






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__snake_case				   =    {
    """configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
    """tokenization_biogpt""": ["""BioGptTokenizer"""],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __snake_case				   =    [
     """BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """BioGptForCausalLM""",
     """BioGptForTokenClassification""",
     """BioGptForSequenceClassification""",
     """BioGptModel""",
     """BioGptPreTrainedModel""",
 ]


if TYPE_CHECKING:
 from .configuration_biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig
 from .tokenization_biogpt import BioGptTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_biogpt import (
      BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
      BioGptForCausalLM,
      BioGptForSequenceClassification,
      BioGptForTokenClassification,
      BioGptModel,
      BioGptPreTrainedModel,
  )


else:
 import sys

 __snake_case				   =    _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)













import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
     from .tokenization_pegasus import PegasusTokenizer
else:
     UpperCAmelCase__							  =						None


UpperCAmelCase__							  =						logging.get_logger(__name__)


UpperCAmelCase__							  =						"▁"

UpperCAmelCase__							  =						{"vocab_file": "spiece.model", "tokenizer_file": "tokenizer.json"}

UpperCAmelCase__							  =						{
    "vocab_file": {"google/pegasus-xsum": "https://huggingface.co/google/pegasus-xsum/resolve/main/spiece.model"},
    "tokenizer_file": {
        "google/pegasus-xsum": "https://huggingface.co/google/pegasus-xsum/resolve/main/tokenizer.json"
    },
}

UpperCAmelCase__							  =						{
    "google/pegasus-xsum": 512,
}






class 						lowercase_   (      lowercase  ):






      '''simple docstring'''




      __snake_case	    =    VOCAB_FILES_NAMES
      __snake_case	    =    PRETRAINED_VOCAB_FILES_MAP
      __snake_case	    =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      __snake_case	    =    PegasusTokenizer
      __snake_case	    =    ['''input_ids''', '''attention_mask''']







      def __init__( self :		List[Any]					,   __UpperCAmelCase :		str=None					,   __UpperCAmelCase :		List[Any]=None					,   __UpperCAmelCase :		Any="<pad>"					,   __UpperCAmelCase :		str="</s>"					,   __UpperCAmelCase :		List[str]="<unk>"					,   __UpperCAmelCase :		List[str]="<mask_2>"					,   __UpperCAmelCase :		Tuple="<mask_1>"					,   __UpperCAmelCase :		int=None					,   __UpperCAmelCase :		str=103					,   **__UpperCAmelCase :		Optional[int]					,   )       ->Dict:




       """simple docstring"""


       a						    = offset

       if additional_special_tokens is not None:
        if not isinstance(__UpperCAmelCase					,   __UpperCAmelCase    ):
         raise TypeError(
             F"""additional_special_tokens should be of type {type(__UpperCAmelCase    )}, but is"""
             F""" {type(__UpperCAmelCase    )}"""    )

        a						    = (
            ([mask_token_sent] + additional_special_tokens)
            if mask_token_sent not in additional_special_tokens and mask_token_sent is not None
            else additional_special_tokens
        )
        # fill additional tokens with ..., <unk_token_102> in case not all additional tokens are already taken
        additional_special_tokens_extended += [
            F"""<unk_{i}>""" for i in range(len(__UpperCAmelCase    )					,   self.offset - 1    )
        ]

        if len(set(__UpperCAmelCase    )    ) != len(__UpperCAmelCase    ):
         raise ValueError(
             '''Please make sure that the provided additional_special_tokens do not contain an incorrectly'''
             F""" shifted list of <unk_x> tokens. Found {additional_special_tokens_extended}."""    )
        a						    = additional_special_tokens_extended
       else:
        a						    = [mask_token_sent] if mask_token_sent is not None else []
        additional_special_tokens += [F"""<unk_{i}>""" for i in range(2					,   self.offset    )]

       super().__init__(
           __UpperCAmelCase					,   tokenizer_file=__UpperCAmelCase					,   pad_token=__UpperCAmelCase					,   eos_token=__UpperCAmelCase					,   unk_token=__UpperCAmelCase					,   mask_token=__UpperCAmelCase					,   mask_token_sent=__UpperCAmelCase					,   offset=__UpperCAmelCase					,   additional_special_tokens=__UpperCAmelCase					,   **__UpperCAmelCase					,   )
       a						    = vocab_file
       a						    = False if not self.vocab_file else True







      def  __lowerCAmelCase   ( self :		Optional[Any]					,   __UpperCAmelCase :		int    )       ->int:




       """simple docstring"""


       a						    = set(self.all_special_ids    )  # call it once instead of inside list comp
       all_special_ids.remove(self.unk_token_id    )  # <unk> is only sometimes special

       if all_special_ids != set(range(len(self.additional_special_tokens    ) + 3    )    ):
        raise ValueError(
            '''There should be 3 special tokens: mask_token, pad_token, and eos_token +'''
            F""" {len(self.additional_special_tokens    )} additional_special_tokens, but got {all_special_ids}"""    )

       return [1 if x in all_special_ids else 0 for x in seq]







      def  __lowerCAmelCase   ( self :		Dict					,   __UpperCAmelCase :		List					,   __UpperCAmelCase :		Optional[List] = None					,   __UpperCAmelCase :		bool = False    )       ->List[int]:




       """simple docstring"""


       if already_has_special_tokens:
        return self._special_token_mask(__UpperCAmelCase    )
       elif token_ids_a is None:
        return self._special_token_mask(__UpperCAmelCase    ) + [1]
       else:
        return self._special_token_mask(token_ids_a + token_ids_a    ) + [1]







      def  __lowerCAmelCase   ( self :		Union[str, Any]					,   __UpperCAmelCase :		int					,   __UpperCAmelCase :		Optional[int]=None    )       ->List[int]:




       """simple docstring"""


       if token_ids_a is None:
        return token_ids_a + [self.eos_token_id]
       # We don't expect to process pairs, but leave the pair logic for API consistency
       return token_ids_a + token_ids_a + [self.eos_token_id]







      def  __lowerCAmelCase   ( self :		Dict					,   __UpperCAmelCase :		str					,   __UpperCAmelCase :		Optional[str] = None    )       ->Tuple[str]:




       """simple docstring"""


       if not self.can_save_slow_tokenizer:
        raise ValueError(
            '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
            '''tokenizer.'''    )

       if not os.path.isdir(__UpperCAmelCase    ):
        logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""    )
        return
       a						    = os.path.join(
           __UpperCAmelCase					,   (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']    )

       if os.path.abspath(self.vocab_file    ) != os.path.abspath(__UpperCAmelCase    ):
        copyfile(self.vocab_file					,   __UpperCAmelCase    )

       return (out_vocab_file,)


