



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:
				lowercase_	       =			None


lowercase_	       =			logging.get_logger(__name__)

lowercase_	       =			{'''vocab_file''': '''spiece.model''', '''tokenizer_file''': '''tokenizer.json'''}

lowercase_	       =			{
    '''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''',
    },
}

lowercase_	       =			{
    '''xlnet-base-cased''': None,
    '''xlnet-large-cased''': None,
}

lowercase_	       =			'''▁'''

# Segments (not really needed)
lowercase_	       =			0
lowercase_	       =			1
lowercase_	       =			2
lowercase_	       =			3
lowercase_	       =			4






class 						__a (     SCREAMING_SNAKE_CASE				):
	SCREAMING_SNAKE_CASE       =       VOCAB_FILES_NAMES
	SCREAMING_SNAKE_CASE       =       PRETRAINED_VOCAB_FILES_MAP
	SCREAMING_SNAKE_CASE       =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	SCREAMING_SNAKE_CASE       =       "left"
	SCREAMING_SNAKE_CASE       =       XLNetTokenizer



	def __init__(						self							:    int				,	snake_case_							:    str=None				,	snake_case_							:    Optional[int]=None				,	snake_case_							:    Tuple=False				,	snake_case_							:    Optional[Any]=True				,	snake_case_							:    List[str]=False				,	snake_case_							:    Optional[int]="<s>"				,	snake_case_							:    Any="</s>"				,	snake_case_							:    List[str]="<unk>"				,	snake_case_							:    Optional[Any]="<sep>"				,	snake_case_							:    Optional[int]="<pad>"				,	snake_case_							:    Any="<cls>"				,	snake_case_							:    List[str]="<mask>"				,	snake_case_							:    Union[str, Any]=["<eop>", "<eod>"]				,	**snake_case_							:    str				,	)->							Tuple:
						# Mask token behave like a normal word, i.e. include the space before it
						__lowerCAmelCase	   =AddedToken(snake_case_				,	lstrip=snake_case_				,	rstrip=snake_case_) if isinstance(snake_case_				,	snake_case_) else mask_token

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

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



	def 		UpperCamelCase							(						self							:    List[str]				,	snake_case_							:    List[int]				,	snake_case_							:    Optional[List[int]] = None)->							List[int]:
						__lowerCAmelCase	   =[self.sep_token_id]
						__lowerCAmelCase	   =[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 		UpperCamelCase							(						self							:    List[str]				,	snake_case_							:    List[int]				,	snake_case_							:    Optional[List[int]] = None)->							List[int]:
						__lowerCAmelCase	   =[self.sep_token_id]
						__lowerCAmelCase	   =[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 		UpperCamelCase							(						self							:    Optional[Any]				,	snake_case_							:    str				,	snake_case_							:    Optional[str] = None)->							Tuple[str]:
						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(snake_case_):
											logger.error(F"""Vocabulary path ({save_directory}) should be a directory""")
											return
						__lowerCAmelCase	   =os.path.join(
						    snake_case_				,	(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""])

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

						return (out_vocab_file,)









from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


lowercase_	       =			{
    '''configuration_encodec''': [
        '''ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''EncodecConfig''',
    ],
    '''feature_extraction_encodec''': ['''EncodecFeatureExtractor'''],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_	       =			[
				    '''ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''EncodecModel''',
				    '''EncodecPreTrainedModel''',
				]

if TYPE_CHECKING:
				from .configuration_encodec import (
				    ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    EncodecConfig,
				)
				from .feature_extraction_encodec import EncodecFeatureExtractor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_encodec import (
								    ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST,
								    EncodecModel,
								    EncodecPreTrainedModel,
								)

else:
				import sys

				lowercase_	       =			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




