
"""simple docstring"""

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			:       Optional[Any]									=				get_tests_dir("fixtures/test_sentencepiece.model")
UpperCamelCase			:       int									=				get_tests_dir("fixtures/test_sentencepiece_bpe.model")

UpperCamelCase			:       List[str]									=				"pt" if is_torch_available() else "tf"

@require_sentencepiece
@require_tokenizers
class __lowerCAmelCase	(   __SCREAMING_SNAKE_CASE    ,						unittest.TestCase    ):
     lowercase		     =		CamembertTokenizer
     lowercase		     =		CamembertTokenizerFast
     lowercase		     =		True
     lowercase		     =		True





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      super().setUp()

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





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      __UpperCamelCase       						= '<pad>'
      __UpperCamelCase       						= 1

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





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      __UpperCamelCase       						= 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(__UpperCAmelCase   )			,  1004   )





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




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





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      __UpperCamelCase       						= CamembertTokenizer(__UpperCAmelCase   )
      tokenizer.save_pretrained(self.tmpdirname   )
      __UpperCamelCase       						= CamembertTokenizerFast.from_pretrained(self.tmpdirname   )

      __UpperCamelCase       						= 'I was born in 92000, and this is falsé.'

      __UpperCamelCase       						= tokenizer.encode(__UpperCAmelCase   )
      __UpperCamelCase       						= rust_tokenizer.encode(__UpperCAmelCase   )
      self.assertListEqual(__UpperCAmelCase			,  __UpperCAmelCase   )

      __UpperCamelCase       						= tokenizer.encode(__UpperCAmelCase			,  add_special_tokens=__UpperCAmelCase   )
      __UpperCamelCase       						= rust_tokenizer.encode(__UpperCAmelCase			,  add_special_tokens=__UpperCAmelCase   )
      self.assertListEqual(__UpperCAmelCase			,  __UpperCAmelCase   )

      # <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)
      __UpperCamelCase       						= tokenizer.convert_ids_to_tokens(__UpperCAmelCase   )
      __UpperCamelCase       						= rust_tokenizer.tokenize(__UpperCAmelCase   )
      self.assertListEqual(__UpperCAmelCase			,  __UpperCAmelCase   )





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      if not self.test_rust_tokenizer:
       return

      __UpperCamelCase       						= self.get_tokenizer()
      __UpperCamelCase       						= self.get_rust_tokenizer()

      __UpperCamelCase       						= 'I was born in 92000, and this is falsé.'

      __UpperCamelCase       						= tokenizer.tokenize(__UpperCAmelCase   )
      __UpperCamelCase       						= rust_tokenizer.tokenize(__UpperCAmelCase   )
      self.assertListEqual(__UpperCAmelCase			,  __UpperCAmelCase   )

      __UpperCamelCase       						= tokenizer.encode(__UpperCAmelCase			,  add_special_tokens=__UpperCAmelCase   )
      __UpperCamelCase       						= rust_tokenizer.encode(__UpperCAmelCase			,  add_special_tokens=__UpperCAmelCase   )
      self.assertListEqual(__UpperCAmelCase			,  __UpperCAmelCase   )

      __UpperCamelCase       						= self.get_rust_tokenizer()
      __UpperCamelCase       						= tokenizer.encode(__UpperCAmelCase   )
      __UpperCamelCase       						= rust_tokenizer.encode(__UpperCAmelCase   )
      self.assertListEqual(__UpperCAmelCase			,  __UpperCAmelCase   )







     @slow
     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      __UpperCamelCase       						= {'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, 2_7575, 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, 2_2804, 1_8818, 10, 38, 629, 607, 607, 142, 19, 7196, 867, 56, 1_0326, 24, 2267, 20, 416, 5072, 1_5612, 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.
      __UpperCamelCase       						= [
          '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=__UpperCAmelCase			,  model_name='camembert-base'			,  revision='3a0641d9a1aeb7e848a74299e7e4c4bca216b4cf'			,  sequences=__UpperCAmelCase			,  )







"""simple docstring"""

import time
from contextlib import contextmanager
from pathlib import Path

import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder


UpperCamelCase			:       Union[str, Any]									=				"__DUMMY_TRANSFORMERS_USER__"
UpperCamelCase			:       List[Any]									=				"Dummy User"
UpperCamelCase			:       List[Any]									=				"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"

UpperCamelCase			:       Any									=				"https://hub-ci.huggingface.co"
UpperCamelCase			:       str									=				CI_HUB_ENDPOINT + "/datasets/{repo_id}/resolve/{revision}/{path}"
UpperCamelCase			:       Optional[Any]									=				CI_HUB_ENDPOINT + "/{repo_id}/resolve/{revision}/{filename}"
UpperCamelCase			:       Optional[int]									=				Path("~/.huggingface/hub_ci_token").expanduser()






@pytest.fixture
def 							A		(       snake_case   :Optional[Any]	)   ->			Union[str, Any]:
 monkeypatch.setattr(
     'huggingface_hub.file_download.HUGGINGFACE_CO_URL_TEMPLATE'       ,      snake_case	)






