




'''simple docstring'''




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


a_      :		List[str]							      =       get_tests_dir("""fixtures/test_sentencepiece_no_bos.model""")


@require_sentencepiece
@require_tokenizers
class   __UpperCamelCase       ( lowerCamelCase__			,					unittest.TestCase				):
       lowercase	:    Dict      						=PegasusTokenizer
       lowercase	:    List[str]      						=PegasusTokenizerFast
       lowercase	:    Any      						=True
       lowercase	:    Tuple      						=True






       def      lowercase__     (							self  ):



              """simple docstring"""







              super().setUp()

              # We have a SentencePiece fixture for testing
              lowerCamelCase_							=PegasusTokenizer(lowerCAmelCase  )
              tokenizer.save_pretrained(self.tmpdirname  )






       @cached_property
       def      lowercase__     (							self  ):



              """simple docstring"""







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






       def      lowercase__     (							self,		**lowerCAmelCase  ):



              """simple docstring"""







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






       def      lowercase__     (							self,		lowerCAmelCase  ):



              """simple docstring"""







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






       def      lowercase__     (							self  ):



              """simple docstring"""







              lowerCamelCase_							='''</s>'''
              lowerCamelCase_							=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  ):



              """simple docstring"""







              lowerCamelCase_							=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_103  )






       def      lowercase__     (							self  ):



              """simple docstring"""







              self.assertEqual(self.get_tokenizer().vocab_size,		1_103  )






       def      lowercase__     (							self  ):



              """simple docstring"""







              lowerCamelCase_							=self.rust_tokenizer_class.from_pretrained(self.tmpdirname  )
              lowerCamelCase_							=self.tokenizer_class.from_pretrained(self.tmpdirname  )
              lowerCamelCase_							=(
                  '''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>'''
              )
              lowerCamelCase_							=rust_tokenizer([raw_input_str],		return_tensors=lowerCAmelCase,		add_special_tokens=lowerCAmelCase  ).input_ids[0]
              lowerCamelCase_							=py_tokenizer([raw_input_str],		return_tensors=lowerCAmelCase,		add_special_tokens=lowerCAmelCase  ).input_ids[0]
              self.assertListEqual(lowerCAmelCase,		lowerCAmelCase  )






       def      lowercase__     (							self  ):



              """simple docstring"""







              lowerCamelCase_							=self._large_tokenizer
              # <mask_1> masks whole sentence while <mask_2> masks single word
              lowerCamelCase_							='''<mask_1> To ensure a <mask_2> flow of bank resolutions.'''
              lowerCamelCase_							=[2, 413, 615, 114, 3, 1_971, 113, 1_679, 10_710, 107, 1]
              lowerCamelCase_							=tokenizer([raw_input_str],		return_tensors=lowerCAmelCase  ).input_ids[0]
              self.assertListEqual(lowerCAmelCase,		lowerCAmelCase  )






       def      lowercase__     (							self  ):



              """simple docstring"""







              lowerCamelCase_							=self._large_tokenizer
              # The tracebacks for the following asserts are **better** without messages or self.assertEqual
              assert tokenizer.vocab_size == 96_103
              assert tokenizer.pad_token_id == 0
              assert tokenizer.eos_token_id == 1
              assert tokenizer.offset == 103
              assert tokenizer.unk_token_id == tokenizer.offset + 2 == 105
              assert tokenizer.unk_token == "<unk>"
              assert tokenizer.model_max_length == 1_024
              lowerCamelCase_							='''To ensure a smooth flow of bank resolutions.'''
              lowerCamelCase_							=[413, 615, 114, 2_291, 1_971, 113, 1_679, 10_710, 107, 1]
              lowerCamelCase_							=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  ):



              """simple docstring"""







              lowerCamelCase_							=['''This is going to be way too long.''' * 150, '''short example''']
              lowerCamelCase_							=['''not super long but more than 5 tokens''', '''tiny''']
              lowerCamelCase_							=self._large_tokenizer(lowerCAmelCase,		padding=lowerCAmelCase,		truncation=lowerCAmelCase,		return_tensors='''pt'''  )
              lowerCamelCase_							=self._large_tokenizer(
                  text_target=lowerCAmelCase,		max_length=5,		padding=lowerCAmelCase,		truncation=lowerCAmelCase,		return_tensors='''pt'''  )

              assert batch.input_ids.shape == (2, 1_024)
              assert batch.attention_mask.shape == (2, 1_024)
              assert targets["input_ids"].shape == (2, 5)
              assert len(lowerCAmelCase  ) == 2  # input_ids, attention_mask.






