




from typing import List

import numpy as np


def    A						(__A   :    dict       )   ->      int:







     """simple docstring"""


     UpperCAmelCase_          =							{key: len(__A       ) for key, value in gen_kwargs.items() if isinstance(__A   ,				__A       )}
     if len(set(lists_lengths.values()       )       ) > 1:
          raise RuntimeError(
              (
                  '''Sharding is ambiguous for this dataset: '''
                  + '''we found several data sources lists of different lengths, and we don\'t know over which list we should parallelize:\n'''
                  + '''\n'''.join(F"""\t- key {key} has length {length}""" for key, length in lists_lengths.items()       )
                  + '''\nTo fix this, check the \'gen_kwargs\' and make sure to use lists only for data sources, '''
                  + '''and use tuples otherwise. In the end there should only be one single list, or several lists with the same length.'''
              )       )
     UpperCAmelCase_          =							max(lists_lengths.values()   ,				default=0       )
     return max(1   ,				__A       )


def    A						(__A   :    int   ,				__A   :    int       )   ->      List[range]:







     """simple docstring"""


     UpperCAmelCase_          =							[]
     for group_idx in range(__A       ):
          UpperCAmelCase_          =							num_shards // max_num_jobs + (group_idx < (num_shards % max_num_jobs))
          if num_shards_to_add == 0:
               break
          UpperCAmelCase_          =							shards_indices_per_group[-1].stop if shards_indices_per_group else 0
          UpperCAmelCase_          =							range(__A   ,				start + num_shards_to_add       )
          shards_indices_per_group.append(__A       )
     return shards_indices_per_group


def    A						(__A   :    dict   ,				__A   :    int       )   ->      List[dict]:







     """simple docstring"""


     UpperCAmelCase_          =							_number_of_shards_in_gen_kwargs(__A       )
     if num_shards == 1:
          return [dict(__A       )]
     else:
          UpperCAmelCase_          =							_distribute_shards(num_shards=__A   ,				max_num_jobs=__A       )
          return [
              {
                  key: [value[shard_idx] for shard_idx in shard_indices_per_group[group_idx]]
                  if isinstance(__A   ,				__A       )
                  else value
                  for key, value in gen_kwargs.items()
              }
              for group_idx in range(len(__A       )       )
          ]


def    A						(__A   :    List[dict]       )   ->      dict:







     """simple docstring"""


     return {
         key: [value for gen_kwargs in gen_kwargs_list for value in gen_kwargs[key]]
         if isinstance(gen_kwargs_list[0][key]   ,				__A       )
         else gen_kwargs_list[0][key]
         for key in gen_kwargs_list[0]
     }


def    A						(__A   :    np.random.Generator   ,				__A   :    dict       )   ->      dict:







     """simple docstring"""


     UpperCAmelCase_          =							{len(__A       ) for value in gen_kwargs.values() if isinstance(__A   ,				__A       )}
     UpperCAmelCase_          =							{}
     for size in list_sizes:
          UpperCAmelCase_          =							list(range(__A       )       )
          rng.shuffle(indices_per_size[size]       )
     # Now let's copy the gen_kwargs and shuffle the lists based on their sizes
     UpperCAmelCase_          =							dict(__A       )
     for key, value in shuffled_kwargs.items():
          if isinstance(__A   ,				__A       ):
               UpperCAmelCase_          =							[value[i] for i in indices_per_size[len(__A       )]]
     return shuffled_kwargs












import os
import unittest

from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer

from ...test_tokenization_common import TokenizerTesterMixin







class __snake_case			(			a ,  unittest.TestCase		):
   UpperCAmelCase__  :    Any          =  PhobertTokenizer
   UpperCAmelCase__  :    List[str]          =  False







   def lowerCamelCase						(      self		:						str):

        """simple docstring"""


        super().setUp()

        # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
        UpperCAmelCase_          =							['''T@@''', '''i''', '''I''', '''R@@''', '''r''', '''e@@''']
        UpperCAmelCase_          =							dict(zip(_snake_case					,						range(len(_snake_case))))
        UpperCAmelCase_          =							['''#version: 0.2''', '''l à</w>''']
        UpperCAmelCase_          =							{'''unk_token''': '''<unk>'''}

        UpperCAmelCase_          =							os.path.join(self.tmpdirname					,						VOCAB_FILES_NAMES['''vocab_file'''])
        UpperCAmelCase_          =							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(_snake_case))







   def lowerCamelCase						(      self		:						int					,						**_snake_case		:						Any):

        """simple docstring"""


        kwargs.update(self.special_tokens_map)
        return PhobertTokenizer.from_pretrained(self.tmpdirname					,						**_snake_case)







   def lowerCamelCase						(      self		:						Optional[Any]					,						_snake_case		:						Union[str, Any]):

        """simple docstring"""


        UpperCAmelCase_          =							'''Tôi là VinAI Research'''
        UpperCAmelCase_          =							'''T<unk> i <unk> <unk> <unk> <unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>'''
        return input_text, output_text







   def lowerCamelCase						(      self		:						List[str]):

        """simple docstring"""


        UpperCAmelCase_          =							PhobertTokenizer(self.vocab_file					,						self.merges_file					,						**self.special_tokens_map)
        UpperCAmelCase_          =							'''Tôi là VinAI Research'''
        UpperCAmelCase_          =							'''T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h'''.split()
        UpperCAmelCase_          =							tokenizer.tokenize(_snake_case)
        print(_snake_case)
        self.assertListEqual(_snake_case					,						_snake_case)

        UpperCAmelCase_          =							tokens + [tokenizer.unk_token]

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