@pytest.fixture
def 							A		(       snake_case   :str	)   ->			List[Any]:
 monkeypatch.setattr('datasets.config.HF_ENDPOINT'       ,      snake_case	)
 monkeypatch.setattr('datasets.config.HUB_DATASETS_URL'       ,      snake_case	)






@pytest.fixture
def 							A		(       snake_case   :Optional[int]	)   ->			Dict:
 monkeypatch.setattr('huggingface_hub.hf_api.HfFolder.path_token'       ,      snake_case	)






@pytest.fixture
def 							A		(       snake_case   :List[Any]       ,      snake_case   :Tuple	)   ->			Tuple:
 HfFolder.save_token(snake_case	)
 yield
 HfFolder.delete_token()






@pytest.fixture(scope='session'	)
def 							A		(       )   ->			List[Any]:
 return HfApi(endpoint=snake_case	)






@pytest.fixture(scope='session'	)
def 							A		(       snake_case   :HfApi	)   ->			List[Any]:
 __UpperCamelCase       						= HfFolder.get_token()
 HfFolder.save_token(snake_case	)
 yield CI_HUB_USER_TOKEN
 if previous_token is not None:
  HfFolder.save_token(snake_case	)






@pytest.fixture
def 							A		(       snake_case   :str	)   ->			str:
 def _cleanup_repo(snake_case   :Union[str, Any]	):
  hf_api.delete_repo(snake_case       ,      token=snake_case       ,      repo_type='dataset'	)

 return _cleanup_repo






@pytest.fixture
def 							A		(       snake_case   :List[str]	)   ->			Any:
 @contextmanager
 def _temporary_repo(snake_case   :Tuple	):
  try:
   yield repo_id
  finally:
   cleanup_repo(snake_case	)

 return _temporary_repo






@pytest.fixture(scope='session'	)
def 							A		(       snake_case   :HfApi       ,      snake_case   :Dict       ,      snake_case   :Dict	)   ->			List[str]:
 __UpperCamelCase       						= f'repo_txt_data-{int(time.time() * 10e3	)}'
 __UpperCamelCase       						= f'{CI_HUB_USER}/{repo_name}'
 hf_api.create_repo(snake_case       ,      token=snake_case       ,      repo_type='dataset'       ,      private=snake_case	)
 hf_api.upload_file(
     token=snake_case       ,      path_or_fileobj=str(snake_case	)       ,      path_in_repo='data/text_data.txt'       ,      repo_id=snake_case       ,      repo_type='dataset'       ,      )
 yield repo_id
 try:
  hf_api.delete_repo(snake_case       ,      token=snake_case       ,      repo_type='dataset'	)
 except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
  pass






@pytest.fixture()
def 							A		(       snake_case   :Optional[int]       ,      snake_case   :str       ,      snake_case   :Tuple	)   ->			Any:
 return hf_private_dataset_repo_txt_data_






@pytest.fixture(scope='session'	)
def 							A		(       snake_case   :HfApi       ,      snake_case   :List[Any]       ,      snake_case   :str	)   ->			Optional[int]:
 __UpperCamelCase       						= f'repo_zipped_txt_data-{int(time.time() * 10e3	)}'
 __UpperCamelCase       						= f'{CI_HUB_USER}/{repo_name}'
 hf_api.create_repo(snake_case       ,      token=snake_case       ,      repo_type='dataset'       ,      private=snake_case	)
 hf_api.upload_file(
     token=snake_case       ,      path_or_fileobj=str(snake_case	)       ,      path_in_repo='data.zip'       ,      repo_id=snake_case       ,      repo_type='dataset'       ,      )
 yield repo_id
 try:
  hf_api.delete_repo(snake_case       ,      token=snake_case       ,      repo_type='dataset'	)
 except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
  pass






@pytest.fixture()
def 							A		(       snake_case   :int       ,      snake_case   :Optional[int]       ,      snake_case   :Optional[int]	)   ->			str:
 return hf_private_dataset_repo_zipped_txt_data_






@pytest.fixture(scope='session'	)
def 							A		(       snake_case   :HfApi       ,      snake_case   :List[str]       ,      snake_case   :Any	)   ->			List[Any]:
 __UpperCamelCase       						= f'repo_zipped_img_data-{int(time.time() * 10e3	)}'
 __UpperCamelCase       						= f'{CI_HUB_USER}/{repo_name}'
 hf_api.create_repo(snake_case       ,      token=snake_case       ,      repo_type='dataset'       ,      private=snake_case	)
 hf_api.upload_file(
     token=snake_case       ,      path_or_fileobj=str(snake_case	)       ,      path_in_repo='data.zip'       ,      repo_id=snake_case       ,      repo_type='dataset'       ,      )
 yield repo_id
 try:
  hf_api.delete_repo(snake_case       ,      token=snake_case       ,      repo_type='dataset'	)
 except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
  pass






@pytest.fixture()
def 							A		(       snake_case   :List[str]       ,      snake_case   :Optional[Any]       ,      snake_case   :Optional[int]	)   ->			Optional[int]:
 return hf_private_dataset_repo_zipped_img_data_



