





import unittest

from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


UpperCAmelCase     :     Dict							=	get_tests_dir("""fixtures/test_sentencepiece_no_bos.model""")







@require_sentencepiece
@require_tokenizers
class     __lowerCAmelCase	(   UpperCamelCase__						,    unittest.TestCase):
      _lowercase    : List[str]            =      PegasusTokenizer
      _lowercase    : Any            =      PegasusTokenizerFast
      _lowercase    : str            =      True
      _lowercase    : Any            =      True







      def        _lowercase  (   self							)       ->						Dict:



        '''simple docstring'''




        super().setUp()

        # We have a SentencePiece fixture for testing
        a__     : Optional[int]  =PegasusTokenizer(lowerCAmelCase__							)
        tokenizer.save_pretrained(self.tmpdirname							)







      @cached_property
      def        _lowercase  (   self							)       ->						Tuple:



        '''simple docstring'''




        return PegasusTokenizer.from_pretrained("google/pegasus-large"							)







      def        _lowercase  (   self		,				**lowerCAmelCase__							)       ->						PegasusTokenizer:



        '''simple docstring'''




        return PegasusTokenizer.from_pretrained(self.tmpdirname		,				**lowerCAmelCase__							)







      def        _lowercase  (   self		,				lowerCAmelCase__							)       ->						List[Any]:



        '''simple docstring'''




        return ("This is a test", "This is a test")







      def        _lowercase  (   self							)       ->						Tuple:



        '''simple docstring'''




        a__     : Optional[int]  ="</s>"
        a__     : List[str]  =1

        self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCAmelCase__							)		,				lowerCAmelCase__							)
        self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCAmelCase__							)		,				lowerCAmelCase__							)







      def        _lowercase  (   self							)       ->						Optional[Any]:



        '''simple docstring'''




        a__     : Tuple  =list(self.get_tokenizer().get_vocab().keys()							)

        self.assertEqual(vocab_keys[0]		,				"<pad>"							)
        self.assertEqual(vocab_keys[1]		,				"</s>"							)
        self.assertEqual(vocab_keys[-1]		,				"v"							)
        self.assertEqual(len(lowerCAmelCase__							)		,				1_1_0_3							)







      def        _lowercase  (   self							)       ->						List[str]:



        '''simple docstring'''




        self.assertEqual(self.get_tokenizer().vocab_size		,				1_1_0_3							)







      def        _lowercase  (   self							)       ->						Optional[Any]:



        '''simple docstring'''




        a__     : Optional[int]  =self.rust_tokenizer_class.from_pretrained(self.tmpdirname							)
        a__     : Dict  =self.tokenizer_class.from_pretrained(self.tmpdirname							)
        a__     : Dict  =(
            "Let's see which <unk> is the better <unk_token_11> one <mask_1> It seems like this <mask_2> was important"
            " </s> <pad> <pad> <pad>"
        )
        a__     : List[str]  =rust_tokenizer([raw_input_str]		,				return_tensors=lowerCAmelCase__		,				add_special_tokens=lowerCAmelCase__							).input_ids[0]
        a__     : Tuple  =py_tokenizer([raw_input_str]		,				return_tensors=lowerCAmelCase__		,				add_special_tokens=lowerCAmelCase__							).input_ids[0]
        self.assertListEqual(lowerCAmelCase__		,				lowerCAmelCase__							)







      def        _lowercase  (   self							)       ->						Any:



        '''simple docstring'''




        a__     : Tuple  =self._large_tokenizer
        # <mask_1> masks whole sentence while <mask_2> masks single word
        a__     : Dict  ="<mask_1> To ensure a <mask_2> flow of bank resolutions."
        a__     : str  =[2, 4_1_3, 6_1_5, 1_1_4, 3, 1_9_7_1, 1_1_3, 1_6_7_9, 1_0_7_1_0, 1_0_7, 1]
        a__     : Dict  =tokenizer([raw_input_str]		,				return_tensors=lowerCAmelCase__							).input_ids[0]
        self.assertListEqual(lowerCAmelCase__		,				lowerCAmelCase__							)







      def        _lowercase  (   self							)       ->						Optional[Any]:



        '''simple docstring'''




        a__     : Any  =self._large_tokenizer
        # The tracebacks for the following asserts are **better** without messages or self.assertEqual
        assert tokenizer.vocab_size == 9_6_1_0_3
        assert tokenizer.pad_token_id == 0
        assert tokenizer.eos_token_id == 1
        assert tokenizer.offset == 1_0_3
        assert tokenizer.unk_token_id == tokenizer.offset + 2 == 1_0_5
        assert tokenizer.unk_token == "<unk>"
        assert tokenizer.model_max_length == 1_0_2_4
        a__     : Dict  ="To ensure a smooth flow of bank resolutions."
        a__     : Union[str, Any]  =[4_1_3, 6_1_5, 1_1_4, 2_2_9_1, 1_9_7_1, 1_1_3, 1_6_7_9, 1_0_7_1_0, 1_0_7, 1]
        a__     : List[Any]  =tokenizer([raw_input_str]		,				return_tensors=lowerCAmelCase__							).input_ids[0]
        self.assertListEqual(lowerCAmelCase__		,				lowerCAmelCase__							)
        assert tokenizer.convert_ids_to_tokens([0, 1, 2, 3]							) == ["<pad>", "</s>", "<mask_1>", "<mask_2>"]







