




'''simple docstring'''




import json
import os
from typing import Dict, List, Optional, Tuple

import regex as re

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


a_      :		Tuple							      =       logging.get_logger(__name__)


a_      :		Tuple							      =       {
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
    'tokenizer_config_file': 'tokenizer_config.json',
}

a_      :		int							      =       {
    'vocab_file': {
        'facebook/blenderbot_small-90M': 'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json'
    },
    'merges_file': {
        'facebook/blenderbot_small-90M': 'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt'
    },
    'tokenizer_config_file': {
        'facebook/blenderbot_small-90M': (
            'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json'
        )
    },
}

a_      :		Optional[int]							      =       {'facebook/blenderbot_small-90M': 5_12}





def      a_							(      __snake_case							:			Tuple   )							->						Union[str, Any]:



       """simple docstring"""
       lowerCamelCase_							=set()
       lowerCamelCase_							=word[0]
       for char in word[1:]:
              pairs.add((prev_char, char)   )
              lowerCamelCase_							=char

       lowerCamelCase_							=set(A_   )
       return pairs


class   __UpperCamelCase       ( _A				):
       lowercase	:    List[str]      						=VOCAB_FILES_NAMES
       lowercase	:    List[str]      						=PRETRAINED_VOCAB_FILES_MAP
       lowercase	:    Dict      						=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       lowercase	:    Union[str, Any]      						=['input_ids', 'attention_mask']






       def __init__(							self,		lowerCAmelCase,		lowerCAmelCase,		lowerCAmelCase="__start__",		lowerCAmelCase="__end__",		lowerCAmelCase="__unk__",		lowerCAmelCase="__null__",		**lowerCAmelCase,		):



              """simple docstring"""







              super().__init__(unk_token=UpperCamelCase__,		bos_token=UpperCamelCase__,		eos_token=UpperCamelCase__,		pad_token=UpperCamelCase__,		**UpperCamelCase__  )

              with open(UpperCamelCase__,		encoding='''utf-8'''  ) as vocab_handle:
                     lowerCamelCase_							=json.load(UpperCamelCase__  )
              lowerCamelCase_							={v: k for k, v in self.encoder.items()}
              with open(UpperCamelCase__,		encoding='''utf-8'''  ) as merges_handle:
                     lowerCamelCase_							=merges_handle.read().split('''\n'''  )[1:-1]
              lowerCamelCase_							=[tuple(merge.split()  ) for merge in merges]
              lowerCamelCase_							=dict(zip(UpperCamelCase__,		range(len(UpperCamelCase__  )  )  )  )
              lowerCamelCase_							={}






       @property
       def      lowercase__     (							self  ):



              """simple docstring"""







              return len(self.encoder  )






       def      lowercase__     (							self  ):



              """simple docstring"""







              return dict(self.encoder,		**self.added_tokens_encoder  )






       def      lowercase__     (							self,		lowerCAmelCase  ):



              """simple docstring"""







              if token in self.cache:
                     return self.cache[token]
              lowerCamelCase_							=re.sub('''([.,!?()])''',		R''' \1''',		UpperCamelCase__  )
              lowerCamelCase_							=re.sub('''(\')''',		R''' \1 ''',		UpperCamelCase__  )
              lowerCamelCase_							=re.sub(R'''\s{2,}''',		''' ''',		UpperCamelCase__  )
              if "\n" in token:
                     lowerCamelCase_							=token.replace('''\n''',		''' __newln__'''  )

              lowerCamelCase_							=token.split(''' '''  )
              lowerCamelCase_							=[]
              for token in tokens:
                     if not len(UpperCamelCase__  ):
                            continue

                     lowerCamelCase_							=token.lower()
                     lowerCamelCase_							=tuple(UpperCamelCase__  )
                     lowerCamelCase_							=tuple(list(word[:-1]  ) + [word[-1] + '''</w>''']  )
                     lowerCamelCase_							=get_pairs(UpperCamelCase__  )

                     if not pairs:
                            words.append(UpperCamelCase__  )
                            continue

                     while True:
                            lowerCamelCase_							=min(UpperCamelCase__,		key=lambda lowerCAmelCase  : self.bpe_ranks.get(UpperCamelCase__,		float('''inf'''  )  )  )
                            if bigram not in self.bpe_ranks:
                                   break
                            lowerCamelCase_,      lowerCamelCase_							=bigram
                            lowerCamelCase_							=[]
                            lowerCamelCase_							=0

