



'''simple docstring'''

import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

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


__lowerCAmelCase		     =  logging.get_logger(__name__)

__lowerCAmelCase		     =  {'''vocab_file''': '''spiece.model'''}

__lowerCAmelCase		     =  {
    '''vocab_file''': {
        '''TsinghuaAI/CPM-Generate''': '''https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/spiece.model''',
    }
}

class       __magic_name__		(       _UpperCamelCase  ):







							def __init__(				self   :			Optional[int]      ,_UpperCAmelCase   :			int      ,_UpperCAmelCase   :			Union[str, Any]=False      ,_UpperCAmelCase   :			int=True      ,_UpperCAmelCase   :			List[str]=False      ,_UpperCAmelCase   :			Any="<s>"      ,_UpperCAmelCase   :			Tuple="</s>"      ,_UpperCAmelCase   :			List[str]="<unk>"      ,_UpperCAmelCase   :			Optional[int]="<sep>"      ,_UpperCAmelCase   :			List[Any]="<pad>"      ,_UpperCAmelCase   :			List[Any]="<cls>"      ,_UpperCAmelCase   :			Optional[int]="<mask>"      ,_UpperCAmelCase   :			List[str]=["<eop>", "<eod>"]      ,_UpperCAmelCase   :			Optional[Dict[str, Any]] = None      ,**_UpperCAmelCase   :			Dict      ,):
									_a	: int								=				AddedToken(_UpperCAmelCase      ,lstrip=_UpperCAmelCase      ,rstrip=_UpperCAmelCase						) if isinstance(_UpperCAmelCase      ,_UpperCAmelCase						) else mask_token

									_a	: Optional[Any]								=				{} if sp_model_kwargs is None else sp_model_kwargs

									super().__init__(
									    do_lower_case=_UpperCAmelCase      ,remove_space=_UpperCAmelCase      ,keep_accents=_UpperCAmelCase      ,bos_token=_UpperCAmelCase      ,eos_token=_UpperCAmelCase      ,unk_token=_UpperCAmelCase      ,sep_token=_UpperCAmelCase      ,pad_token=_UpperCAmelCase      ,cls_token=_UpperCAmelCase      ,mask_token=_UpperCAmelCase      ,additional_special_tokens=_UpperCAmelCase      ,sp_model_kwargs=self.sp_model_kwargs      ,**_UpperCAmelCase      ,)

									_a	: List[str]								=				3

									_a	: Union[str, Any]								=				do_lower_case
									_a	: Any								=				remove_space
									_a	: List[str]								=				keep_accents
									_a	: int								=				vocab_file

									_a	: Union[str, Any]								=				spm.SentencePieceProcessor(**self.sp_model_kwargs						)
									self.sp_model.Load(_UpperCAmelCase						)

									try:
											import jieba
									except ModuleNotFoundError as error:
											raise error.__class__(
											    'You need to install jieba to use CpmTokenizer or CpmTokenizerFast. '
											    'See https://pypi.org/project/jieba/ for installation.'						)
									_a	: Tuple								=				jieba
									_a	: Optional[Any]								=				str.maketrans(' \n'      ,'\u2582\u2583'						)







							@property
							# Copied from transformers.models.xlnet.tokenization_xlnet.XLNetTokenizer.vocab_size
							def 				__lowercase     (				self   :			str						):
									return len(self.sp_model						)







							def 				__lowercase     (				self   :			Any						):
									_a	: Union[str, Any]								=				{self.convert_ids_to_tokens(_UpperCAmelCase						): i for i in range(self.vocab_size						)}
									vocab.update(self.added_tokens_encoder						)
									return vocab







							def __getstate__(				self   :			Union[str, Any]						):
									_a	: Dict								=				self.__dict__.copy()
									_a	: Any								=				None
									return state







							def __setstate__(				self   :			str      ,_UpperCAmelCase   :			List[Any]						):
									_a	: Tuple								=				d

									# for backward compatibility
									if not hasattr(self      ,'sp_model_kwargs'						):
											_a	: str								=				{}