      @require_torch
      def        _lowercase  (   self							)       ->						Dict:



        '''simple docstring'''




        a__     : str  =["This is going to be way too long." * 1_5_0, "short example"]
        a__     : Any  =["not super long but more than 5 tokens", "tiny"]
        a__     : Union[str, Any]  =self._large_tokenizer(lowerCAmelCase__		,				padding=lowerCAmelCase__		,				truncation=lowerCAmelCase__		,				return_tensors="pt"							)
        a__     : Any  =self._large_tokenizer(
            text_target=lowerCAmelCase__		,				max_length=5		,				padding=lowerCAmelCase__		,				truncation=lowerCAmelCase__		,				return_tensors="pt"							)

        assert batch.input_ids.shape == (2, 1_0_2_4)
        assert batch.attention_mask.shape == (2, 1_0_2_4)
        assert targets["input_ids"].shape == (2, 5)
        assert len(lowerCAmelCase__							) == 2  # input_ids, attention_mask.







      @slow
      def        _lowercase  (   self							)       ->						int:



        '''simple docstring'''




        a__     : Any  ={"input_ids": [[3_8_9_7_9, 1_4_3, 1_8_4_8_5, 6_0_6, 1_3_0, 2_6_6_6_9, 8_7_6_8_6, 1_2_1, 5_4_1_8_9, 1_1_2_9, 1_1_1, 2_6_6_6_9, 8_7_6_8_6, 1_2_1, 9_1_1_4, 1_4_7_8_7, 1_2_1, 1_3_2_4_9, 1_5_8, 5_9_2, 9_5_6, 1_2_1, 1_4_6_2_1, 3_1_5_7_6, 1_4_3, 6_2_6_1_3, 1_0_8, 9_6_8_8, 9_3_0, 4_3_4_3_0, 1_1_5_6_2, 6_2_6_1_3, 3_0_4, 1_0_8, 1_1_4_4_3, 8_9_7, 1_0_8, 9_3_1_4, 1_7_4_1_5, 6_3_3_9_9, 1_0_8, 1_1_4_4_3, 7_6_1_4, 1_8_3_1_6, 1_1_8, 4_2_8_4, 7_1_4_8, 1_2_4_3_0, 1_4_3, 1_4_0_0, 2_5_7_0_3, 1_5_8, 1_1_1, 4_2_8_4, 7_1_4_8, 1_1_7_7_2, 1_4_3, 2_1_2_9_7, 1_0_6_4, 1_5_8, 1_2_2, 2_0_4, 3_5_0_6, 1_7_5_4, 1_1_3_3, 1_4_7_8_7, 1_5_8_1, 1_1_5, 3_3_2_2_4, 4_4_8_2, 1_1_1, 1_3_5_5, 1_1_0, 2_9_1_7_3, 3_1_7, 5_0_8_3_3, 1_0_8, 2_0_1_4_7, 9_4_6_6_5, 1_1_1, 7_7_1_9_8, 1_0_7, 1], [1_1_0, 6_2_6_1_3, 1_1_7, 6_3_8, 1_1_2, 1_1_3_3, 1_2_1, 2_0_0_9_8, 1_3_5_5, 7_9_0_5_0, 1_3_8_7_2, 1_3_5, 1_5_9_6, 5_3_5_4_1, 1_3_5_2, 1_4_1, 1_3_0_3_9, 5_5_4_2, 1_2_4, 3_0_2, 5_1_8, 1_1_1, 2_6_8, 2_9_5_6, 1_1_5, 1_4_9, 4_4_2_7, 1_0_7, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1_3_9, 1_2_3_5, 2_7_9_9, 1_8_2_8_9, 1_7_7_8_0, 2_0_4, 1_0_9, 9_4_7_4, 1_2_9_6, 1_0_7, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], "attention_mask": [[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, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
        # fmt: on

        self.tokenizer_integration_test_util(
            expected_encoding=lowerCAmelCase__		,				model_name="google/bigbird-pegasus-large-arxiv"		,				revision="ba85d0851d708441f91440d509690f1ab6353415"		,				)







