




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


SCREAMING_SNAKE_CASE__       :      int  =   {
    'configuration_pegasus_x': ['PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusXConfig'],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       SCREAMING_SNAKE_CASE__       :      Optional[Any]  =   [
           'PEGASUS_X_PRETRAINED_MODEL_ARCHIVE_LIST',
           'PegasusXForConditionalGeneration',
           'PegasusXModel',
           'PegasusXPreTrainedModel',
       ]


if TYPE_CHECKING:
       from .configuration_pegasus_x import PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP, PegasusXConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_pegasus_x import (
                  PEGASUS_X_PRETRAINED_MODEL_ARCHIVE_LIST,
                  PegasusXForConditionalGeneration,
                  PegasusXModel,
                  PegasusXPreTrainedModel,
              )


else:
       import sys

       SCREAMING_SNAKE_CASE__       :      Any  =   _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)








"""simple docstring"""





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

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


if is_sentencepiece_available():
    from .tokenization_fnet import FNetTokenizer
else:
    _a		       =							None

_a		       =							logging.get_logger(__name__)
_a		       =							{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

_a		       =							{
    'vocab_file': {
        'google/fnet-base': 'https://huggingface.co/google/fnet-base/resolve/main/spiece.model',
        'google/fnet-large': 'https://huggingface.co/google/fnet-large/resolve/main/spiece.model',
    },
    'tokenizer_file': {
        'google/fnet-base': 'https://huggingface.co/google/fnet-base/resolve/main/tokenizer.json',
        'google/fnet-large': 'https://huggingface.co/google/fnet-large/resolve/main/tokenizer.json',
    },
}

_a		       =							{
    'google/fnet-base': 512,
    'google/fnet-large': 512,
}

_a		       =							'▁'


class A_	(lowercase__      ):




  '''simple docstring'''
  SCREAMING_SNAKE_CASE__			:						List[str]       =		VOCAB_FILES_NAMES
  SCREAMING_SNAKE_CASE__			:						Tuple       =		PRETRAINED_VOCAB_FILES_MAP
  SCREAMING_SNAKE_CASE__			:						Any       =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  SCREAMING_SNAKE_CASE__			:						Union[str, Any]       =		["""input_ids""", """token_type_ids"""]
  SCREAMING_SNAKE_CASE__			:						Tuple       =		FNetTokenizer







  def __init__(		self				,   lowercase_=None				,   lowercase_=None				,   lowercase_=False				,   lowercase_=True				,   lowercase_=True				,   lowercase_="<unk>"				,   lowercase_="[SEP]"				,   lowercase_="<pad>"				,   lowercase_="[CLS]"				,   lowercase_="[MASK]"				,   **lowercase_				,   ):

     """simple docstring"""
     # Mask token behave like a normal word, i.e. include the space before it and
     # is included in the raw text, there should be a match in a non-normalized sentence.
     UpperCAmelCase_					:					int			     =    (
         AddedToken(lowercase_				,   lstrip=lowercase_				,   rstrip=lowercase_				,   normalized=lowercase_  )
         if isinstance(lowercase_				,   lowercase_  )
         else mask_token
     )

     super().__init__(
         lowercase_				,   tokenizer_file=lowercase_				,   do_lower_case=lowercase_				,   remove_space=lowercase_				,   keep_accents=lowercase_				,   unk_token=lowercase_				,   sep_token=lowercase_				,   pad_token=lowercase_				,   cls_token=lowercase_				,   mask_token=lowercase_				,   **lowercase_				,   )

     UpperCAmelCase_					:					Any			     =    do_lower_case
     UpperCAmelCase_					:					Tuple			     =    remove_space
     UpperCAmelCase_					:					str			     =    keep_accents
     UpperCAmelCase_					:					Any			     =    vocab_file
     UpperCAmelCase_					:					List[Any]			     =    False if not self.vocab_file else True







  def        UpperCamelCase__					(		self				,   lowercase_				,   lowercase_ = None  ):

     """simple docstring"""
     UpperCAmelCase_					:					Tuple			     =    [self.sep_token_id]
     UpperCAmelCase_					:					Any			     =    [self.cls_token_id]
     if token_ids_a is None:
        return cls + token_ids_a + sep
     return cls + token_ids_a + sep + token_ids_a + sep







  def        UpperCamelCase__					(		self				,   lowercase_				,   lowercase_ = None  ):

     """simple docstring"""
     UpperCAmelCase_					:					Any			     =    [self.sep_token_id]
     UpperCAmelCase_					:					Any			     =    [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  ) * [0] + len(token_ids_a + sep  ) * [1]







  def        UpperCamelCase__					(		self				,   lowercase_				,   lowercase_ = None  ):

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

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

     return (out_vocab_file,)