									_a	: List[Any]								=				spm.SentencePieceProcessor(**self.sp_model_kwargs						)
									self.sp_model.Load(self.vocab_file						)







							def 				__lowercase     (				self   :			Dict      ,_UpperCAmelCase   :			Any						):
									if self.remove_space:
											_a	: Any								=				' '.join(inputs.strip().split()						)
									else:
											_a	: Any								=				inputs
									_a	: List[Any]								=				outputs.replace('``'      ,'"'						).replace('\'\''      ,'"'						)

									if not self.keep_accents:
											_a	: int								=				unicodedata.normalize('NFKD'      ,_UpperCAmelCase						)
											_a	: List[Any]								=				''.join([c for c in outputs if not unicodedata.combining(_UpperCAmelCase						)]						)
									if self.do_lower_case:
											_a	: List[Any]								=				outputs.lower()

									return outputs







							def 				__lowercase     (				self   :			int      ,_UpperCAmelCase   :			str						):
									_a	: Optional[Any]								=				self.preprocess_text(_UpperCAmelCase						)
									_a	: Any								=				self.sp_model.encode(_UpperCAmelCase      ,out_type=_UpperCAmelCase						)
									_a	: List[str]								=				[]
									for piece in pieces:
											if len(_UpperCAmelCase						) > 1 and piece[-1] == str(','						) and piece[-2].isdigit():
													_a	: int								=				self.sp_model.EncodeAsPieces(piece[:-1].replace(_UpperCAmelCase      ,''						)						)
													if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
															if len(cur_pieces[0]						) == 1:
																	_a	: Optional[int]								=				cur_pieces[1:]
															else:
																	_a	: str								=				cur_pieces[0][1:]
													cur_pieces.append(piece[-1]						)
													new_pieces.extend(_UpperCAmelCase						)
											else:
													new_pieces.append(_UpperCAmelCase						)

									return new_pieces







							def 				__lowercase     (				self   :			int      ,_UpperCAmelCase   :			List[str]						):
									return self.sp_model.PieceToId(_UpperCAmelCase						)







							def 				__lowercase     (				self   :			Any      ,_UpperCAmelCase   :			Union[str, Any]						):
									return self.sp_model.IdToPiece(_UpperCAmelCase						)







							def 				__lowercase     (				self   :			Dict      ,_UpperCAmelCase   :			List[str]						):
									_a	: List[str]								=				''.join(_UpperCAmelCase						).replace(_UpperCAmelCase      ,' '						).strip()
									return out_string







							def 				__lowercase     (				self   :			Union[str, Any]      ,_UpperCAmelCase   :			List[int]      ,_UpperCAmelCase   :			Optional[List[int]] = None						):
									_a	: List[str]								=				[self.sep_token_id]
									_a	: Tuple								=				[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 				__lowercase     (				self   :			str      ,_UpperCAmelCase   :			List[int]      ,_UpperCAmelCase   :			Optional[List[int]] = None      ,_UpperCAmelCase   :			bool = False						):

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

									if token_ids_a is not None:
											return ([0] * len(_UpperCAmelCase						)) + [1] + ([0] * len(_UpperCAmelCase						)) + [1, 1]
									return ([0] * len(_UpperCAmelCase						)) + [1, 1]







							def 				__lowercase     (				self   :			Union[str, Any]      ,_UpperCAmelCase   :			List[int]      ,_UpperCAmelCase   :			Optional[List[int]] = None						):
									_a	: Optional[Any]								=				[self.sep_token_id]
									_a	: Dict								=				[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 				__lowercase     (				self   :			Tuple      ,_UpperCAmelCase   :			str      ,_UpperCAmelCase   :			Optional[str] = None						):
									if not os.path.isdir(_UpperCAmelCase						):
											logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""						)
											return
									_a	: str								=				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						) and os.path.isfile(self.vocab_file						):
											copyfile(self.vocab_file      ,_UpperCAmelCase						)
									elif not os.path.isfile(self.vocab_file						):
											with open(_UpperCAmelCase      ,'wb'						) as fi:
													_a	: List[str]								=				self.sp_model.serialized_model_proto()
													fi.write(_UpperCAmelCase						)

									return (out_vocab_file,)







							def 				__lowercase     (				self   :			int      ,*_UpperCAmelCase   :			Union[str, Any]      ,**_UpperCAmelCase   :			Any						):
									_a	: Tuple								=				super()._decode(*_UpperCAmelCase      ,**_UpperCAmelCase						)
									_a	: List[str]								=				text.replace(' '      ,''						).replace('\u2582'      ,' '						).replace('\u2583'      ,'\n'						)
									return text









'''simple docstring'''

import warnings

from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor


__lowerCAmelCase		     =  logging.get_logger(__name__)

class       __magic_name__		(       _UpperCamelCase  ):







							def __init__(				self   :			Optional[int]      ,*_UpperCAmelCase   :			List[Any]      ,**_UpperCAmelCase   :			Union[str, Any]						):
									warnings.warn(
									    'The class GLPNFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
									    ' use GLPNImageProcessor instead.'      ,_UpperCAmelCase      ,)
									super().__init__(*_UpperCAmelCase      ,**_UpperCAmelCase						)




