






'''simple docstring'''




import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


lowerCamelCase_							      =      50_00_00

lowerCamelCase_      ,    lowerCamelCase_							      =      os.path.split(__file__)
lowerCamelCase_							      =      os.path.join(RESULTS_BASEPATH, '''results''', RESULTS_FILENAME.replace('''.py''', '''.json'''))

@get_duration
def       __lowercase		(    __lowercase ) ->		Any:

      '''simple docstring'''


      _A      =			dataset.select(range(0     ,						len(__lowercase )     ,						2 ) )

@get_duration
def       __lowercase		(    __lowercase ) ->		List[Any]:

      '''simple docstring'''


      _A      =			dataset.sort("numbers" )

@get_duration
def       __lowercase		(    __lowercase ) ->		List[str]:

      '''simple docstring'''


      _A      =			dataset.shuffle()

@get_duration
def       __lowercase		(    __lowercase ) ->		Optional[Any]:

      '''simple docstring'''


      _A      =			dataset.train_test_split(0.1 )

@get_duration
def       __lowercase		(    __lowercase     ,						__lowercase=10 ) ->		Any:

      '''simple docstring'''


      for shard_id in range(__lowercase ):
            _A      =			dataset.shard(__lowercase     ,						__lowercase )

def       __lowercase		(    ) ->		List[Any]:

      '''simple docstring'''


      _A      =			{"num examples": SPEED_TEST_N_EXAMPLES}
      _A      =			(select, sort, shuffle, train_test_split, shard)
      with tempfile.TemporaryDirectory() as tmp_dir:
            print("generating dataset" )
            _A      =			datasets.Features({"text": datasets.Value("string" ), "numbers": datasets.Value("float32" )} )
            _A      =			generate_example_dataset(
                os.path.join(__lowercase     ,						"dataset.arrow" )     ,						__lowercase     ,						num_examples=__lowercase )
            print("Functions" )
            for func in functions:
                  print(func.__name__ )
                  _A      =			func(__lowercase )

      with open(__lowercase     ,						"wb" ) as f:
            f.write(json.dumps(__lowercase ).encode("utf-8" ) )


if __name__ == "__main__":  # useful to run the profiler
    benchmark_indices_mapping()













'''simple docstring'''




import os
from shutil import copyfile
from typing import Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
    from .tokenization_reformer import ReformerTokenizer
else:
    lowerCamelCase_							      =      None


lowerCamelCase_							      =      logging.get_logger(__name__)


lowerCamelCase_							      =      '''▁'''

lowerCamelCase_							      =      {'''vocab_file''': '''spiece.model''', '''tokenizer_file''': '''tokenizer.json'''}

lowerCamelCase_							      =      {
    '''vocab_file''': {
        '''google/reformer-crime-and-punishment''': (
            '''https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model'''
        )
    },
    '''tokenizer_file''': {
        '''google/reformer-crime-and-punishment''': (
            '''https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/tokenizer.json'''
        )
    },
}

lowerCamelCase_							      =      {
    '''google/reformer-crime-and-punishment''': 52_42_88,
}

class      _UpperCAmelCase    (  snake_case_		):




   """simple docstring"""

   snake_case					       =		VOCAB_FILES_NAMES
   snake_case					       =		PRETRAINED_VOCAB_FILES_MAP
   snake_case					       =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   snake_case					       =		['''input_ids''', '''attention_mask''']
   snake_case					       =		ReformerTokenizer

   def __init__(	self				:			List[str]   ,   __UpperCAmelCase				:			List[str]=None   ,   __UpperCAmelCase				:			Any=None   ,   __UpperCAmelCase				:			List[Any]="</s>"   ,   __UpperCAmelCase				:			Optional[Any]="<unk>"   ,   __UpperCAmelCase				:			List[Any]=[]   ,   **__UpperCAmelCase				:			int   ,   ):





         '''simple docstring'''





         super().__init__(
             __UpperCAmelCase   ,   tokenizer_file=__UpperCAmelCase   ,   eos_token=__UpperCAmelCase   ,   unk_token=__UpperCAmelCase   ,   additional_special_tokens=__UpperCAmelCase   ,   **__UpperCAmelCase   ,   )

         _A      =			vocab_file
         _A      =			False if not self.vocab_file else True

   def 		lowerCAmelCase				(	self				:			Any   ,   __UpperCAmelCase				:			str   ,   __UpperCAmelCase				:			Optional[str] = None	):





         '''simple docstring'''





         if not self.can_save_slow_tokenizer:
               raise ValueError(
                   "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
                   "tokenizer."	)

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

         if os.path.abspath(self.vocab_file	) != os.path.abspath(__UpperCAmelCase	):
               copyfile(self.vocab_file   ,   __UpperCAmelCase	)

         return (out_vocab_file,)





