code: 
  
  
  
  
  
  '''simple docstring'''
  
  
  
  
  
  import unittest
  
  from transformers import ErnieMTokenizer
  from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
  
  from ...test_tokenization_common import TokenizerTesterMixin
  
  
  UpperCAmelCase			:			Tuple	  = get_tests_dir("""fixtures/spiece.model""")
  
  
  
  
  
  
  
  @require_sentencepiece
  @require_tokenizers
  class        __lowerCAmelCase (					lowerCamelCase__		,       unittest.TestCase):
        _lowercase       :      Optional[Any]        =    ErnieMTokenizer
        _lowercase       :      Dict        =    False
        _lowercase       :      int        =    True
        _lowercase       :      List[Any]        =    False
        _lowercase       :      Optional[int]        =    False
  
  
  
  
  
  
  
        def      _lowercase						(					self							)     ->		Dict:
  
  
  
          '''simple docstring'''
  
  
  
  
          super().setUp()
  
          # We have a SentencePiece fixture for testing
          a__			:      Any            =ErnieMTokenizer(lowercase_	,   unk_token="<unk>"	,   pad_token="<pad>"							)
          tokenizer.save_pretrained(self.tmpdirname							)
  
  
  
  
  
  
  
        def      _lowercase						(					self	,   lowerCAmelCase__							)     ->		Dict:
  
  
  
          '''simple docstring'''
  
  
  
  
          a__			:      Tuple            ="this is a test"
          a__			:      Optional[Any]            ="this is a test"
          return input_text, output_text
  
  
  
  
  
  
  
        def      _lowercase						(					self							)     ->		Dict:
  
  
  
          '''simple docstring'''
  
  
  
  
          a__			:      Any            ="<pad>"
          a__			:      int            =0
  
          self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowercase_							)	,   lowercase_							)
          self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowercase_							)	,   lowercase_							)
  
  
  
  
  
  
  
        def      _lowercase						(					self							)     ->		List[str]:
  
  
  
          '''simple docstring'''
  
  
  
  
          a__			:      List[Any]            =list(self.get_tokenizer().get_vocab().keys()							)
  
          self.assertEqual(vocab_keys[0]	,   "<pad>"							)
          self.assertEqual(vocab_keys[1]	,   "<unk>"							)
          self.assertEqual(vocab_keys[-1]	,   "▁eloquent"							)
          self.assertEqual(len(lowercase_							)	,   3_0_0_0_0							)
  
  
  
  
  
  
  
        def      _lowercase						(					self							)     ->		List[str]:
  
  
  
          '''simple docstring'''
  
  
  
  
          self.assertEqual(self.get_tokenizer().vocab_size	,   3_0_0_0_0							)
  
  
  
  
  
  
  
        def      _lowercase						(					self							)     ->		Dict:
  
  
  
          '''simple docstring'''
  
  
  
  
          if not self.test_rust_tokenizer:
            return
  
          a__			:      Union[str, Any]            =self.get_tokenizer()
          a__			:      int            =self.get_rust_tokenizer()
  
          a__			:      Optional[Any]            ="I was born in 92000, and this is falsé."
  
          a__			:      Dict            =tokenizer.tokenize(lowercase_							)
          a__			:      Union[str, Any]            =rust_tokenizer.tokenize(lowercase_							)
          self.assertListEqual(lowercase_	,   lowercase_							)
  
          a__			:      Tuple            =tokenizer.encode(lowercase_	,   add_special_tokens=lowercase_							)
          a__			:      Optional[Any]            =rust_tokenizer.encode(lowercase_	,   add_special_tokens=lowercase_							)
          self.assertListEqual(lowercase_	,   lowercase_							)
  
          a__			:      Union[str, Any]            =self.get_rust_tokenizer()
          a__			:      Any            =tokenizer.encode(lowercase_							)
          a__			:      str            =rust_tokenizer.encode(lowercase_							)
          self.assertListEqual(lowercase_	,   lowercase_							)
  
  
  
  
  
  
  
        def      _lowercase						(					self							)     ->		Any:
  
  
  
          '''simple docstring'''
  
  
  
  
          a__			:      Optional[int]            =ErnieMTokenizer(lowercase_	,   do_lower_case=lowercase_	,   unk_token="<unk>"	,   pad_token="<pad>"							)
  
          a__			:      Dict            =tokenizer.tokenize("This is a test"							)
          self.assertListEqual(lowercase_	,   ["▁this", "▁is", "▁a", "▁test"]							)
  
          self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase_							)	,   [4_8, 2_5, 2_1, 1_2_8_9]							)
  
          a__			:      Tuple            =tokenizer.tokenize("I was born in 92000, and this is falsé."							)
          # ErnieMTokenizer(paddlenlp implementation) outputs '9' instead of '_9' so to mimic that '_9' is changed to '9'
          self.assertListEqual(
              lowercase_	,   ["▁i", "▁was", "▁born", "▁in", "9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "é", "."]							)
          a__			:      Any            =tokenizer.convert_tokens_to_ids(lowercase_							)
          self.assertListEqual(lowercase_	,   [3_1, 2_3, 3_8_6, 1_9, 5_1_8, 3_0_5_0, 1_5, 1_7, 4_8, 2_5, 8_2_5_6, 1_8, 1, 9]							)
  
          a__			:      Union[str, Any]            =tokenizer.convert_ids_to_tokens(lowercase_							)
          self.assertListEqual(
              lowercase_	,   ["▁i", "▁was", "▁born", "▁in", "9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", "."]	,   )
  