@require_sentencepiece
@require_tokenizers
class     __lowerCAmelCase	(   UpperCamelCase__						,    unittest.TestCase):
      _lowercase    : Dict            =      PegasusTokenizer
      _lowercase    : Optional[int]            =      PegasusTokenizerFast
      _lowercase    : List[str]            =      True
      _lowercase    : int            =      True







      def        _lowercase  (   self							)       ->						Tuple:



        '''simple docstring'''




        super().setUp()

        # We have a SentencePiece fixture for testing
        a__     : str  =PegasusTokenizer(lowerCAmelCase__		,				offset=0		,				mask_token_sent=lowerCAmelCase__		,				mask_token="[MASK]"							)
        tokenizer.save_pretrained(self.tmpdirname							)







      @cached_property
      def        _lowercase  (   self							)       ->						List[str]:



        '''simple docstring'''




        return PegasusTokenizer.from_pretrained("google/bigbird-pegasus-large-arxiv"							)







      def        _lowercase  (   self		,				**lowerCAmelCase__							)       ->						PegasusTokenizer:



        '''simple docstring'''




        return PegasusTokenizer.from_pretrained(self.tmpdirname		,				**lowerCAmelCase__							)







      def        _lowercase  (   self		,				lowerCAmelCase__							)       ->						Any:



        '''simple docstring'''




        return ("This is a test", "This is a test")







      def        _lowercase  (   self							)       ->						Any:



        '''simple docstring'''




        a__     : int  =self.rust_tokenizer_class.from_pretrained(self.tmpdirname							)
        a__     : int  =self.tokenizer_class.from_pretrained(self.tmpdirname							)
        a__     : Any  =(
            "Let's see which <unk> is the better <unk_token> one [MASK] It seems like this [MASK] was important </s>"
            " <pad> <pad> <pad>"
        )
        a__     : List[Any]  =rust_tokenizer([raw_input_str]		,				return_tensors=lowerCAmelCase__		,				add_special_tokens=lowerCAmelCase__							).input_ids[0]
        a__     : str  =py_tokenizer([raw_input_str]		,				return_tensors=lowerCAmelCase__		,				add_special_tokens=lowerCAmelCase__							).input_ids[0]
        self.assertListEqual(lowerCAmelCase__		,				lowerCAmelCase__							)







      @require_torch
      def        _lowercase  (   self							)       ->						List[Any]:



        '''simple docstring'''




        a__     : List[Any]  =["This is going to be way too long." * 1_0_0_0, "short example"]
        a__     : int  =["not super long but more than 5 tokens", "tiny"]
        a__     : Any  =self._large_tokenizer(lowerCAmelCase__		,				padding=lowerCAmelCase__		,				truncation=lowerCAmelCase__		,				return_tensors="pt"							)
        a__     : List[str]  =self._large_tokenizer(
            text_target=lowerCAmelCase__		,				max_length=5		,				padding=lowerCAmelCase__		,				truncation=lowerCAmelCase__		,				return_tensors="pt"							)

        assert batch.input_ids.shape == (2, 4_0_9_6)
        assert batch.attention_mask.shape == (2, 4_0_9_6)
        assert targets["input_ids"].shape == (2, 5)
        assert len(lowerCAmelCase__							) == 2  # input_ids, attention_mask.







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



        '''simple docstring'''




        a__     : List[Any]  =(
            "This is an example string that is used to test the original TF implementation against the HF"
            " implementation"
        )

        a__     : Tuple  =self._large_tokenizer(lowerCAmelCase__							).input_ids

        self.assertListEqual(
            lowerCAmelCase__		,				[1_8_2, 1_1_7, 1_4_2, 5_8_7, 4_2_1_1, 1_2_0, 1_1_7, 2_6_3, 1_1_2, 8_0_4, 1_0_9, 8_5_6, 2_5_0_1_6, 3_1_3_7, 4_6_4, 1_0_9, 2_6_9_5_5, 3_1_3_7, 1]		,				)













def 					_A	(		SCREAMING_SNAKE_CASE					:       int = 1	,	SCREAMING_SNAKE_CASE					:       int = 1_000						):





  """simple docstring"""



  a__     : Any  =1
  a__     : Any  =0

  for divide_by_number in range(SCREAMING_SNAKE_CASE	,	digit + 1						):
    a__     : list[int]  =[]
    a__     : int  =numerator
    for _ in range(1	,	digit + 1						):
      if now_divide in has_been_divided:
        if longest_list_length < len(SCREAMING_SNAKE_CASE						):
          a__     : Optional[Any]  =len(SCREAMING_SNAKE_CASE						)
          a__     : List[str]  =divide_by_number
      else:
        has_been_divided.append(SCREAMING_SNAKE_CASE						)
        a__     : List[Any]  =now_divide * 10 % divide_by_number

  return the_digit


# Tests
if __name__ == "__main__":
     import doctest

     doctest.testmod()






