






"""simple docstring"""




from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_snake_case          =   logging.get_logger(__name__)

_snake_case          =   {
    'microsoft/beit-base-patch16-224-pt22k': (
        'https://huggingface.co/microsoft/beit-base-patch16-224-pt22k/resolve/main/config.json'
    ),
    # See all BEiT models at https://huggingface.co/models?filter=beit
}






class        UpperCamelCase			(	snake_case_      ):
 UpperCamelCase					:       List[str]			=					'''beit'''


 def __init__(     self		:						List[str]							,						UpperCAmelCase__		:						Tuple=8192							,						UpperCAmelCase__		:						Optional[int]=768							,						UpperCAmelCase__		:						Any=12							,						UpperCAmelCase__		:						List[Any]=12							,						UpperCAmelCase__		:						List[Any]=3072							,						UpperCAmelCase__		:						Union[str, Any]="gelu"							,						UpperCAmelCase__		:						Optional[Any]=0.0							,						UpperCAmelCase__		:						Optional[int]=0.0							,						UpperCAmelCase__		:						Union[str, Any]=0.0_2							,						UpperCAmelCase__		:						str=1E-12							,						UpperCAmelCase__		:						Optional[int]=224							,						UpperCAmelCase__		:						List[Any]=16							,						UpperCAmelCase__		:						Union[str, Any]=3							,						UpperCAmelCase__		:						int=False							,						UpperCAmelCase__		:						Optional[Any]=False							,						UpperCAmelCase__		:						Tuple=False							,						UpperCAmelCase__		:						Tuple=False							,						UpperCAmelCase__		:						Optional[Any]=0.1							,						UpperCAmelCase__		:						Optional[int]=0.1							,						UpperCAmelCase__		:						int=True							,						UpperCAmelCase__		:						Union[str, Any]=[3, 5, 7, 11]							,						UpperCAmelCase__		:						List[Any]=[1, 2, 3, 6]							,						UpperCAmelCase__		:						List[str]=True							,						UpperCAmelCase__		:						int=0.4							,						UpperCAmelCase__		:						Optional[Any]=256							,						UpperCAmelCase__		:						Optional[Any]=1							,						UpperCAmelCase__		:						int=False							,						UpperCAmelCase__		:						Dict=255							,						**UpperCAmelCase__		:						List[str]							,						)					->       Any:
   super().__init__(**UpperCAmelCase__							)

   _a  :       List[str]             =	vocab_size
   _a  :       Optional[Any]             =	hidden_size
   _a  :       Tuple             =	num_hidden_layers
   _a  :       Union[str, Any]             =	num_attention_heads
   _a  :       Tuple             =	intermediate_size
   _a  :       Dict             =	hidden_act
   _a  :       List[str]             =	hidden_dropout_prob
   _a  :       Any             =	attention_probs_dropout_prob
   _a  :       List[Any]             =	initializer_range
   _a  :       Any             =	layer_norm_eps

   _a  :       str             =	image_size
   _a  :       Union[str, Any]             =	patch_size
   _a  :       str             =	num_channels
   _a  :       List[str]             =	use_mask_token
   _a  :       int             =	use_absolute_position_embeddings
   _a  :       Tuple             =	use_relative_position_bias
   _a  :       Dict             =	use_shared_relative_position_bias
   _a  :       List[Any]             =	layer_scale_init_value
   _a  :       int             =	drop_path_rate
   _a  :       Tuple             =	use_mean_pooling
   # decode head attributes (semantic segmentation)
   _a  :       Optional[Any]             =	out_indices
   _a  :       Tuple             =	pool_scales
   # auxiliary head attributes (semantic segmentation)
   _a  :       List[Any]             =	use_auxiliary_head
   _a  :       Union[str, Any]             =	auxiliary_loss_weight
   _a  :       str             =	auxiliary_channels
   _a  :       Dict             =	auxiliary_num_convs
   _a  :       List[str]             =	auxiliary_concat_input
   _a  :       Dict             =	semantic_loss_ignore_index







class        UpperCamelCase			(	snake_case_      ):
 UpperCamelCase					:       str			=					version.parse('''1.11'''      )


 @property
 def _lowercase	(     self		:						Tuple							)					->       Mapping[str, Mapping[int, str]]:
   return OrderedDict(
       [
           ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
       ]							)







 @property
 def _lowercase	(     self		:						Optional[Any]							)					->       float:
   return 1E-4









"""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


_snake_case          =   logging.get_logger(__name__)

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

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






class        UpperCamelCase			(	snake_case_      ):


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

   _a  :       Union[str, 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  :       Optional[Any]             =	3

   _a  :       Tuple             =	do_lower_case
   _a  :       Tuple             =	remove_space
   _a  :       Tuple             =	keep_accents
   _a  :       Tuple             =	vocab_file

   _a  :       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  :       int             =	jieba
   _a  :       Tuple             =	str.maketrans(""" \n"""							,						"""\u2582\u2583"""							)