  
  
  
  
  
  
        def      _lowercase						(					self							)     ->		Tuple:
  
  
  
          '''simple docstring'''
  
  
  
  
          a__			:      Any            =ErnieMTokenizer(lowercase_	,   unk_token="<unk>"	,   pad_token="<pad>"							)
  
          a__			:      Any            =tokenizer.encode("sequence builders"							)
          a__			:      Optional[int]            =tokenizer.encode("multi-sequence build"							)
  
          a__			:      Dict            =tokenizer.build_inputs_with_special_tokens(lowercase_							)
          a__			:      int            =tokenizer.build_inputs_with_special_tokens(lowercase_	,   lowercase_							)
  
          assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
          assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + [
              tokenizer.sep_token_id
          ] + text_a + [tokenizer.sep_token_id]
  
  
  
  
  
  
  
        @slow
        def      _lowercase						(					self							)     ->		str:
  
  
  
          '''simple docstring'''
  
  
  
  
          a__			:      List[str]            ={"input_ids": [[0, 1_1_0_6_2, 8_2_7_7_2, 7, 1_5, 8_2_7_7_2, 5_3_8, 5_1_5_2_9, 2_3_7, 1_7_1_9_8, 1_2_9_0, 2_0_6, 9, 2_1_5_1_7_5, 1_3_1_4, 1_3_6, 1_7_1_9_8, 1_2_9_0, 2_0_6, 9, 5_6_3_5_9, 4_2, 1_2_2_0_0_9, 9, 1_6_4_6_6, 1_6, 8_7_3_4_4, 4_5_3_7, 9, 4_7_1_7, 7_8_3_8_1, 6, 1_5_9_9_5_8, 7, 1_5, 2_4_4_8_0, 6_1_8, 4, 5_2_7, 2_2_6_9_3, 9, 3_0_4, 4, 2_7_7_7, 2_4_4_8_0, 9_8_7_4, 4, 4_3_5_2_3, 5_9_4, 4, 8_0_3, 1_8_3_9_2, 3_3_1_8_9, 1_8, 4, 4_3_5_2_3, 2_4_4_4_7, 5, 5, 5, 1_6, 1_0_0, 2_4_9_5_5, 8_3_6_5_8, 9_6_2_6, 1_4_4_0_5_7, 1_5, 8_3_9, 2_2_3_3_5, 1_6, 1_3_6, 2_4_9_5_5, 8_3_6_5_8, 8_3_4_7_9, 1_5, 3_9_1_0_2, 7_2_4, 1_6, 6_7_8, 6_4_5, 6_4_6_0, 1_3_2_8, 4_5_8_9, 4_2, 1_2_2_0_0_9, 1_1_5_7_7_4, 2_3, 3_5_5_9, 1_3_2_8, 4_6_8_7_6, 7, 1_3_6, 5_3_8_9_4, 1_9_4_0, 4_2_2_2_7, 4_1_1_5_9, 1_7_7_2_1, 8_2_3, 4_2_5, 4, 2_7_5_1_2, 9_8_7_2_2, 2_0_6, 1_3_6, 5_5_3_1, 4_9_7_0, 9_1_9, 1_7_3_3_6, 5, 2], [0, 2_0_0_8_0, 6_1_8, 8_3, 8_2_7_7_5, 4_7, 4_7_9, 9, 1_5_1_7, 7_3, 5_3_8_9_4, 3_3_3, 8_0_5_8_1, 1_1_0_1_1_7, 1_8_8_1_1, 5_2_5_6, 1_2_9_5, 5_1, 1_5_2_5_2_6, 2_9_7, 7_9_8_6, 3_9_0, 1_2_4_4_1_6, 5_3_8, 3_5_4_3_1, 2_1_4, 9_8, 1_5_0_4_4, 2_5_7_3_7, 1_3_6, 7_1_0_8, 4_3_7_0_1, 2_3, 7_5_6, 1_3_5_3_5_5, 7, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 5_8_1, 6_3_7_7_3, 1_1_9_4_5_5, 6, 1_4_7_7_9_7, 8_8_2_0_3, 7, 6_4_5, 7_0, 2_1, 3_2_8_5, 1_0_2_6_9, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}
          # fmt: on
  
          self.tokenizer_integration_test_util(
              expected_encoding=lowercase_	,   model_name="susnato/ernie-m-base_pytorch"	,   sequences=[
                  "Transformers (formerly known as pytorch-transformers and pytorch-pretrained-bert) provides "
                  "general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet...) for Natural "
                  "Language Understanding (NLU) and Natural Language Generation (NLG) with over32+ pretrained "
                  "models in100+ languages and deep interoperability between Jax, PyTorch and TensorFlow.",
                  "BERT is designed to pre-train deep bidirectional representations from unlabeled text by jointly "
                  "conditioning on both left and right context in all layers.",
                  "The quick brown fox jumps over the lazy dog.",
              ]	,   )
  
  
  
  
  
  
  
style_context: 
  
  
  
  
  
  def   _A (	SCREAMING_SNAKE_CASE  :     int		):
  
  
  
  
  
    """simple docstring"""
  
  
  
    if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE		) or number < 0:
      raise ValueError("Input must be a non-negative integer"		)
  
    a__			:      List[str]            =number & ~(number - 1)
    a__			:      Optional[int]            =0
    while intermediate:
      intermediate >>= 1
      index += 1
    return index - 1
  
  
  if __name__ == "__main__":
       import doctest
  
       doctest.testmod(verbose=True)
  
  
  
  
  
  
  