       @slow
       def      lowercase__     (							self  ):



              """simple docstring"""







              lowerCamelCase_							={'''input_ids''': [[38_979, 143, 18_485, 606, 130, 26_669, 87_686, 121, 54_189, 1_129, 111, 26_669, 87_686, 121, 9_114, 14_787, 121, 13_249, 158, 592, 956, 121, 14_621, 31_576, 143, 62_613, 108, 9_688, 930, 43_430, 11_562, 62_613, 304, 108, 11_443, 897, 108, 9_314, 17_415, 63_399, 108, 11_443, 7_614, 18_316, 118, 4_284, 7_148, 12_430, 143, 1_400, 25_703, 158, 111, 4_284, 7_148, 11_772, 143, 21_297, 1_064, 158, 122, 204, 3_506, 1_754, 1_133, 14_787, 1_581, 115, 33_224, 4_482, 111, 1_355, 110, 29_173, 317, 50_833, 108, 20_147, 94_665, 111, 77_198, 107, 1], [110, 62_613, 117, 638, 112, 1_133, 121, 20_098, 1_355, 79_050, 13_872, 135, 1_596, 53_541, 1_352, 141, 13_039, 5_542, 124, 302, 518, 111, 268, 2_956, 115, 149, 4_427, 107, 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], [139, 1_235, 2_799, 18_289, 17_780, 204, 109, 9_474, 1_296, 107, 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   __UpperCamelCase       ( lowerCamelCase__			,					unittest.TestCase				):
       lowercase	:    List[Any]      						=PegasusTokenizer
       lowercase	:    List[str]      						=PegasusTokenizerFast
       lowercase	:    List[Any]      						=True
       lowercase	:    Union[str, Any]      						=True






       def      lowercase__     (							self  ):



              """simple docstring"""







              super().setUp()

              # We have a SentencePiece fixture for testing
              lowerCamelCase_							=PegasusTokenizer(lowerCAmelCase,		offset=0,		mask_token_sent=lowerCAmelCase,		mask_token='''[MASK]'''  )
              tokenizer.save_pretrained(self.tmpdirname  )






       @cached_property
       def      lowercase__     (							self  ):



              """simple docstring"""







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






       def      lowercase__     (							self,		**lowerCAmelCase  ):



              """simple docstring"""







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






       def      lowercase__     (							self,		lowerCAmelCase  ):



              """simple docstring"""







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






       def      lowercase__     (							self  ):



              """simple docstring"""







              lowerCamelCase_							=self.rust_tokenizer_class.from_pretrained(self.tmpdirname  )
              lowerCamelCase_							=self.tokenizer_class.from_pretrained(self.tmpdirname  )
              lowerCamelCase_							=(
                  '''Let\'s see which <unk> is the better <unk_token> one [MASK] It seems like this [MASK] was important </s>'''
                  ''' <pad> <pad> <pad>'''
              )
              lowerCamelCase_							=rust_tokenizer([raw_input_str],		return_tensors=lowerCAmelCase,		add_special_tokens=lowerCAmelCase  ).input_ids[0]
              lowerCamelCase_							=py_tokenizer([raw_input_str],		return_tensors=lowerCAmelCase,		add_special_tokens=lowerCAmelCase  ).input_ids[0]
              self.assertListEqual(lowerCAmelCase,		lowerCAmelCase  )






       @require_torch
       def      lowercase__     (							self  ):



              """simple docstring"""







              lowerCamelCase_							=['''This is going to be way too long.''' * 1_000, '''short example''']
              lowerCamelCase_							=['''not super long but more than 5 tokens''', '''tiny''']
              lowerCamelCase_							=self._large_tokenizer(lowerCAmelCase,		padding=lowerCAmelCase,		truncation=lowerCAmelCase,		return_tensors='''pt'''  )
              lowerCamelCase_							=self._large_tokenizer(
                  text_target=lowerCAmelCase,		max_length=5,		padding=lowerCAmelCase,		truncation=lowerCAmelCase,		return_tensors='''pt'''  )

              assert batch.input_ids.shape == (2, 4_096)
              assert batch.attention_mask.shape == (2, 4_096)
              assert targets["input_ids"].shape == (2, 5)
              assert len(lowerCAmelCase  ) == 2  # input_ids, attention_mask.






       def      lowercase__     (							self  ):



              """simple docstring"""







              lowerCamelCase_							=(
                  '''This is an example string that is used to test the original TF implementation against the HF'''
                  ''' implementation'''
              )

              lowerCamelCase_							=self._large_tokenizer(lowerCAmelCase  ).input_ids

              self.assertListEqual(
                  lowerCAmelCase,		[182, 117, 142, 587, 4_211, 120, 117, 263, 112, 804, 109, 856, 25_016, 3_137, 464, 109, 26_955, 3_137, 1],		)








