



import json
from typing import 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_mvp import MvpTokenizer


a_								=    logging.get_logger(__name__)


a_								=    {"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

# See all MVP models at https://huggingface.co/models?filter=mvp
a_								=    {
    """vocab_file""": {
        """RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/vocab.json""",
    },
    """added_tokens.json""": {
        """RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/added_tokens.json""",
    },
    """merges_file""": {
        """RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/merges.txt""",
    },
    """tokenizer_file""": {
        """RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/tokenizer.json""",
    },
}

a_								=    {
    """RUCAIBox/mvp""": 1_024,
}



class        __lowerCAmelCase   (		_a      ):
 lowerCAmelCase__				    =     VOCAB_FILES_NAMES
 lowerCAmelCase__				    =     PRETRAINED_VOCAB_FILES_MAP
 lowerCAmelCase__				    =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowerCAmelCase__				    =     ['''input_ids''', '''attention_mask''']
 lowerCAmelCase__				    =     MvpTokenizer




 def __init__(  self		, __UpperCAmelCase=None		, __UpperCAmelCase=None		, __UpperCAmelCase=None		, __UpperCAmelCase="replace"		, __UpperCAmelCase="<s>"		, __UpperCAmelCase="</s>"		, __UpperCAmelCase="</s>"		, __UpperCAmelCase="<s>"		, __UpperCAmelCase="<unk>"		, __UpperCAmelCase="<pad>"		, __UpperCAmelCase="<mask>"		, __UpperCAmelCase=False		, __UpperCAmelCase=True		, **__UpperCAmelCase		, ):



    '''simple docstring'''
    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

    # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
    __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
 def 				lowerCamelCase					(  self ):



    '''simple docstring'''



    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 				lowerCamelCase					(  self		, __UpperCAmelCase ):



    '''simple docstring'''
    __lowerCamelCase  							=			AddedToken(__UpperCAmelCase		, lstrip=__UpperCAmelCase		, rstrip=__UpperCAmelCase ) if isinstance(__UpperCAmelCase		, __UpperCAmelCase ) else value
    __lowerCamelCase  							=			value




 def 				lowerCamelCase					(  self		, *__UpperCAmelCase		, **__UpperCAmelCase ):



    '''simple docstring'''
    __lowerCamelCase  							=			kwargs.get('''is_split_into_words'''		, __UpperCAmelCase )

    if is_split_into_words and not self.add_prefix_space:
       raise ValueError(
           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 				lowerCamelCase					(  self		, *__UpperCAmelCase		, **__UpperCAmelCase ):



    '''simple docstring'''
    __lowerCamelCase  							=			kwargs.get('''is_split_into_words'''		, __UpperCAmelCase )

    if is_split_into_words and not self.add_prefix_space:
       raise ValueError(
           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 				lowerCamelCase					(  self		, __UpperCAmelCase		, __UpperCAmelCase = None ):



    '''simple docstring'''
    __lowerCamelCase  							=			self._tokenizer.model.save(__UpperCAmelCase		, name=__UpperCAmelCase )
    return tuple(__UpperCAmelCase )




 def 				lowerCamelCase					(  self		, __UpperCAmelCase		, __UpperCAmelCase=None ):



    '''simple docstring'''
    __lowerCamelCase  							=			[self.bos_token_id] + token_ids_a + [self.eos_token_id]
    if token_ids_a is None:
       return output

    return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]




 def 				lowerCamelCase					(  self		, __UpperCAmelCase		, __UpperCAmelCase = None ):



    '''simple docstring'''
    __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]













import json
import os
import unittest

from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin



class 					__lowerCAmelCase       (			_a,     unittest.TestCase     ):
			lowerCamelCase_     :     Any       			=      BioGptTokenizer
			lowerCamelCase_     :     Optional[Any]       			=      False






			def 			lowerCamelCase  (self    )     ->   List[Any]:


							'''simple docstring'''



							super().setUp()

							# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
							snake_case_						:    Optional[Any]				=  [
							    '''l''',
							    '''o''',
							    '''w''',
							    '''e''',
							    '''r''',
							    '''s''',
							    '''t''',
							    '''i''',
							    '''d''',
							    '''n''',
							    '''w</w>''',
							    '''r</w>''',
							    '''t</w>''',
							    '''lo''',
							    '''low''',
							    '''er</w>''',
							    '''low</w>''',
							    '''lowest</w>''',
							    '''newer</w>''',
							    '''wider</w>''',
							    '''<unk>''',
							]
							snake_case_						:    Union[str, Any]				=  dict(zip(__magic_name__					,							range(len(__magic_name__    )    )    )    )
							snake_case_						:    Union[str, Any]				=  ['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

							snake_case_						:    Any				=  os.path.join(self.tmpdirname					,							VOCAB_FILES_NAMES['''vocab_file''']    )
							snake_case_						:    Dict				=  os.path.join(self.tmpdirname					,							VOCAB_FILES_NAMES['''merges_file''']    )
							with open(self.vocab_file					,							'''w'''    ) as fp:
											fp.write(json.dumps(__magic_name__    )    )
							with open(self.merges_file					,							'''w'''    ) as fp:
											fp.write('''\n'''.join(__magic_name__    )    )






			def 			lowerCamelCase  (self					,							__magic_name__    )     ->   int:


							'''simple docstring'''



							snake_case_						:    str				=  '''lower newer'''
							snake_case_						:    Dict				=  '''lower newer'''
							return input_text, output_text






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


							'''simple docstring'''



							snake_case_						:    Optional[int]				=  BioGptTokenizer(self.vocab_file					,							self.merges_file    )

							snake_case_						:    Union[str, Any]				=  '''lower'''
							snake_case_						:    Optional[int]				=  ['''low''', '''er</w>''']
							snake_case_						:    Any				=  tokenizer.tokenize(__magic_name__    )
							self.assertListEqual(__magic_name__					,							__magic_name__    )

							snake_case_						:    Optional[int]				=  tokens + ['''<unk>''']
							snake_case_						:    List[str]				=  [14, 15, 20]
							self.assertListEqual(tokenizer.convert_tokens_to_ids(__magic_name__    )					,							__magic_name__    )






			@slow
			def 			lowerCamelCase  (self    )     ->   Optional[Any]:


							'''simple docstring'''



							snake_case_						:    Optional[int]				=  BioGptTokenizer.from_pretrained('''microsoft/biogpt'''    )

							snake_case_						:    List[Any]				=  tokenizer.encode('''sequence builders'''					,							add_special_tokens=__magic_name__    )
							snake_case_						:    str				=  tokenizer.encode('''multi-sequence build'''					,							add_special_tokens=__magic_name__    )

							snake_case_						:    str				=  tokenizer.build_inputs_with_special_tokens(__magic_name__    )
							snake_case_						:    List[str]				=  tokenizer.build_inputs_with_special_tokens(__magic_name__					,							__magic_name__    )

							self.assertTrue(encoded_sentence == [2] + text    )
							self.assertTrue(encoded_pair == [2] + text + [2] + text_a    )
