




from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


_lowerCamelCase					:     Any				       =    logging.get_logger(__name__)

class     lowercase (      A__):
				__lowerCAmelCase      :      Dict					    =				["""input_ids""", """attention_mask"""]







				def __init__(							self				:   Optional[int] ,       _lowerCamelCase				:   Optional[Any]="[PAD]" ,       _lowerCamelCase				:   Any="[BOS]" ,       _lowerCamelCase				:   Optional[Any]="[EOS]" ,       _lowerCamelCase				:   str="[MASK]" ,       _lowerCamelCase				:   List[Any]="[CLS]" ,       _lowerCamelCase				:   str="[SEP]" ,       _lowerCamelCase				:   int=20_48 ,       **_lowerCamelCase				:   Tuple ,       ):



					"""simple docstring"""

					A_					:			str						=						AddedToken(_A ,       lstrip=_A ,       rstrip=_A    ) if isinstance(_A ,       _A    ) else pad_token
					A_					:			Dict						=						AddedToken(_A ,       lstrip=_A ,       rstrip=_A    ) if isinstance(_A ,       _A    ) else bos_token
					A_					:			Optional[int]						=						AddedToken(_A ,       lstrip=_A ,       rstrip=_A    ) if isinstance(_A ,       _A    ) else eos_token
					A_					:			Dict						=						AddedToken(_A ,       lstrip=_A ,       rstrip=_A    ) if isinstance(_A ,       _A    ) else mask_token
					A_					:			int						=						AddedToken(_A ,       lstrip=_A ,       rstrip=_A    ) if isinstance(_A ,       _A    ) else cls_token
					A_					:			str						=						AddedToken(_A ,       lstrip=_A ,       rstrip=_A    ) if isinstance(_A ,       _A    ) else sep_token

					super().__init__(
					    pad_token=_A ,       bos_token=_A ,       eos_token=_A ,       mask_token=_A ,       cls_token=_A ,       sep_token=_A ,       model_max_length=_A ,       **_A ,       )

					A_					:			int						=						2**8  # utf is 8 bits

					# define special tokens dict
					A_					:			Dict[str, int]						=						{
					    self.pad_token: 0,
					    self.bos_token: 1,
					    self.eos_token: 2,
					    self.mask_token: 3,
					    self.cls_token: 4,
					    self.sep_token: 5,
					}
					A_					:			str						=						len(self.special_tokens_encoder    )
					A_					:			Dict[int, str]						=						{v: k for k, v in self.special_tokens_encoder.items()}







				def    a_					(							self				:   Any    ):



					"""simple docstring"""

					A_					:			str						=						self.special_tokens_encoder.copy()
					vocab.update(self.added_tokens_encoder    )
					for i in range(self._utf_vocab_size    ):
						A_					:			str						=						chr(_A    )
						A_					:			Union[str, Any]						=						i + len(self.special_tokens_encoder    )
					return vocab







				@property
				def    a_					(							self				:   Optional[int]    ):



					"""simple docstring"""

					return self._utf_vocab_size + self._num_special_tokens







				def    a_					(							self				:   Optional[Any] ,       _lowerCamelCase				:   List[int] ,       _lowerCamelCase				:   Optional[List[int]] = None ,       _lowerCamelCase				:   bool = False    ):



					"""simple docstring"""

					if already_has_special_tokens:
						return super().get_special_tokens_mask(
						    token_ids_a=_A ,       token_ids_a=_A ,       already_has_special_tokens=_A    )

					# normal case: some special tokens
					if token_ids_a is None:
						return [1] + [0] * len(_A    ) + [1]
					return [1] + ([0] * len(_A    )) + [1] + ([0] * len(_A    )) + [1]







				def    a_					(							self				:   str ,       _lowerCamelCase				:   List[int] ,       _lowerCamelCase				:   Optional[List[int]] = None    ):



					"""simple docstring"""

					if token_ids_a is None:
						return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
					else:
						return [self.cls_token_id] + token_ids_a + [self.sep_token_id] + token_ids_a + [self.sep_token_id]







				def    a_					(							self				:   Optional[Any] ,       _lowerCamelCase				:   str    ):



					"""simple docstring"""

					A_					:			Optional[Any]						=						[chr(_A    ) for i in text.encode('''utf-8'''    )]
					return tokens







				def    a_					(							self				:   Optional[Any] ,       _lowerCamelCase				:   str    ):



					"""simple docstring"""

					if token in self.special_tokens_encoder:
						A_					:			int						=						self.special_tokens_encoder[token]
					elif token in self.added_tokens_encoder:
						A_					:			Optional[Any]						=						self.added_tokens_encoder[token]
					elif len(_A    ) != 1:
						A_					:			int						=						self.unk_token_id
					else:
						A_					:			Any						=						ord(_A    ) + self._num_special_tokens
					return token_id







				def    a_					(							self				:   Union[str, Any] ,       _lowerCamelCase				:   Dict    ):



					"""simple docstring"""

					if index in self.special_tokens_decoder:
						A_					:			Tuple						=						self.special_tokens_decoder[index]
					elif index in self.added_tokens_decoder:
						A_					:			Optional[Any]						=						self.added_tokens_decoder[index]
					else:
						A_					:			Union[str, Any]						=						chr(index - self._num_special_tokens    )
					return token







				def    a_					(							self				:   Optional[Any] ,       _lowerCamelCase				:   str    ):



