

'''simple docstring'''

import unittest

from datasets import load_dataset

from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin





@require_tokenizers
class 							_snake_case (       _a	,  unittest.TestCase						):
   _A       :     List[Any]       =					None
   _A       :     Tuple       =					BloomTokenizerFast
   _A       :     List[Any]       =					BloomTokenizerFast
   _A       :     List[Any]       =					True
   _A       :     Tuple       =					False
   _A       :     List[str]       =					'''tokenizer_file'''
   _A       :     int       =					{'''bos_token''': '''<s>''', '''eos_token''': '''</s>''', '''unk_token''': '''<unk>''', '''pad_token''': '''<pad>'''}
   def     __UpperCamelCase						( self			:      List[str]							):
    super().setUp()
    SCREAMING_SNAKE_CASE:str						      =					BloomTokenizerFast.from_pretrained("bigscience/tokenizer"							)
    tokenizer.save_pretrained(self.tmpdirname							)
   def     __UpperCamelCase						( self			:      List[Any]     ,**SCREAMING_SNAKE_CASE__			:      Union[str, Any]							):
    kwargs.update(self.special_tokens_map							)
    return BloomTokenizerFast.from_pretrained(self.tmpdirname     ,**SCREAMING_SNAKE_CASE__							)
   def     __UpperCamelCase						( self			:      Optional[int]							):
    SCREAMING_SNAKE_CASE:int						      =					self.get_rust_tokenizer()

    SCREAMING_SNAKE_CASE:Optional[int]						      =					["The quick brown fox</s>", "jumps over the lazy dog</s>"]
    SCREAMING_SNAKE_CASE:str						      =					[[2_175, 23_714, 73_173, 144_252, 2], [77, 132_619, 3_478, 368, 109_586, 35_433, 2]]

    SCREAMING_SNAKE_CASE:Any						      =					tokenizer.batch_encode_plus(SCREAMING_SNAKE_CASE__							)["input_ids"]
    self.assertListEqual(SCREAMING_SNAKE_CASE__     ,SCREAMING_SNAKE_CASE__							)

    SCREAMING_SNAKE_CASE:Dict						      =					tokenizer.batch_decode(SCREAMING_SNAKE_CASE__							)
    self.assertListEqual(SCREAMING_SNAKE_CASE__     ,SCREAMING_SNAKE_CASE__							)
   def     __UpperCamelCase						( self			:      List[Any]     ,SCREAMING_SNAKE_CASE__			:      List[Any]=6							):
    for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
     with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''							):
      SCREAMING_SNAKE_CASE:str						      =					self.rust_tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE__     ,**SCREAMING_SNAKE_CASE__							)
      # tokenizer_r.pad_token = None # Hotfixing padding = None
      # Simple input
      SCREAMING_SNAKE_CASE:Optional[Any]						      =					"This is a simple input"
      SCREAMING_SNAKE_CASE:List[str]						      =					["This is a simple input 1", "This is a simple input 2"]
      SCREAMING_SNAKE_CASE:int						      =					("This is a simple input", "This is a pair")
      SCREAMING_SNAKE_CASE:Union[str, Any]						      =					[
          ("This is a simple input 1", "This is a simple input 2"),
          ("This is a simple pair 1", "This is a simple pair 2"),
      ]

      # Simple input tests
      try:
       tokenizer_r.encode(SCREAMING_SNAKE_CASE__     ,max_length=SCREAMING_SNAKE_CASE__							)
       tokenizer_r.encode_plus(SCREAMING_SNAKE_CASE__     ,max_length=SCREAMING_SNAKE_CASE__							)

       tokenizer_r.batch_encode_plus(SCREAMING_SNAKE_CASE__     ,max_length=SCREAMING_SNAKE_CASE__							)
       tokenizer_r.encode(SCREAMING_SNAKE_CASE__     ,max_length=SCREAMING_SNAKE_CASE__							)
       tokenizer_r.batch_encode_plus(SCREAMING_SNAKE_CASE__     ,max_length=SCREAMING_SNAKE_CASE__							)
      except ValueError:
       self.fail("Bloom Tokenizer should be able to deal with padding"							)

