




'''simple docstring'''




import unittest

from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin


@require_rjieba
@require_tokenizers
class   __UpperCamelCase       ( _A			,					unittest.TestCase				):
       lowercase	:    str      						=RoFormerTokenizer
       lowercase	:    Optional[int]      						=RoFormerTokenizerFast
       lowercase	:    int      						=True
       lowercase	:    Optional[int]      						=True






       def      lowercase__     (							self  ):



              """simple docstring"""







              super().setUp()






       def      lowercase__     (							self,		**lowerCAmelCase  ):



              """simple docstring"""







              return self.tokenizer_class.from_pretrained('''junnyu/roformer_chinese_base''',		**UpperCamelCase__  )






       def      lowercase__     (							self,		**lowerCAmelCase  ):



              """simple docstring"""







              return self.rust_tokenizer_class.from_pretrained('''junnyu/roformer_chinese_base''',		**UpperCamelCase__  )






       def      lowercase__     (							self  ):



              """simple docstring"""







              lowerCamelCase_							='''永和服装饰品有限公司,今天天气非常好'''
              lowerCamelCase_							='''永和 服装 饰品 有限公司 , 今 天 天 气 非常 好'''
              return input_text, output_text






       def      lowercase__     (							self  ):



              """simple docstring"""







              lowerCamelCase_							=self.get_tokenizer()
              lowerCamelCase_,      lowerCamelCase_							=self.get_chinese_input_output_texts()
              lowerCamelCase_							=tokenizer.tokenize(UpperCamelCase__  )

              self.assertListEqual(UpperCamelCase__,		output_text.split()  )

              lowerCamelCase_							=tokens + [tokenizer.unk_token]
              lowerCamelCase_							=[22_943, 21_332, 34_431, 45_904, 117, 306, 1_231, 1_231, 2_653, 33_994, 1_266, 100]
              self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase__  ),		UpperCamelCase__  )






       def      lowercase__     (							self  ):



              """simple docstring"""







              lowerCamelCase_							=self.get_rust_tokenizer()
              lowerCamelCase_,      lowerCamelCase_							=self.get_chinese_input_output_texts()
              lowerCamelCase_							=tokenizer.tokenize(UpperCamelCase__  )
              self.assertListEqual(UpperCamelCase__,		output_text.split()  )
              lowerCamelCase_							=tokens + [tokenizer.unk_token]
              lowerCamelCase_							=[22_943, 21_332, 34_431, 45_904, 117, 306, 1_231, 1_231, 2_653, 33_994, 1_266, 100]
              self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase__  ),		UpperCamelCase__  )






       def      lowercase__     (							self  ):



              """simple docstring"""







              pass






       def      lowercase__     (							self  ):



              """simple docstring"""







              pass






       def      lowercase__     (							self  ):



              """simple docstring"""







              pass






import os
from tempfile import TemporaryDirectory
from unittest import TestCase

import pytest
from absl.testing import parameterized

from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict
from datasets.iterable_dataset import IterableDataset
from datasets.load import dataset_module_factory, import_main_class
from datasets.utils.file_utils import cached_path


__lowerCAmelCase			:     Any           =   [
    {'dataset': 'wikipedia', 'config_name': '20220301.de'},
    {'dataset': 'wikipedia', 'config_name': '20220301.en'},
    {'dataset': 'wikipedia', 'config_name': '20220301.fr'},
    {'dataset': 'wikipedia', 'config_name': '20220301.frr'},
    {'dataset': 'wikipedia', 'config_name': '20220301.it'},
    {'dataset': 'wikipedia', 'config_name': '20220301.simple'},
    {'dataset': 'snli', 'config_name': 'plain_text'},
    {'dataset': 'eli5', 'config_name': 'LFQA_reddit'},
    {'dataset': 'wiki40b', 'config_name': 'en'},
    {'dataset': 'wiki_dpr', 'config_name': 'psgs_w100.nq.compressed'},
    {'dataset': 'wiki_dpr', 'config_name': 'psgs_w100.nq.no_index'},
    {'dataset': 'wiki_dpr', 'config_name': 'psgs_w100.multiset.no_index'},
    {'dataset': 'natural_questions', 'config_name': 'default'},
]

def a__    (       A_=True					):






  '''simple docstring'''





  if with_config:
    return [
        {
            "testcase_name": d["dataset"] + "/" + d["config_name"],
            "dataset": d["dataset"],
            "config_name": d["config_name"],
        }
        for d in DATASETS_ON_HF_GCP
    ]
  else:
    return [
        {"testcase_name": dataset, "dataset": dataset} for dataset in {d["dataset"] for d in DATASETS_ON_HF_GCP}
    ]




@parameterized.named_parameters(list_datasets_on_hf_gcp_parameters(with_config=_A     )     )
class        UpperCAmelCase_			( _A     ):


  '''simple docstring'''







  a__           =		None
  a__           =		None
  def 							_lowercase							( self			: List[Any]			,							UpperCamelCase__			: int			,							UpperCamelCase__			: Union[str, Any]    )			->	Tuple:







    """simple docstring"""






    with TemporaryDirectory() as tmp_dir:
      __magic_name__				     =       dataset_module_factory(UpperCamelCase__			,							cache_dir=UpperCamelCase__    )

      __magic_name__				     =       import_main_class(dataset_module.module_path			,							dataset=UpperCamelCase__    )

      __magic_name__				     =       builder_cls(
          cache_dir=UpperCamelCase__			,							config_name=UpperCamelCase__			,							hash=dataset_module.hash			,							)

      __magic_name__				     =       """/""".join(
          [
              HF_GCP_BASE_URL,
              builder_instance._relative_data_dir(with_hash=UpperCamelCase__    ).replace(os.sep			,							"""/"""    ),
              config.DATASET_INFO_FILENAME,
          ]    )
      __magic_name__				     =       cached_path(UpperCamelCase__			,							cache_dir=UpperCamelCase__    )
      self.assertTrue(os.path.exists(UpperCamelCase__    )    )







@pytest.mark.integration
def a__    (       A_					):






  '''simple docstring'''





  __magic_name__				     =       tmp_path_factory.mktemp("""test_hf_gcp"""					) / """test_wikipedia_simple"""
  __magic_name__				     =       dataset_module_factory("""wikipedia""",     cache_dir=A_					)
  __magic_name__				     =       import_main_class(dataset_module.module_path					)
  __magic_name__				     =       builder_cls(
      cache_dir=A_,     config_name="""20220301.frr""",     hash=dataset_module.hash,     )
  # use the HF cloud storage, not the original download_and_prepare that uses apache-beam
  __magic_name__				     =       None
  builder_instance.download_and_prepare()
  __magic_name__				     =       builder_instance.as_dataset()
  assert ds





@pytest.mark.integration
def a__    (       A_					):






  '''simple docstring'''





  __magic_name__				     =       dataset_module_factory("""wikipedia""",     cache_dir=A_					)
  __magic_name__				     =       import_main_class(dataset_module.module_path,     dataset=A_					)
  __magic_name__				     =       builder_cls(
      cache_dir=A_,     config_name="""20220301.frr""",     hash=dataset_module.hash,     )
  __magic_name__				     =       builder_instance.as_streaming_dataset()
  assert ds
  assert isinstance(A_,     A_					)
  assert "train" in ds
  assert isinstance(ds["""train"""],     A_					)
  assert next(iter(ds["""train"""]					)					)

