



import os
import unittest

from transformers.models.bertweet.tokenization_bertweet import VOCAB_FILES_NAMES, BertweetTokenizer

from ...test_tokenization_common import TokenizerTesterMixin

class       UpperCamelCase  (					_SCREAMING_SNAKE_CASE      , unittest.TestCase				):





     """simple docstring"""






     _lowerCamelCase					: Tuple				   =BertweetTokenizer
     _lowerCamelCase					: Any				   =False





     def 						A__  (					self :							Dict ):
          super().setUp()

          # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
          A__				=   ['''I''', '''m''', '''V@@''', '''R@@''', '''r''', '''e@@''']
          A__				=   dict(zip(__A	,      range(len(__A ) ) ) )
          A__				=   ['''#version: 0.2''', '''a m</w>''']
          A__				=   {'''unk_token''': '''<unk>'''}

          A__				=   os.path.join(self.tmpdirname	,      VOCAB_FILES_NAMES['''vocab_file'''] )
          A__				=   os.path.join(self.tmpdirname	,      VOCAB_FILES_NAMES['''merges_file'''] )
          with open(self.vocab_file	,      '''w'''	,      encoding='''utf-8''' ) as fp:
               for token in vocab_tokens:
                    fp.write(F'''{token} {vocab_tokens[token]}\n''' )
          with open(self.merges_file	,      '''w'''	,      encoding='''utf-8''' ) as fp:
               fp.write('''\n'''.join(__A ) )





     def 						A__  (					self :							Dict	,      **_lowerCamelCase :							int ):
          kwargs.update(self.special_tokens_map )
          return BertweetTokenizer.from_pretrained(self.tmpdirname	,      **__A )





     def 						A__  (					self :							Optional[int]	,      _lowerCamelCase :							Optional[Any] ):
          A__				=   '''I am VinAI Research'''
          A__				=   '''I <unk> m V<unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>'''
          return input_text, output_text





     def 						A__  (					self :							str ):
          A__				=   BertweetTokenizer(self.vocab_file	,      self.merges_file	,      **self.special_tokens_map )
          A__				=   '''I am VinAI Research'''
          A__				=   '''I a@@ m V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h'''.split()
          A__				=   tokenizer.tokenize(__A )
          self.assertListEqual(__A	,      __A )

          A__				=   tokens + [tokenizer.unk_token]

          A__				=   [4, 3, 5, 6, 3, 3, 3, 4, 7, 9, 3, 9, 3, 3, 3, 3, 3]
          self.assertListEqual(tokenizer.convert_tokens_to_ids(__A )	,      __A )








"""simple docstring"""







import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


__snake_case	:				Optional[Any]  					=			500_000

__snake_case					,  __snake_case	:				Any  					=			os.path.split(__file__)
__snake_case	:				Optional[Any]  					=			os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENAME.replace('.py', '.json'))



@get_duration
def   a_	(			__a      ):
     A__				=   dataset.select(range(0		,							len(__a      )		,							2      )      )



@get_duration
def   a_	(			__a      ):
     A__				=   dataset.sort('''numbers'''      )



@get_duration
def   a_	(			__a      ):
     A__				=   dataset.shuffle()



@get_duration
def   a_	(			__a      ):
     A__				=   dataset.train_test_split(0.1      )



@get_duration
def   a_	(			__a		,							__a=10      ):
     for shard_id in range(__a      ):
          A__				=   dataset.shard(__a		,							__a      )



def   a_	(			):
     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(__a		,							'''dataset.arrow'''      )		,							__a		,							num_examples=__a      )
          print('''Functions'''      )
          for func in functions:
               print(func.__name__      )
               A__				=   func(__a      )

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


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



