'''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: int          =   logging.get_logger(__name__)

__a: List[Any]          =   {"""vocab_file""": """spiece.model"""}

__a: Union[str, Any]          =   {
    """vocab_file""": {
        """TsinghuaAI/CPM-Generate""": """https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/spiece.model""",
    }
}



class 			UpperCAmelCase  (						a__					):





       '''simple docstring'''



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

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

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

        lowercase__				:    List[Any]  =					3

        lowercase__				:    Any  =					do_lower_case
        lowercase__				:    List[Any]  =					remove_space
        lowercase__				:    Tuple  =					keep_accents
        lowercase__				:    Optional[int]  =					vocab_file

        lowercase__				:    str  =					spm.SentencePieceProcessor(**self.sp_model_kwargs )
        self.sp_model.Load(__lowerCAmelCase )

        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.''' )
        lowercase__				:    Tuple  =					jieba
        lowercase__				:    Union[str, Any]  =					str.maketrans(''' \n'''	,   '''\u2582\u2583''' )

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

       def _lowerCAmelCase(						self )  ->  Any:
        lowercase__				:    List[Any]  =					{self.convert_ids_to_tokens(__lowerCAmelCase ): i for i in range(self.vocab_size )}
        vocab.update(self.added_tokens_encoder )
        return vocab

       def __getstate__(						self )  ->  Optional[int]:
        lowercase__				:    str  =					self.__dict__.copy()
        lowercase__				:    Union[str, Any]  =					None
        return state

       def __setstate__(						self	,   __lowerCAmelCase )  ->  List[Any]:
        lowercase__				:    List[str]  =					d

        # for backward compatibility
        if not hasattr(self	,   '''sp_model_kwargs''' ):
         lowercase__				:    List[Any]  =					{}

        lowercase__				:    Tuple  =					spm.SentencePieceProcessor(**self.sp_model_kwargs )
        self.sp_model.Load(self.vocab_file )

       def _lowerCAmelCase(						self	,   __lowerCAmelCase )  ->  Any:
        if self.remove_space:
         lowercase__				:    int  =					''' '''.join(inputs.strip().split() )
        else:
         lowercase__				:    Union[str, Any]  =					inputs
        lowercase__				:    Any  =					outputs.replace('''``'''	,   '''"''' ).replace('''\'\''''	,   '''"''' )

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

        return outputs

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

        return new_pieces

       def _lowerCAmelCase(						self	,   __lowerCAmelCase )  ->  str:
        return self.sp_model.PieceToId(__lowerCAmelCase )

       def _lowerCAmelCase(						self	,   __lowerCAmelCase )  ->  Optional[int]:
        return self.sp_model.IdToPiece(__lowerCAmelCase )

       def _lowerCAmelCase(						self	,   __lowerCAmelCase )  ->  List[str]:
        lowercase__				:    Any  =					''''''.join(__lowerCAmelCase ).replace(__lowerCAmelCase	,   ''' ''' ).strip()
        return out_string

       def _lowerCAmelCase(						self	,   __lowerCAmelCase	,   __lowerCAmelCase = None )  ->  List[int]:
        lowercase__				:    Dict  =					[self.sep_token_id]
        lowercase__				:    Any  =					[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	,   __lowerCAmelCase	,   __lowerCAmelCase = None	,   __lowerCAmelCase = False )  ->  List[int]:

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

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

       def _lowerCAmelCase(						self	,   __lowerCAmelCase	,   __lowerCAmelCase = None )  ->  List[int]:
        lowercase__				:    Optional[Any]  =					[self.sep_token_id]
        lowercase__				:    int  =					[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	,   __lowerCAmelCase	,   __lowerCAmelCase = None )  ->  Tuple[str]:
        if not os.path.isdir(__lowerCAmelCase ):
         logger.error(F"""Vocabulary path ({save_directory}) should be a directory""" )
         return
        lowercase__				:    int  =					os.path.join(
            __lowerCAmelCase	,   (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file'''] )

        if os.path.abspath(self.vocab_file ) != os.path.abspath(__lowerCAmelCase ) and os.path.isfile(self.vocab_file ):
         copyfile(self.vocab_file	,   __lowerCAmelCase )
        elif not os.path.isfile(self.vocab_file ):
         with open(__lowerCAmelCase	,   '''wb''' ) as fi:
          lowercase__				:    Optional[Any]  =					self.sp_model.serialized_model_proto()
          fi.write(__lowerCAmelCase )

        return (out_vocab_file,)


       def _lowerCAmelCase(						self	,   *__lowerCAmelCase	,   **__lowerCAmelCase )  ->  Dict:
        lowercase__				:    Dict  =					super()._decode(*__lowerCAmelCase	,   **__lowerCAmelCase )
        lowercase__				:    Union[str, Any]  =					text.replace(''' '''	,   '''''' ).replace('''\u2582'''	,   ''' ''' ).replace('''\u2583'''	,   '''\n''' )
        return text


'''simple docstring'''

import doctest
from collections import deque

import numpy as np



class 			UpperCAmelCase  :





       '''simple docstring'''



       def __init__(						self )  ->  None:
        lowercase__				:    str  =					[2, 1, 2, -1]
        lowercase__				:    str  =					[1, 2, 3, 4]


       def _lowerCAmelCase(						self )  ->  list[float]:
        lowercase__				:    Optional[Any]  =					len(self.first_signal )
        lowercase__				:    Union[str, Any]  =					len(self.second_signal )

        lowercase__				:    int  =					max(__lowerCAmelCase	,   __lowerCAmelCase )

        # create a zero matrix of max_length x max_length
        lowercase__				:    List[str]  =					[[0] * max_length for i in range(__lowerCAmelCase )]

        # fills the smaller signal with zeros to make both signals of same length
        if length_first_signal < length_second_signal:
         self.first_signal += [0] * (max_length - length_first_signal)
        elif length_first_signal > length_second_signal:
         self.second_signal += [0] * (max_length - length_second_signal)
        for i in range(__lowerCAmelCase ):
         lowercase__				:    int  =					deque(self.second_signal )
         rotated_signal.rotate(__lowerCAmelCase )
         for j, item in enumerate(__lowerCAmelCase ):
          matrix[i][j] += item

        # multiply the matrix with the first signal
        lowercase__				:    Optional[int]  =					np.matmul(np.transpose(__lowerCAmelCase )	,   np.transpose(self.first_signal ) )

        # rounding-off to two decimal places
        return [round(__lowerCAmelCase	,   2 ) for i in final_signal]


if __name__ == "__main__":
  doctest.testmod()

