tokenizer.encode(snake_case_     ,			add_special_tokens=snake_case_				)
     A__	=    rust_tokenizer.encode(snake_case_     ,			add_special_tokens=snake_case_				)
     self.assertListEqual(snake_case_     ,			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)
     A__	=    tokenizer.convert_ids_to_tokens(snake_case_				)
     A__	=    rust_tokenizer.tokenize(snake_case_				)
     self.assertListEqual(snake_case_     ,			snake_case_				)




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




     '''simple docstring'''

     if not self.test_rust_tokenizer:
      return

     A__	=    self.get_tokenizer()
     A__	=    self.get_rust_tokenizer()

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

     A__	=    tokenizer.tokenize(snake_case_				)
     A__	=    rust_tokenizer.tokenize(snake_case_				)
     self.assertListEqual(snake_case_     ,			snake_case_				)

     A__	=    tokenizer.encode(snake_case_     ,			add_special_tokens=snake_case_				)
     A__	=    rust_tokenizer.encode(snake_case_     ,			add_special_tokens=snake_case_				)
     self.assertListEqual(snake_case_     ,			snake_case_				)

     A__	=    self.get_rust_tokenizer()
     A__	=    tokenizer.encode(snake_case_				)
     A__	=    rust_tokenizer.encode(snake_case_				)
     self.assertListEqual(snake_case_     ,			snake_case_				)




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




     '''simple docstring'''

     A__	=    {"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.
     A__	=    [
         "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=snake_case_     ,			model_name="camembert-base"     ,			revision="3a0641d9a1aeb7e848a74299e7e4c4bca216b4cf"     ,			sequences=snake_case_     ,			)











"""simple docstring"""



from argparse import ArgumentParser

from .env import EnvironmentCommand







def   _SCREAMING_SNAKE_CASE       (							)						->		List[Any]:
 A__	=    ArgumentParser("Diffusers CLI tool"      ,			usage="diffusers-cli <command> [<args>]"						)
 A__	=    parser.add_subparsers(help="diffusers-cli command helpers"						)

 # Register commands
 EnvironmentCommand.register_subcommand(lowercase_						)

 # Let's go
 A__	=    parser.parse_args()

 if not hasattr(lowercase_      ,			"func"						):
  parser.print_help()
  exit(1						)

 # Run
 A__	=    args.func(lowercase_						)
 service.run()


if __name__ == "__main__":
      main()