'''simple docstring'''




import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot import BlenderbotTokenizer


if TYPE_CHECKING:
       from transformers.pipelines.conversational import Conversation

__snake_case    						=logging.get_logger(__name__)


__snake_case    						={
    """vocab_file""": """vocab.json""",
    """merges_file""": """merges.txt""",
    """tokenizer_config_file""": """tokenizer_config.json""",
}

__snake_case    						={
    """vocab_file""": {"""facebook/blenderbot-3B""": """https://huggingface.co/facebook/blenderbot-3B/resolve/main/vocab.json"""},
    """merges_file""": {"""facebook/blenderbot-3B""": """https://huggingface.co/facebook/blenderbot-3B/resolve/main/merges.txt"""},
    """tokenizer_config_file""": {
        """facebook/blenderbot-3B""": """https://huggingface.co/facebook/blenderbot-3B/resolve/main/tokenizer_config.json"""
    },
}

__snake_case    						={"""facebook/blenderbot-3B""": 128}

class 		UpperCAmelCase_      (  __lowercase		):
     lowerCamelCase				:	List[Any]		=     VOCAB_FILES_NAMES
     lowerCamelCase				:	Optional[int]		=     PRETRAINED_VOCAB_FILES_MAP
     lowerCamelCase				:	str		=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     lowerCamelCase				:	Optional[Any]		=     ['''input_ids''', '''attention_mask''']
     lowerCamelCase				:	List[Any]		=     BlenderbotTokenizer





     def __init__( self       :      Union[str, Any]    ,      UpperCAmelCase__       :      Tuple=None    ,      UpperCAmelCase__       :      Tuple=None    ,      UpperCAmelCase__       :      List[Any]=None    ,      UpperCAmelCase__       :      str="replace"    ,      UpperCAmelCase__       :      Dict="<s>"    ,      UpperCAmelCase__       :      Tuple="</s>"    ,      UpperCAmelCase__       :      Optional[Any]="</s>"    ,      UpperCAmelCase__       :      Any="<s>"    ,      UpperCAmelCase__       :      List[str]="<unk>"    ,      UpperCAmelCase__       :      int="<pad>"    ,      UpperCAmelCase__       :      Union[str, Any]="<mask>"    ,      UpperCAmelCase__       :      str=False    ,      UpperCAmelCase__       :      Union[str, Any]=True    ,      **UpperCAmelCase__       :      Optional[int]    ,      )				->  int:
        super().__init__(
            UpperCAmelCase__    ,      UpperCAmelCase__    ,      tokenizer_file=UpperCAmelCase__    ,      errors=UpperCAmelCase__    ,      bos_token=UpperCAmelCase__    ,      eos_token=UpperCAmelCase__    ,      sep_token=UpperCAmelCase__    ,      cls_token=UpperCAmelCase__    ,      unk_token=UpperCAmelCase__    ,      pad_token=UpperCAmelCase__    ,      mask_token=UpperCAmelCase__    ,      add_prefix_space=UpperCAmelCase__    ,      trim_offsets=UpperCAmelCase__    ,      **UpperCAmelCase__    ,      )

        lowerCAmelCase     =			json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()    )
        if pre_tok_state.get('add_prefix_space'    ,      UpperCAmelCase__    ) != add_prefix_space:
           lowerCAmelCase     =			getattr(UpperCAmelCase__    ,      pre_tok_state.pop('type'    )    )
           lowerCAmelCase     =			add_prefix_space
           lowerCAmelCase     =			pre_tok_class(**UpperCAmelCase__    )

        lowerCAmelCase     =			add_prefix_space

        lowerCAmelCase     =			'post_processor'
        lowerCAmelCase     =			getattr(self.backend_tokenizer    ,      UpperCAmelCase__    ,      UpperCAmelCase__    )
        if tokenizer_component_instance:
           lowerCAmelCase     =			json.loads(tokenizer_component_instance.__getstate__()    )

