
"""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


SCREAMING_SNAKE_CASE_					     =	logging.get_logger(__name__)

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

SCREAMING_SNAKE_CASE_					     =	{
    '''vocab_file''': {
        '''TsinghuaAI/CPM-Generate''': '''https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/spiece.model''',
    }
}
class       lowerCAmelCase_		(				A__ ):



							'''simple docstring'''





							def __init__( self    ,				snake_case_    ,				snake_case_=False    ,				snake_case_=True    ,				snake_case_=False    ,				snake_case_="<s>"    ,				snake_case_="</s>"    ,				snake_case_="<unk>"    ,				snake_case_="<sep>"    ,				snake_case_="<pad>"    ,				snake_case_="<cls>"    ,				snake_case_="<mask>"    ,				snake_case_=["<eop>", "<eod>"]    ,				snake_case_ = None    ,				**snake_case_    ,				)       ->  None:
													__lowerCAmelCase     =  AddedToken(snake_case_    ,				lstrip=snake_case_    ,				rstrip=snake_case_				) if isinstance(snake_case_    ,				snake_case_				) else mask_token

													__lowerCAmelCase     =  {} if sp_model_kwargs is None else sp_model_kwargs

													super().__init__(
													    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_    ,				sp_model_kwargs=self.sp_model_kwargs    ,				**snake_case_    ,				)

													__lowerCAmelCase     =  3

													__lowerCAmelCase     =  do_lower_case
													__lowerCAmelCase     =  remove_space
													__lowerCAmelCase     =  keep_accents
													__lowerCAmelCase     =  vocab_file

													__lowerCAmelCase     =  spm.SentencePieceProcessor(**self.sp_model_kwargs				)
													self.sp_model.Load(snake_case_				)

													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."""				)
													__lowerCAmelCase     =  jieba
													__lowerCAmelCase     =  str.maketrans(""" \n"""    ,				"""\u2582\u2583"""				)




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




							def    A__						( self				)       ->  int:
													__lowerCAmelCase     =  {self.convert_ids_to_tokens(snake_case_				): i for i in range(self.vocab_size				)}
													vocab.update(self.added_tokens_encoder				)
													return vocab




							def __getstate__( self				)       ->  List[Any]:
													__lowerCAmelCase     =  self.__dict__.copy()
													__lowerCAmelCase     =  None
													return state




							def __setstate__( self    ,				snake_case_				)       ->  Dict:
													__lowerCAmelCase     =  d

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

													__lowerCAmelCase     =  spm.SentencePieceProcessor(**self.sp_model_kwargs				)
													self.sp_model.Load(self.vocab_file				)




							def    A__						( self    ,				snake_case_				)       ->  Dict:
													if self.remove_space:
																			__lowerCAmelCase     =  """ """.join(inputs.strip().split()				)
													else:
																			__lowerCAmelCase     =  inputs
													__lowerCAmelCase     =  outputs.replace("""``"""    ,				"""\""""				).replace("""''"""    ,				"""\""""				)

													if not self.keep_accents:
																			__lowerCAmelCase     =  unicodedata.normalize("""NFKD"""    ,				snake_case_				)
																			__lowerCAmelCase     =  """""".join([c for c in outputs if not unicodedata.combining(snake_case_				)]				)
													if self.do_lower_case:
																			__lowerCAmelCase     =  outputs.lower()

													return outputs




							def    A__						( self    ,				snake_case_				)       ->  List[str]:
													__lowerCAmelCase     =  self.preprocess_text(snake_case_				)
													__lowerCAmelCase     =  self.sp_model.encode(snake_case_    ,				out_type=snake_case_				)
													__lowerCAmelCase     =  []
													for piece in pieces:
																			if len(snake_case_				) > 1 and piece[-1] == str(""","""				) and piece[-2].isdigit():
																									__lowerCAmelCase     =  self.sp_model.EncodeAsPieces(piece[:-1].replace(snake_case_    ,				""""""				)				)
																									if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
																															if len(cur_pieces[0]				) == 1:
																																					__lowerCAmelCase     =  cur_pieces[1:]
																															else:
																																					__lowerCAmelCase     =  cur_pieces[0][1:]
																									cur_pieces.append(piece[-1]				)
																									new_pieces.extend(snake_case_				)
																			else:
																									new_pieces.append(snake_case_				)