 @property
 # Copied from transformers.models.xlnet.tokenization_xlnet.XLNetTokenizer.vocab_size
 def _lowercase	(     self		:						Optional[Any]							)					->       Any:
   return len(self.sp_model							)


 def _lowercase	(     self		:						str							)					->       Union[str, Any]:
   _a  :       int             =	{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		:						Tuple							)					->       List[str]:
   _a  :       Tuple             =	self.__dict__.copy()
   _a  :       Tuple             =	None
   return state


 def __setstate__(     self		:						Any							,						UpperCAmelCase__		:						Dict							)					->       Dict:
   _a  :       Tuple             =	d

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

   _a  :       int             =	spm.SentencePieceProcessor(**self.sp_model_kwargs							)
   self.sp_model.Load(self.vocab_file							)


 def _lowercase	(     self		:						List[str]							,						UpperCAmelCase__		:						Union[str, Any]							)					->       Dict:
   if self.remove_space:
     _a  :       Optional[int]             =	""" """.join(inputs.strip().split()							)
   else:
     _a  :       List[Any]             =	inputs
   _a  :       int             =	outputs.replace("""``"""							,						"""\""""							).replace("""''"""							,						"""\""""							)

   if not self.keep_accents:
     _a  :       Optional[Any]             =	unicodedata.normalize("""NFKD"""							,						UpperCAmelCase__							)
     _a  :       Dict             =	"""""".join([c for c in outputs if not unicodedata.combining(UpperCAmelCase__							)]							)
   if self.do_lower_case:
     _a  :       Union[str, Any]             =	outputs.lower()

   return outputs


 def _lowercase	(     self		:						List[str]							,						UpperCAmelCase__		:						str							)					->       List[str]:
   _a  :       str             =	self.preprocess_text(UpperCAmelCase__							)
   _a  :       Dict             =	self.sp_model.encode(UpperCAmelCase__							,						out_type=UpperCAmelCase__							)
   _a  :       Union[str, Any]             =	[]
   for piece in pieces:
     if len(UpperCAmelCase__							) > 1 and piece[-1] == str(""","""							) and piece[-2].isdigit():
       _a  :       Dict             =	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  :       Dict             =	cur_pieces[1:]
         else:
           _a  :       Any             =	cur_pieces[0][1:]
       cur_pieces.append(piece[-1]							)
       new_pieces.extend(UpperCAmelCase__							)
     else:
       new_pieces.append(UpperCAmelCase__							)

   return new_pieces


 def _lowercase	(     self		:						Union[str, Any]							,						UpperCAmelCase__		:						int							)					->       int:
   return self.sp_model.PieceToId(UpperCAmelCase__							)


 def _lowercase	(     self		:						List[Any]							,						UpperCAmelCase__		:						Optional[Any]							)					->       Any:
   return self.sp_model.IdToPiece(UpperCAmelCase__							)


 def _lowercase	(     self		:						Any							,						UpperCAmelCase__		:						Any							)					->       Dict:
   _a  :       Dict             =	"""""".join(UpperCAmelCase__							).replace(UpperCAmelCase__							,						""" """							).strip()
   return out_string


 def _lowercase	(     self		:						Any							,						UpperCAmelCase__		:						List[int]							,						UpperCAmelCase__		:						Optional[List[int]] = None							)					->       List[int]:
   _a  :       Optional[Any]             =	[self.sep_token_id]
   _a  :       Dict             =	[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		:						Tuple							,						UpperCAmelCase__		:						List[int]							,						UpperCAmelCase__		:						Optional[List[int]] = None							,						UpperCAmelCase__		:						bool = False							)					->       List[int]:

   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		:						str							,						UpperCAmelCase__		:						List[int]							,						UpperCAmelCase__		:						Optional[List[int]] = None							)					->       List[int]:
   _a  :       Any             =	[self.sep_token_id]
   _a  :       Optional[Any]             =	[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		:						Optional[int]							,						UpperCAmelCase__		:						str							,						UpperCAmelCase__		:						Optional[str] = None							)					->       Tuple[str]:
   if not os.path.isdir(UpperCAmelCase__							):
     logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""							)
     return
   _a  :       Union[str, Any]             =	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  :       Optional[Any]             =	self.sp_model.serialized_model_proto()
       fi.write(UpperCAmelCase__							)

   return (out_vocab_file,)







 def _lowercase	(     self		:						Any							,						*UpperCAmelCase__		:						List[str]							,						**UpperCAmelCase__		:						List[str]							)					->       List[str]:
   _a  :       Tuple             =	super()._decode(*UpperCAmelCase__							,						**UpperCAmelCase__							)
   _a  :       Optional[Any]             =	text.replace(""" """							,						""""""							).replace("""\u2582"""							,						""" """							).replace("""\u2583"""							,						"""\n"""							)
   return text

