"""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


_A   					=    logging.get_logger(__name__)

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

_A   					=    {
    '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',
    }
}

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

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

class lowerCamelCase		(_SCREAMING_SNAKE_CASE      ):






					'''simple docstring'''


					a   	=		VOCAB_FILES_NAMES
					a   	=		PRETRAINED_VOCAB_FILES_MAP
					a   	=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					a   	=		"left"



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

									SCREAMING_SNAKE_CASE__		  =				{} 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   , )

									SCREAMING_SNAKE_CASE__		  =				3

									SCREAMING_SNAKE_CASE__		  =				do_lower_case
									SCREAMING_SNAKE_CASE__		  =				remove_space
									SCREAMING_SNAKE_CASE__		  =				keep_accents
									SCREAMING_SNAKE_CASE__		  =				vocab_file

									SCREAMING_SNAKE_CASE__		  =				spm.SentencePieceProcessor(**self.sp_model_kwargs		)
									self.sp_model.Load(_snake_case		)



					@property
					def 			lowerCAmelCase_					(						self			:				str		)							->       List[Any]:
									return len(self.sp_model		)



					def 			lowerCAmelCase_					(						self			:				Optional[Any]		)							->       Optional[Any]:
									SCREAMING_SNAKE_CASE__		  =				{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			:				Optional[Any]		)							->       Optional[int]:
									SCREAMING_SNAKE_CASE__		  =				self.__dict__.copy()
									SCREAMING_SNAKE_CASE__		  =				None
									return state



					def __setstate__(						self			:				Optional[Any]   , _snake_case			:				List[Any]		)							->       Optional[Any]:
									SCREAMING_SNAKE_CASE__		  =				d

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

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



					def 			lowerCAmelCase_					(						self			:				Optional[Any]   , _snake_case			:				Tuple		)							->       str:
									if self.remove_space:
													SCREAMING_SNAKE_CASE__		  =				" ".join(inputs.strip().split()		)
									else:
													SCREAMING_SNAKE_CASE__		  =				inputs
									SCREAMING_SNAKE_CASE__		  =				outputs.replace("``"   , "\""		).replace("''"   , "\""		)

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

									return outputs



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

									return new_pieces



					def 			lowerCAmelCase_					(						self			:				Dict   , _snake_case			:				List[str]		)							->       Any:
									return self.sp_model.PieceToId(_snake_case		)



					def 			lowerCAmelCase_					(						self			:				str   , _snake_case			:				str		)							->       Tuple:
									return self.sp_model.IdToPiece(_snake_case		)



					def 			lowerCAmelCase_					(						self			:				str   , _snake_case			:				Optional[int]		)							->       int:
									SCREAMING_SNAKE_CASE__		  =				"".join(_snake_case		).replace(_snake_case   , " "		).strip()
									return out_string



					def 			lowerCAmelCase_					(						self			:				Optional[int]   , _snake_case			:				List[int]   , _snake_case			:				bool = False   , _snake_case			:				bool = None   , _snake_case			:				bool = True   , **_snake_case			:				int   , )							->       str:
									SCREAMING_SNAKE_CASE__		  =				kwargs.pop("use_source_tokenizer"   , _snake_case		)

									SCREAMING_SNAKE_CASE__		  =				self.convert_ids_to_tokens(_snake_case   , skip_special_tokens=_snake_case		)

									# To avoid mixing byte-level and unicode for byte-level BPT
									# we need to build string separately for added tokens and byte-level tokens
									# cf. https://github.com/huggingface/transformers/issues/1133
									SCREAMING_SNAKE_CASE__		  =				[]
									SCREAMING_SNAKE_CASE__		  =				[]
									for token in filtered_tokens:
													if skip_special_tokens and token in self.all_special_ids:
																	continue
													if token in self.added_tokens_encoder:
																	if current_sub_text:
																					sub_texts.append(self.convert_tokens_to_string(_snake_case		)		)
																					SCREAMING_SNAKE_CASE__		  =				[]
																	sub_texts.append(_snake_case		)
													else:
																	current_sub_text.append(_snake_case		)
									if current_sub_text:
													sub_texts.append(self.convert_tokens_to_string(_snake_case		)		)

									# Mimic the behavior of the Rust tokenizer:
									# By default, there are no spaces between special tokens
									SCREAMING_SNAKE_CASE__		  =				"".join(_snake_case		)