           # The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
           if "sep" in state:
              lowerCAmelCase     =			tuple(state['sep']    )
           if "cls" in state:
              lowerCAmelCase     =			tuple(state['cls']    )

           lowerCAmelCase     =			False

           if state.get('add_prefix_space'    ,      UpperCAmelCase__    ) != add_prefix_space:
              lowerCAmelCase     =			add_prefix_space
              lowerCAmelCase     =			True

           if state.get('trim_offsets'    ,      UpperCAmelCase__    ) != trim_offsets:
              lowerCAmelCase     =			trim_offsets
              lowerCAmelCase     =			True

           if changes_to_apply:
              lowerCAmelCase     =			getattr(UpperCAmelCase__    ,      state.pop('type'    )    )
              lowerCAmelCase     =			component_class(**UpperCAmelCase__    )
              setattr(self.backend_tokenizer    ,      UpperCAmelCase__    ,      UpperCAmelCase__    )





     @property
     # Copied from transformers.models.roberta.tokenization_roberta_fast.RobertaTokenizerFast.mask_token with Roberta->Blenderbot, RoBERTa->Blenderbot
     def 							__UpperCAmelCase      ( self       :      Union[str, Any]    )				->  str:
        if self._mask_token is None:
           if self.verbose:
              logger.error('Using mask_token, but it is not set yet.'    )
           return None
        return str(self._mask_token    )





     @mask_token.setter
     def 							__UpperCAmelCase      ( self       :      int    ,      UpperCAmelCase__       :      Optional[Any]    )				->  Tuple:
        lowerCAmelCase     =			AddedToken(UpperCAmelCase__    ,      lstrip=UpperCAmelCase__    ,      rstrip=UpperCAmelCase__    ) if isinstance(UpperCAmelCase__    ,      UpperCAmelCase__    ) else value
        lowerCAmelCase     =			value





     def 							__UpperCAmelCase      ( self       :      Optional[Any]    ,      *UpperCAmelCase__       :      Union[str, Any]    ,      **UpperCAmelCase__       :      List[str]    )				->  BatchEncoding:
        lowerCAmelCase     =			kwargs.get('is_split_into_words'    ,      UpperCAmelCase__    )
        assert self.add_prefix_space or not is_split_into_words, (
            F'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
            "to use it with pretokenized inputs."
        )

        return super()._batch_encode_plus(*UpperCAmelCase__    ,      **UpperCAmelCase__    )





     def 							__UpperCAmelCase      ( self       :      List[str]    ,      *UpperCAmelCase__       :      str    ,      **UpperCAmelCase__       :      List[str]    )				->  BatchEncoding:
        lowerCAmelCase     =			kwargs.get('is_split_into_words'    ,      UpperCAmelCase__    )

        assert self.add_prefix_space or not is_split_into_words, (
            F'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
            "to use it with pretokenized inputs."
        )

        return super()._encode_plus(*UpperCAmelCase__    ,      **UpperCAmelCase__    )





     def 							__UpperCAmelCase      ( self       :      str    ,      UpperCAmelCase__       :      str    ,      UpperCAmelCase__       :      Optional[str] = None    )				->  Tuple[str]:
        lowerCAmelCase     =			self._tokenizer.model.save(UpperCAmelCase__    ,      name=UpperCAmelCase__    )
        return tuple(UpperCAmelCase__    )





     def 							__UpperCAmelCase      ( self       :      Optional[int]    ,      UpperCAmelCase__       :      List[int]    ,      UpperCAmelCase__       :      Optional[List[int]] = None    )				->  List[int]:
        lowerCAmelCase     =			[self.sep_token_id]
        lowerCAmelCase     =			[self.cls_token_id]

        if token_ids_a is None:
           return len(cls + token_ids_a + sep    ) * [0]
        return len(cls + token_ids_a + sep + sep + token_ids_a + sep    ) * [0]





     def 							__UpperCAmelCase      ( self       :      List[str]    ,      UpperCAmelCase__       :      List[int]    ,      UpperCAmelCase__       :      Optional[List[int]] = None    )				->  Any:
        return token_ids_a + [self.eos_token_id]





     def 							__UpperCAmelCase      ( self       :      Union[str, Any]    ,      UpperCAmelCase__       :      "Conversation"    )				->  List[int]:
        lowerCAmelCase     =			[]
        for is_user, text in conversation.iter_texts():
           if is_user:
              # We need to space prefix as it's being done within blenderbot
              inputs.append(' ' + text    )
           else:
              # Generated responses should contain them already.
              inputs.append(UpperCAmelCase__    )

        lowerCAmelCase     =			'  '.join(UpperCAmelCase__    )
        lowerCAmelCase     =			self.encode(UpperCAmelCase__    )
        if len(UpperCAmelCase__    ) > self.model_max_length:
           lowerCAmelCase     =			input_ids[-self.model_max_length :]
           logger.warning(F'''Trimmed input from conversation as it was longer than {self.model_max_length} tokens.'''    )
        return input_ids