      SCREAMING_SNAKE_CASE:Optional[Any]						      =					None  # Hotfixing padding = None
      self.assertRaises(SCREAMING_SNAKE_CASE__     ,tokenizer_r.encode     ,SCREAMING_SNAKE_CASE__     ,max_length=SCREAMING_SNAKE_CASE__     ,padding="max_length"							)

      # Simple input
      self.assertRaises(SCREAMING_SNAKE_CASE__     ,tokenizer_r.encode_plus     ,SCREAMING_SNAKE_CASE__     ,max_length=SCREAMING_SNAKE_CASE__     ,padding="max_length"							)

      # Simple input
      self.assertRaises(
          SCREAMING_SNAKE_CASE__     ,tokenizer_r.batch_encode_plus     ,SCREAMING_SNAKE_CASE__     ,max_length=SCREAMING_SNAKE_CASE__     ,padding="max_length"     ,)

      # Pair input
      self.assertRaises(SCREAMING_SNAKE_CASE__     ,tokenizer_r.encode     ,SCREAMING_SNAKE_CASE__     ,max_length=SCREAMING_SNAKE_CASE__     ,padding="max_length"							)

      # Pair input
      self.assertRaises(SCREAMING_SNAKE_CASE__     ,tokenizer_r.encode_plus     ,SCREAMING_SNAKE_CASE__     ,max_length=SCREAMING_SNAKE_CASE__     ,padding="max_length"							)

      # Pair input
      self.assertRaises(
          SCREAMING_SNAKE_CASE__     ,tokenizer_r.batch_encode_plus     ,SCREAMING_SNAKE_CASE__     ,max_length=SCREAMING_SNAKE_CASE__     ,padding="max_length"     ,)
   def     __UpperCamelCase						( self			:      Dict							):
    SCREAMING_SNAKE_CASE:List[Any]						      =					self.get_rust_tokenizer()
    SCREAMING_SNAKE_CASE:Any						      =					load_dataset("xnli"     ,"all_languages"     ,split="test"     ,streaming=SCREAMING_SNAKE_CASE__							)

    SCREAMING_SNAKE_CASE:List[str]						      =					next(iter(SCREAMING_SNAKE_CASE__							)							)["premise"]  # pick up one data
    SCREAMING_SNAKE_CASE:Union[str, Any]						      =					list(sample_data.values()							)

    SCREAMING_SNAKE_CASE:Tuple						      =					list(map(tokenizer.encode     ,SCREAMING_SNAKE_CASE__							)							)
    SCREAMING_SNAKE_CASE:str						      =					[tokenizer.decode(SCREAMING_SNAKE_CASE__     ,clean_up_tokenization_spaces=SCREAMING_SNAKE_CASE__							) for x in output_tokens]
    self.assertListEqual(SCREAMING_SNAKE_CASE__     ,SCREAMING_SNAKE_CASE__							)







   def     __UpperCamelCase						( self			:      int							):
    # The test has to be overriden because BLOOM uses ALiBi positional embeddings that does not have
    # any sequence length constraints. This test of the parent class will fail since it relies on the
    # maximum sequence length of the positoonal embeddings.
    self.assertGreaterEqual(len(self.tokenizer_class.pretrained_vocab_files_map							)     ,1							)
    self.assertGreaterEqual(len(list(self.tokenizer_class.pretrained_vocab_files_map.values()							)[0]							)     ,1							)









'''simple docstring'''

def    A_  ( snake_case = 100 ):
  SCREAMING_SNAKE_CASE:Dict						      =					0
  SCREAMING_SNAKE_CASE:Optional[int]						      =					0
  for i in range(1      ,       n + 1 ):
    sum_of_squares += i**2
    sum_of_ints += i
  return sum_of_ints**2 - sum_of_squares


if __name__ == "__main__":
    print(f'''{solution() = }''')