													return new_pieces




							def    A__						( self    ,				snake_case_				)       ->  Tuple:
													return self.sp_model.PieceToId(snake_case_				)




							def    A__						( self    ,				snake_case_				)       ->  Optional[Any]:
													return self.sp_model.IdToPiece(snake_case_				)




							def    A__						( self    ,				snake_case_				)       ->  Dict:
													__lowerCAmelCase     =  """""".join(snake_case_				).replace(snake_case_    ,				""" """				).strip()
													return out_string




							def    A__						( self    ,				snake_case_    ,				snake_case_ = 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    A__						( self    ,				snake_case_    ,				snake_case_ = None    ,				snake_case_ = False				)       ->  List[int]:

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

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




							def    A__						( self    ,				snake_case_    ,				snake_case_ = 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    A__						( self    ,				snake_case_    ,				snake_case_ = None				)       ->  Tuple[str]:
													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_				) and os.path.isfile(self.vocab_file				):
																			copyfile(self.vocab_file    ,				snake_case_				)
													elif not os.path.isfile(self.vocab_file				):
																			with open(snake_case_    ,				"""wb"""				) as fi:
																									__lowerCAmelCase     =  self.sp_model.serialized_model_proto()
																									fi.write(snake_case_				)

													return (out_vocab_file,)




							def    A__						( self    ,				*snake_case_    ,				**snake_case_				)       ->  Any:
													__lowerCAmelCase     =  super()._decode(*snake_case_    ,				**snake_case_				)
													__lowerCAmelCase     =  text.replace(""" """    ,				""""""				).replace("""\u2582"""    ,				""" """				).replace("""\u2583"""    ,				"""\n"""				)
													return text


"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE_					     =	logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_					     =	{
    '''alibaba-damo/mgp-str-base''': '''https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json''',
}
class       lowerCAmelCase_		(				A__ ):



							'''simple docstring'''





							_snake_case						      =		'''mgp-str'''




							def __init__( self    ,				snake_case_=[32, 128]    ,				snake_case_=4    ,				snake_case_=3    ,				snake_case_=27    ,				snake_case_=38    ,				snake_case_=50_257    ,				snake_case_=30_522    ,				snake_case_=768    ,				snake_case_=12    ,				snake_case_=12    ,				snake_case_=4.0    ,				snake_case_=True    ,				snake_case_=False    ,				snake_case_=1e-5    ,				snake_case_=0.0    ,				snake_case_=0.0    ,				snake_case_=0.0    ,				snake_case_=False    ,				snake_case_=0.02    ,				**snake_case_    ,				)       ->  List[Any]:
													super().__init__(**snake_case_				)

													__lowerCAmelCase     =  image_size
													__lowerCAmelCase     =  patch_size
													__lowerCAmelCase     =  num_channels
													__lowerCAmelCase     =  max_token_length
													__lowerCAmelCase     =  num_character_labels
													__lowerCAmelCase     =  num_bpe_labels
													__lowerCAmelCase     =  num_wordpiece_labels
													__lowerCAmelCase     =  hidden_size
													__lowerCAmelCase     =  num_hidden_layers
													__lowerCAmelCase     =  num_attention_heads
													__lowerCAmelCase     =  mlp_ratio
													__lowerCAmelCase     =  distilled
													__lowerCAmelCase     =  layer_norm_eps
													__lowerCAmelCase     =  drop_rate
													__lowerCAmelCase     =  qkv_bias
													__lowerCAmelCase     =  attn_drop_rate
													__lowerCAmelCase     =  drop_path_rate
													__lowerCAmelCase     =  output_aa_attentions
													__lowerCAmelCase     =  initializer_range
