






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_xlnet import XLNetTokenizer
else:
       __magic_name__   :  Tuple        =							None


__magic_name__   :  Optional[int]        =							logging.get_logger(__name__)

__magic_name__   :  Union[str, Any]        =							{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

__magic_name__   :  Optional[int]        =							{
    'vocab_file': {
        'xlnet-base-cased': 'https://huggingface.co/xlnet-base-cased/resolve/main/spiece.model',
        'xlnet-large-cased': 'https://huggingface.co/xlnet-large-cased/resolve/main/spiece.model',
    },
    'tokenizer_file': {
        'xlnet-base-cased': 'https://huggingface.co/xlnet-base-cased/resolve/main/tokenizer.json',
        'xlnet-large-cased': 'https://huggingface.co/xlnet-large-cased/resolve/main/tokenizer.json',
    },
}

__magic_name__   :  Optional[Any]        =							{
    'xlnet-base-cased': None,
    'xlnet-large-cased': None,
}

__magic_name__   :  Tuple        =							'▁'

# Segments (not really needed)
__magic_name__   :  Dict        =							0
__magic_name__   :  str        =							1
__magic_name__   :  Optional[int]        =							2
__magic_name__   :  List[str]        =							3
__magic_name__   :  List[Any]        =							4





class 					A__     (     A__ ):

     '''simple docstring'''






     snake_case__					=					VOCAB_FILES_NAMES
     snake_case__					=					PRETRAINED_VOCAB_FILES_MAP
     snake_case__					=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     snake_case__					=					"""left"""
     snake_case__					=					XLNetTokenizer







     def __init__( self      :    Tuple   ,						_SCREAMING_SNAKE_CASE      :    Optional[Any]=None   ,						_SCREAMING_SNAKE_CASE      :    Tuple=None   ,						_SCREAMING_SNAKE_CASE      :    List[str]=False   ,						_SCREAMING_SNAKE_CASE      :    Any=True   ,						_SCREAMING_SNAKE_CASE      :    Dict=False   ,						_SCREAMING_SNAKE_CASE      :    Tuple="<s>"   ,						_SCREAMING_SNAKE_CASE      :    str="</s>"   ,						_SCREAMING_SNAKE_CASE      :    Tuple="<unk>"   ,						_SCREAMING_SNAKE_CASE      :    Union[str, Any]="<sep>"   ,						_SCREAMING_SNAKE_CASE      :    Union[str, Any]="<pad>"   ,						_SCREAMING_SNAKE_CASE      :    Dict="<cls>"   ,						_SCREAMING_SNAKE_CASE      :    List[Any]="<mask>"   ,						_SCREAMING_SNAKE_CASE      :    Union[str, Any]=["<eop>", "<eod>"]   ,						**_SCREAMING_SNAKE_CASE      :    str   ,						):






           """simple docstring"""




           UpperCamelCase					       =  AddedToken(_SCREAMING_SNAKE_CASE   ,						lstrip=_SCREAMING_SNAKE_CASE   ,						rstrip=_SCREAMING_SNAKE_CASE ) if isinstance(_SCREAMING_SNAKE_CASE   ,						_SCREAMING_SNAKE_CASE ) else mask_token

           super().__init__(
               vocab_file=_SCREAMING_SNAKE_CASE   ,						tokenizer_file=_SCREAMING_SNAKE_CASE   ,						do_lower_case=_SCREAMING_SNAKE_CASE   ,						remove_space=_SCREAMING_SNAKE_CASE   ,						keep_accents=_SCREAMING_SNAKE_CASE   ,						bos_token=_SCREAMING_SNAKE_CASE   ,						eos_token=_SCREAMING_SNAKE_CASE   ,						unk_token=_SCREAMING_SNAKE_CASE   ,						sep_token=_SCREAMING_SNAKE_CASE   ,						pad_token=_SCREAMING_SNAKE_CASE   ,						cls_token=_SCREAMING_SNAKE_CASE   ,						mask_token=_SCREAMING_SNAKE_CASE   ,						additional_special_tokens=_SCREAMING_SNAKE_CASE   ,						**_SCREAMING_SNAKE_CASE   ,						)

           UpperCamelCase					       =  3
           UpperCamelCase					       =  do_lower_case
           UpperCamelCase					       =  remove_space
           UpperCamelCase					       =  keep_accents
           UpperCamelCase					       =  vocab_file
           UpperCamelCase					       =  False if not self.vocab_file else True







     def   _SCREAMING_SNAKE_CASE     ( self      :    Union[str, Any]   ,						_SCREAMING_SNAKE_CASE      :    List[int]   ,						_SCREAMING_SNAKE_CASE      :    Optional[List[int]] = None ):






           """simple docstring"""




           UpperCamelCase					       =  [self.sep_token_id]
           UpperCamelCase					       =  [self.cls_token_id]
           if token_ids_a is None:
                 return token_ids_a + sep + cls
           return token_ids_a + sep + token_ids_a + sep + cls







     def   _SCREAMING_SNAKE_CASE     ( self      :    Dict   ,						_SCREAMING_SNAKE_CASE      :    List[int]   ,						_SCREAMING_SNAKE_CASE      :    Optional[List[int]] = None ):






           """simple docstring"""




           UpperCamelCase					       =  [self.sep_token_id]
           UpperCamelCase					       =  [2]

           if token_ids_a is None:
                 return len(token_ids_a + sep ) * [0] + cls_segment_id
           return len(token_ids_a + sep ) * [0] + len(token_ids_a + sep ) * [1] + cls_segment_id







     def   _SCREAMING_SNAKE_CASE     ( self      :    Optional[Any]   ,						_SCREAMING_SNAKE_CASE      :    str   ,						_SCREAMING_SNAKE_CASE      :    Optional[str] = None ):






           """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(_SCREAMING_SNAKE_CASE ):
                 logger.error(f'Vocabulary path ({save_directory}) should be a directory' )
                 return
           UpperCamelCase					       =  os.path.join(
               _SCREAMING_SNAKE_CASE   ,						(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'] )

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

           return (out_vocab_file,)











from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A__      :     Optional[int]       =					{
    'configuration_clap': [
        'CLAP_PRETRAINED_MODEL_ARCHIVE_LIST',
        'ClapAudioConfig',
        'ClapConfig',
        'ClapTextConfig',
    ],
    'processing_clap': ['ClapProcessor'],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A__      :     str       =					[
							    'CLAP_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'ClapModel',
							    'ClapPreTrainedModel',
							    'ClapTextModel',
							    'ClapTextModelWithProjection',
							    'ClapAudioModel',
							    'ClapAudioModelWithProjection',
							]
							A__      :     List[Any]       =					['ClapFeatureExtractor']

if TYPE_CHECKING:
							from .configuration_clap import (
							    CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
							    ClapAudioConfig,
							    ClapConfig,
							    ClapTextConfig,
							)
							from .processing_clap import ClapProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_clap import ClapFeatureExtractor
														from .modeling_clap import (
														    CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
														    ClapAudioModel,
														    ClapAudioModelWithProjection,
														    ClapModel,
														    ClapPreTrainedModel,
														    ClapTextModel,
														    ClapTextModelWithProjection,
														)


else:
							import sys

							A__      :     int       =					_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




