




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     __lowerCAmelCase (       __magic_name__			,				unittest.TestCase ):

			"""simple docstring"""







			snake_case_   		=       None
			snake_case_   		=       BloomTokenizerFast
			snake_case_   		=       BloomTokenizerFast
			snake_case_   		=       True
			snake_case_   		=       False
			snake_case_   		=       '''tokenizer_file'''
			snake_case_   		=       {'''bos_token''': '''<s>''', '''eos_token''': '''</s>''', '''unk_token''': '''<unk>''', '''pad_token''': '''<pad>'''}


			def       lowercase_    (      self							)    ->      str:



							'''simple docstring'''
							super().setUp()
							__lowerCamelCase		       =    BloomTokenizerFast.from_pretrained('bigscience/tokenizer'							)
							tokenizer.save_pretrained(self.tmpdirname							)


			def       lowercase_    (      self			,						**lowerCamelCase__							)    ->      Optional[int]:



							'''simple docstring'''
							kwargs.update(self.special_tokens_map							)
							return BloomTokenizerFast.from_pretrained(self.tmpdirname			,						**lowerCamelCase__							)


			def       lowercase_    (      self							)    ->      Union[str, Any]:



							'''simple docstring'''
							__lowerCamelCase		       =    self.get_rust_tokenizer()

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

							__lowerCamelCase		       =    tokenizer.batch_encode_plus(lowerCamelCase__							)['input_ids']
							self.assertListEqual(lowerCamelCase__			,						lowerCamelCase__							)

							__lowerCamelCase		       =    tokenizer.batch_decode(lowerCamelCase__							)
							self.assertListEqual(lowerCamelCase__			,						lowerCamelCase__							)


			def       lowercase_    (      self			,						lowerCamelCase__=6							)    ->      Optional[int]:



							'''simple docstring'''
							for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
											with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""							):
															__lowerCamelCase		       =    self.rust_tokenizer_class.from_pretrained(lowerCamelCase__			,						**lowerCamelCase__							)
															# tokenizer_r.pad_token = None # Hotfixing padding = None
															# Simple input
															__lowerCamelCase		       =    'This is a simple input'
															__lowerCamelCase		       =    ['This is a simple input 1', 'This is a simple input 2']
															__lowerCamelCase		       =    ('This is a simple input', 'This is a pair')
															__lowerCamelCase		       =    [
															    ('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(lowerCamelCase__			,						max_length=lowerCamelCase__							)
																			tokenizer_r.encode_plus(lowerCamelCase__			,						max_length=lowerCamelCase__							)

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

															__lowerCamelCase		       =    None  # Hotfixing padding = None
															self.assertRaises(lowerCamelCase__			,						tokenizer_r.encode			,						lowerCamelCase__			,						max_length=lowerCamelCase__			,						padding='max_length'							)

															# Simple input
															self.assertRaises(lowerCamelCase__			,						tokenizer_r.encode_plus			,						lowerCamelCase__			,						max_length=lowerCamelCase__			,						padding='max_length'							)

															# Simple input
															self.assertRaises(
															    lowerCamelCase__			,						tokenizer_r.batch_encode_plus			,						lowerCamelCase__			,						max_length=lowerCamelCase__			,						padding='max_length'			,						)

															# Pair input
															self.assertRaises(lowerCamelCase__			,						tokenizer_r.encode			,						lowerCamelCase__			,						max_length=lowerCamelCase__			,						padding='max_length'							)

															# Pair input
															self.assertRaises(lowerCamelCase__			,						tokenizer_r.encode_plus			,						lowerCamelCase__			,						max_length=lowerCamelCase__			,						padding='max_length'							)

															# Pair input
															self.assertRaises(
															    lowerCamelCase__			,						tokenizer_r.batch_encode_plus			,						lowerCamelCase__			,						max_length=lowerCamelCase__			,						padding='max_length'			,						)


			def       lowercase_    (      self							)    ->      Tuple:



							'''simple docstring'''
							__lowerCamelCase		       =    self.get_rust_tokenizer()
							__lowerCamelCase		       =    load_dataset('xnli'			,						'all_languages'			,						split='test'			,						streaming=lowerCamelCase__							)

							__lowerCamelCase		       =    next(iter(lowerCamelCase__							)							)['premise']  # pick up one data
							__lowerCamelCase		       =    list(sample_data.values()							)

							__lowerCamelCase		       =    list(map(tokenizer.encode			,						lowerCamelCase__							)							)
							__lowerCamelCase		       =    [tokenizer.decode(lowerCamelCase__			,						clean_up_tokenization_spaces=lowerCamelCase__							) for x in output_tokens]
							self.assertListEqual(lowerCamelCase__			,						lowerCamelCase__							)






			def       lowercase_    (      self							)    ->      str:



							'''simple docstring'''
							# 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							)









def      _A       (		SCREAMING_SNAKE_CASE     :   list						):





  """simple docstring"""



  if not isinstance(SCREAMING_SNAKE_CASE       ,       SCREAMING_SNAKE_CASE						):
    raise ValueError("Input series is not valid, valid series - [2, 4, 6]"						)
  if len(SCREAMING_SNAKE_CASE						) == 0:
    raise ValueError("Input list must be a non empty list"						)
  if len(SCREAMING_SNAKE_CASE						) == 1:
    return True
  a__	:					Union[str, Any]										=series[1] - series[0]
  for index in range(len(SCREAMING_SNAKE_CASE						) - 1						):
    if series[index + 1] - series[index] != common_diff:
      return False
  return True
def      _A       (		SCREAMING_SNAKE_CASE     :   list						):





  """simple docstring"""



  if not isinstance(SCREAMING_SNAKE_CASE       ,       SCREAMING_SNAKE_CASE						):
    raise ValueError("Input series is not valid, valid series - [2, 4, 6]"						)
  if len(SCREAMING_SNAKE_CASE						) == 0:
    raise ValueError("Input list must be a non empty list"						)
  a__	:					Any										=0
  for val in series:
    answer += val
  return answer / len(SCREAMING_SNAKE_CASE						)


if __name__ == "__main__":
     import doctest

     doctest.testmod()