					"""simple docstring"""

					A_					:			Optional[int]						=						B""
					for token in tokens:
						if token in self.special_tokens_decoder:
							A_					:			List[str]						=						self.special_tokens_decoder[token].encode('''utf-8'''    )
						elif token in self.added_tokens_decoder:
							A_					:			Union[str, Any]						=						self.special_tokens_decoder[token].encode('''utf-8'''    )
						elif token in self.special_tokens_encoder:
							A_					:			str						=						token.encode('''utf-8'''    )
						elif token in self.added_tokens_encoder:
							A_					:			Optional[int]						=						token.encode('''utf-8'''    )
						else:
							A_					:			Any						=						bytes([ord(_A    )]    )
						bstring += tok_string
					A_					:			int						=						bstring.decode('''utf-8''' ,       errors='''replace'''    )
					return string







				def    a_					(							self				:   Dict ,       _lowerCamelCase				:   str ,       _lowerCamelCase				:   Optional[str] = None    ):



					"""simple docstring"""

					return ()











"""simple docstring"""

import enum
import inspect
import warnings
from functools import wraps
from typing import Callable, Optional

from .logging import get_logger


_lowerCamelCase					:     Optional[int]				       =    set()
_lowerCamelCase					:     Union[str, Any]				       =    get_logger(__name__)

def 						lowercase_ (						_UpperCAmelCase = None		):




	"""simple docstring"""






	def decorator(_UpperCAmelCase		):
		global _emitted_deprecation_warnings

		if inspect.isclass(_UpperCAmelCase		):
			A_					:			Union[str, Any]						=						deprecated_class_or_function.__init__
			A_					:			int						=						deprecated_class_or_function.__name__
		else:
			A_					:			Union[str, Any]						=						deprecated_class_or_function
			A_					:			List[Any]						=						deprecated_function.__name__
			# Support deprecating __init__ class method: class name instead
			A_					:			List[Any]						=						name if name != '''__init__''' else deprecated_function.__qualname__.split('''.'''		)[-2]

		A_					:			str						=						(
		    f"""{name} is deprecated and will be removed in the next major version of datasets.""" + f""" {help_message}"""
		    if help_message
		    else ''''''
		)

		@wraps(_UpperCAmelCase		)
		def wrapper(*_UpperCAmelCase					, **_UpperCAmelCase		):
			A_					:			Any						=						hash(_UpperCAmelCase		)
			if func_hash not in _emitted_deprecation_warnings:
				warnings.warn(_UpperCAmelCase					, category=_UpperCAmelCase					, stacklevel=2		)
				_emitted_deprecation_warnings.add(_UpperCAmelCase		)
			return deprecated_function(*_UpperCAmelCase					, **_UpperCAmelCase		)

		A_					:			Any						=						'''deprecated'''

		if inspect.isclass(_UpperCAmelCase		):
			A_					:			List[Any]						=						wrapper
			return deprecated_class_or_function
		else:
			return wrapper

	return decorator

class     lowercase (      enum.EnumMeta):







				def __getattribute__(							cls				:   Any ,       _lowerCamelCase				:   List[Any]    ):



					"""simple docstring"""

					A_					:			str						=						super().__getattribute__(_lowerCamelCase    )
					if isinstance(_lowerCamelCase ,       enum.Enum    ) and obj._on_access:
						obj._on_access()
					return obj







				def __getitem__(							cls				:   Any ,       _lowerCamelCase				:   Union[str, Any]    ):



					"""simple docstring"""

					A_					:			Optional[Any]						=						super().__getitem__(_lowerCamelCase    )
					if member._on_access:
						member._on_access()
					return member







				def __call__(							cls				:   str ,       _lowerCamelCase				:   str ,       _lowerCamelCase				:   List[Any]=None ,       *, _lowerCamelCase				:   int=None ,       _lowerCamelCase				:   str=None ,       _lowerCamelCase				:   Dict=None ,       _lowerCamelCase				:   Tuple=1    ):



					"""simple docstring"""

					A_					:			Dict						=						super().__call__(_lowerCamelCase ,       _lowerCamelCase ,       module=_lowerCamelCase ,       qualname=_lowerCamelCase ,       type=_lowerCamelCase ,       start=_lowerCamelCase    )
					if isinstance(_lowerCamelCase ,       enum.Enum    ) and obj._on_access:
						obj._on_access()
					return obj

class     lowercase (      enum.Enum       ,		metaclass=__UpperCAmelCase):







				def __new__(							cls				:   Optional[Any] ,       _lowerCamelCase				:   int    ):



					"""simple docstring"""

					A_					:			Tuple						=						object.__new__(cls    )
					A_					:			Union[str, Any]						=						value
					A_					:			Union[str, Any]						=						member.deprecate
					return member







				@property
				def    a_					(							self				:   Tuple    ):



					"""simple docstring"""

					return ""







				def    a_					(							self				:   Any    ):



					"""simple docstring"""

					A_					:			Optional[int]						=						F""" {self.help_message}""" if self.help_message else ''''''
					warnings.warn(
					    F"""'{self.__objclass__.__name__}' is deprecated and will be removed in the next major version of datasets."""
					    + help_message ,       _lowerCamelCase ,       stacklevel=3 ,       )





