


import json
import os
import unittest

from transformers import HerbertTokenizer, HerbertTokenizerFast
from transformers.models.herbert.tokenization_herbert import VOCAB_FILES_NAMES
from transformers.testing_utils import get_tests_dir, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class      __snake_case				(   __a	,      unittest.TestCase):
					SCREAMING_SNAKE_CASE_		:       Tuple								=			HerbertTokenizer
					SCREAMING_SNAKE_CASE_		:       List[Any]								=			HerbertTokenizerFast
					SCREAMING_SNAKE_CASE_		:       List[Any]								=			True
					def 	a			(						self       :						Optional[int]  )							->					str:



											'''simple docstring'''





											super().setUp()

											# Use a simpler test file without japanese/chinese characters
											with open(F'''{get_tests_dir()}/fixtures/sample_text_no_unicode.txt'''	,      encoding='utf-8'  ) as f_data:
																	__magic_name__					=      f_data.read().replace('\n\n'	,      '\n'  ).strip()

											__magic_name__					=      [
											    '<s>',
											    '</s>',
											    'l',
											    'o',
											    'w',
											    'e',
											    'r',
											    's',
											    't',
											    'i',
											    'd',
											    'n',
											    'w</w>',
											    'r</w>',
											    't</w>',
											    'lo',
											    'low',
											    'er</w>',
											    'low</w>',
											    'lowest</w>',
											    'newer</w>',
											    'wider</w>',
											    ',</w>',
											    '<unk>',
											]
											__magic_name__					=      dict(zip(_lowerCAmelCase	,      range(len(_lowerCAmelCase  )  )  )  )
											__magic_name__					=      ['l o 123', 'lo w 1456', 'e r</w> 1789', '']

											__magic_name__					=      os.path.join(self.tmpdirname	,      VOCAB_FILES_NAMES['vocab_file']  )
											__magic_name__					=      os.path.join(self.tmpdirname	,      VOCAB_FILES_NAMES['merges_file']  )
											with open(self.vocab_file	,      'w'  ) as fp:
																	fp.write(json.dumps(_lowerCAmelCase  )  )
											with open(self.merges_file	,      'w'  ) as fp:
																	fp.write('\n'.join(_lowerCAmelCase  )  )
					def 	a			(						self       :						Tuple	,      _lowerCAmelCase       :						List[Any]  )							->					List[Any]:



											'''simple docstring'''





											__magic_name__					=      'lower newer'
											__magic_name__					=      'lower newer'
											return input_text, output_text
					def 	a			(						self       :						List[Any]  )							->					List[str]:



											'''simple docstring'''





											__magic_name__					=      self.tokenizer_class(vocab_file=self.vocab_file	,      merges_file=self.merges_file  )

											__magic_name__					=      'lower'
											__magic_name__					=      ['low', 'er</w>']
											__magic_name__					=      tokenizer.tokenize(_lowerCAmelCase  )
											self.assertListEqual(_lowerCAmelCase	,      _lowerCAmelCase  )

											__magic_name__					=      tokens + ['<unk>']
											__magic_name__					=      [1_6, 1_7, 2_3]
											self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCAmelCase  )	,      _lowerCAmelCase  )
					def 	a			(						self       :						List[str]  )							->					Union[str, Any]:



											'''simple docstring'''





											if not self.test_rust_tokenizer:
																	return

											__magic_name__					=      self.get_tokenizer()
											__magic_name__					=      self.get_rust_tokenizer()

											__magic_name__					=      'lower,newer'

											__magic_name__					=      tokenizer.tokenize(_lowerCAmelCase  )
											__magic_name__					=      rust_tokenizer.tokenize(_lowerCAmelCase  )
											self.assertListEqual(_lowerCAmelCase	,      _lowerCAmelCase  )

											__magic_name__					=      tokenizer.encode(_lowerCAmelCase	,      add_special_tokens=_lowerCAmelCase  )
											__magic_name__					=      rust_tokenizer.encode(_lowerCAmelCase	,      add_special_tokens=_lowerCAmelCase  )
											self.assertListEqual(_lowerCAmelCase	,      _lowerCAmelCase  )

											__magic_name__					=      self.get_rust_tokenizer()
											__magic_name__					=      tokenizer.encode(_lowerCAmelCase  )
											__magic_name__					=      rust_tokenizer.encode(_lowerCAmelCase  )
											self.assertListEqual(_lowerCAmelCase	,      _lowerCAmelCase  )







					@slow
					def 	a			(						self       :						Union[str, Any]  )							->					Union[str, Any]:



											'''simple docstring'''





											__magic_name__					=      self.tokenizer_class.from_pretrained('allegro/herbert-base-cased'  )

											__magic_name__					=      tokenizer.encode('konstruowanie sekwencji'	,      add_special_tokens=_lowerCAmelCase  )
											__magic_name__					=      tokenizer.encode('konstruowanie wielu sekwencji'	,      add_special_tokens=_lowerCAmelCase  )

											__magic_name__					=      tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase  )
											__magic_name__					=      tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase	,      _lowerCAmelCase  )

											assert encoded_sentence == [0] + text + [2]
											assert encoded_pair == [0] + text + [2] + text_a + [2]







'''simple docstring'''







import json
import os
from dataclasses import dataclass

import numpy as np
import pyarrow as pa

import datasets
from utils import get_duration


A					       =10_00_00_00_00_00
A					       =1_00_00

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





def 		snake_case_				(_a      :				int       ,  _a      :				int	):
    UpperCAmelCase     			=						pa.Table.from_pydict({'''col''': [0] * chunk_size}	)
    UpperCAmelCase     			=						pa.concat_tables([table] * (num_examples // chunk_size)	)
    return datasets.Dataset(_a       ,  fingerprint='''table_100B'''	)


@dataclass
class      _a    :
       __a							:	int
       __a							:	int
       __a							:	int
       __a							:	int
       def        A (      self		:      List[str]							):



           '''simple docstring'''

           UpperCAmelCase     			=						np.random.default_rng(self.seed							)
           UpperCAmelCase     			=						rng.integers(low=self.low  ,							high=self.high  ,							size=self.size							).tolist()
       def __iter__(      self		:      Tuple							):



           '''simple docstring'''

           return iter(self._sampled_values							)







       def __len__(      self		:      Dict							):



           '''simple docstring'''

           return self.size






@get_duration
def 		snake_case_				(_a      :				datasets.Dataset	):
    UpperCAmelCase     			=						dataset[0]





@get_duration
def 		snake_case_				(_a      :				datasets.Dataset	):
    UpperCAmelCase     			=						dataset[-1]





@get_duration
def 		snake_case_				(_a      :				datasets.Dataset	):
    UpperCAmelCase     			=						dataset[range(len(_a	) // 2       ,  len(_a	) // 2 + 1_0_2_4	)]





@get_duration
def 		snake_case_				(_a      :				datasets.Dataset	):
    UpperCAmelCase     			=						dataset[RandIter(0       ,  len(_a	)       ,  1_0_2_4       ,  seed=4_2	)]





def 		snake_case_				():
    UpperCAmelCase     			=						{'''num examples''': SPEED_TEST_N_EXAMPLES}
    UpperCAmelCase     			=						(get_first_row, get_last_row, get_batch_of_aaaa_rows, get_batch_of_aaaa_random_rows)
    print('''generating dataset'''	)
    UpperCAmelCase     			=						generate_100B_dataset(num_examples=_a       ,  chunk_size=_a	)
    print('''Functions'''	)
    for func in functions:
        print(func.__name__	)
        UpperCAmelCase     			=						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_table_100B()