									SCREAMING_SNAKE_CASE__		  =				(
									    clean_up_tokenization_spaces
									    if clean_up_tokenization_spaces is not None
									    else self.clean_up_tokenization_spaces
									)
									if clean_up_tokenization_spaces:
													SCREAMING_SNAKE_CASE__		  =				self.clean_up_tokenization(_snake_case		)
													return clean_text
									else:
													return text



					def 			lowerCAmelCase_					(						self			:				List[str]   , _snake_case			:				List[int]   , _snake_case			:				Optional[List[int]] = None		)							->       List[int]:
									SCREAMING_SNAKE_CASE__		  =				[self.sep_token_id]
									SCREAMING_SNAKE_CASE__		  =				[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 			lowerCAmelCase_					(						self			:				Optional[Any]   , _snake_case			:				List[int]   , _snake_case			:				Optional[List[int]] = None   , _snake_case			:				bool = 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 			lowerCAmelCase_					(						self			:				Dict   , _snake_case			:				List[int]   , _snake_case			:				Optional[List[int]] = None		)							->       List[int]:
									SCREAMING_SNAKE_CASE__		  =				[self.sep_token_id]
									SCREAMING_SNAKE_CASE__		  =				[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 			lowerCAmelCase_					(						self			:				str   , _snake_case			:				str   , _snake_case			:				Optional[str] = None		)							->       Tuple[str]:
									if not os.path.isdir(_snake_case		):
													logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""		)
													return
									SCREAMING_SNAKE_CASE__		  =				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:
																	SCREAMING_SNAKE_CASE__		  =				self.sp_model.serialized_model_proto()
																	fi.write(_snake_case		)

									return (out_vocab_file,)





"""simple docstring"""






import sys




def 						SCREAMING_SNAKE_CASE					(  __UpperCAmelCase       )							->   Any:
				SCREAMING_SNAKE_CASE__		  =				len(__UpperCAmelCase       )
				SCREAMING_SNAKE_CASE__		  =				[[0 for x in range(__UpperCAmelCase       )] for x in range(__UpperCAmelCase       )]
				SCREAMING_SNAKE_CASE__		  =				[[0 for x in range(__UpperCAmelCase       )] for x in range(__UpperCAmelCase       )]

				for chain_length in range(2  ,					__UpperCAmelCase       ):
								for a in range(1  ,					n - chain_length + 1       ):
												SCREAMING_SNAKE_CASE__		  =				a + chain_length - 1

												SCREAMING_SNAKE_CASE__		  =				sys.maxsize
												for c in range(__UpperCAmelCase  ,					__UpperCAmelCase       ):
																SCREAMING_SNAKE_CASE__		  =				(
																    matrix[a][c] + matrix[c + 1][b] + array[a - 1] * array[c] * array[b]
																)
																if cost < matrix[a][b]:
																				SCREAMING_SNAKE_CASE__		  =				cost
																				SCREAMING_SNAKE_CASE__		  =				c
				return matrix, sol




def 						SCREAMING_SNAKE_CASE					(  __UpperCAmelCase  ,					__UpperCAmelCase  ,					__UpperCAmelCase       )							->   Union[str, Any]:
				if i == j:
								print("A" + str(__UpperCAmelCase       )  ,					end=" "       )
				else:
								print("("  ,					end=" "       )
								print_optiomal_solution(__UpperCAmelCase  ,					__UpperCAmelCase  ,					optimal_solution[i][j]       )
								print_optiomal_solution(__UpperCAmelCase  ,					optimal_solution[i][j] + 1  ,					__UpperCAmelCase       )
								print(")"  ,					end=" "       )




def 						SCREAMING_SNAKE_CASE					(  )							->   Any:
				SCREAMING_SNAKE_CASE__		  =				[30, 35, 15, 5, 10, 20, 25]
				SCREAMING_SNAKE_CASE__		  =				len(__UpperCAmelCase       )
				# Size of matrix created from above array will be
				# 30*35 35*15 15*5 5*10 10*20 20*25
				SCREAMING_SNAKE_CASE__  ,       SCREAMING_SNAKE_CASE__		  =				matrix_chain_order(__UpperCAmelCase       )

				print("No. of Operation required: " + str(matrix[1][n - 1]       )       )
				print_optiomal_solution(__UpperCAmelCase  ,					1  ,					n - 1       )


if __name__ == "__main__":
						main()