                            while i < len(UpperCamelCase__  ):
                                   try:
                                          lowerCamelCase_							=word.index(UpperCamelCase__,		UpperCamelCase__  )
                                          new_word.extend(word[i:j]  )
                                          lowerCamelCase_							=j
                                   except ValueError:
                                          new_word.extend(word[i:]  )
                                          break

                                   if word[i] == first and i < len(UpperCamelCase__  ) - 1 and word[i + 1] == second:
                                          new_word.append(first + second  )
                                          i += 2
                                   else:
                                          new_word.append(word[i]  )
                                          i += 1
                            lowerCamelCase_							=tuple(UpperCamelCase__  )
                            lowerCamelCase_							=new_word
                            if len(UpperCamelCase__  ) == 1:
                                   break
                            else:
                                   lowerCamelCase_							=get_pairs(UpperCamelCase__  )
                     lowerCamelCase_							='''@@ '''.join(UpperCamelCase__  )
                     lowerCamelCase_							=word[:-4]

                     lowerCamelCase_							=word
                     words.append(UpperCamelCase__  )
              return " ".join(UpperCamelCase__  )






       def      lowercase__     (							self,		lowerCAmelCase  ):



              """simple docstring"""







              lowerCamelCase_							=[]

              lowerCamelCase_							=re.findall(R'''\S+\n?''',		UpperCamelCase__  )

              for token in words:
                     split_tokens.extend(list(self.bpe(UpperCamelCase__  ).split(''' '''  )  )  )
              return split_tokens






       def      lowercase__     (							self,		lowerCAmelCase  ):



              """simple docstring"""







              lowerCamelCase_							=token.lower()
              return self.encoder.get(UpperCamelCase__,		self.encoder.get(self.unk_token  )  )






       def      lowercase__     (							self,		lowerCAmelCase  ):



              """simple docstring"""







              return self.decoder.get(UpperCamelCase__,		self.unk_token  )






       def      lowercase__     (							self,		lowerCAmelCase  ):



              """simple docstring"""







              lowerCamelCase_							=''' '''.join(UpperCamelCase__  ).replace('''@@ ''',		''''''  ).strip()
              return out_string






       def      lowercase__     (							self,		lowerCAmelCase,		lowerCAmelCase = None  ):



              """simple docstring"""







              if not os.path.isdir(UpperCamelCase__  ):
                     logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''  )
                     return
              lowerCamelCase_							=os.path.join(
                  UpperCamelCase__,		(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']  )
              lowerCamelCase_							=os.path.join(
                  UpperCamelCase__,		(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']  )

              with open(UpperCamelCase__,		'''w''',		encoding='''utf-8'''  ) as f:
                     f.write(json.dumps(self.encoder,		indent=2,		sort_keys=UpperCamelCase__,		ensure_ascii=UpperCamelCase__  ) + '''\n'''  )

              lowerCamelCase_							=0
              with open(UpperCamelCase__,		'''w''',		encoding='''utf-8'''  ) as writer:
                     writer.write('''#version: 0.2\n'''  )
                     for bpe_tokens, token_index in sorted(self.bpe_ranks.items(),		key=lambda lowerCAmelCase  : kv[1]  ):
                            if index != token_index:
                                   logger.warning(
                                       f'''Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'''
                                       ''' Please check that the tokenizer is not corrupted!'''  )
                                   lowerCamelCase_							=token_index
                            writer.write(''' '''.join(UpperCamelCase__  ) + '''\n'''  )
                            index += 1

              return vocab_file, merge_file






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"""]					)					)

