


import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer


if TYPE_CHECKING:
    from ...tokenization_utils_base import TextInput
from ...utils import logging


A      = logging.get_logger(__name__)

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

A      = {
    '''vocab_file''': {
        '''t5-small''': '''https://huggingface.co/t5-small/resolve/main/spiece.model''',
        '''t5-base''': '''https://huggingface.co/t5-base/resolve/main/spiece.model''',
        '''t5-large''': '''https://huggingface.co/t5-large/resolve/main/spiece.model''',
        '''t5-3b''': '''https://huggingface.co/t5-3b/resolve/main/spiece.model''',
        '''t5-11b''': '''https://huggingface.co/t5-11b/resolve/main/spiece.model''',
    }
}


# TODO(PVP) - this should be removed in Transformers v5
A      = {
    '''t5-small''': 512,
    '''t5-base''': 512,
    '''t5-large''': 512,
    '''t5-3b''': 512,
    '''t5-11b''': 512,
}

A      = '''▁'''


class     lowercase__  (					UpperCAmelCase__		):
  A__=  VOCAB_FILES_NAMES
  A__=  PRETRAINED_VOCAB_FILES_MAP
  A__=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  A__=  ['input_ids', 'attention_mask']






  def __init__(					self      :					Any		,						_lowercase      :					Optional[Any]		,						_lowercase      :					List[Any]="</s>"		,						_lowercase      :					Any="<unk>"		,						_lowercase      :					Dict="<pad>"		,						_lowercase      :					int=1_00		,						_lowercase      :					Optional[Any]=None		,						_lowercase      :					Optional[Dict[str, Any]] = None		,						_lowercase      :					Tuple=True		,						**_lowercase      :					Tuple		,						):




         """simple docstring"""







         if extra_ids > 0 and additional_special_tokens is None:
                UpperCAmelCase__										=     [F"""<extra_id_{i}>""" for i in range(__lowerCAmelCase )]
         elif extra_ids > 0 and additional_special_tokens is not None:
                # Check that we have the right number of extra_id special tokens
                UpperCAmelCase__										=     len(set(filter(lambda _lowercase : bool("extra_id" in str(__lowerCAmelCase ) )		,						__lowerCAmelCase ) ) )
                if extra_tokens != extra_ids:
                       raise ValueError(
                           F"""Both extra_ids ({extra_ids}) and additional_special_tokens ({additional_special_tokens}) are"""
                           " provided to T5Tokenizer. In this case the additional_special_tokens must include the extra_ids"
                           " tokens" )
         if legacy:
                logger.warning_once(
                    F"""You are using the legacy behaviour of the {self.__class__}. This means that tokens that come after special tokens will not be properly handled. We recommend you to"""
                    " read the related pull request available at https://github.com/huggingface/transformers/pull/24565" )

         UpperCAmelCase__										=     legacy
         UpperCAmelCase__										=     {} if sp_model_kwargs is None else sp_model_kwargs

         super().__init__(
             eos_token=__lowerCAmelCase		,						unk_token=__lowerCAmelCase		,						pad_token=__lowerCAmelCase		,						extra_ids=__lowerCAmelCase		,						additional_special_tokens=__lowerCAmelCase		,						sp_model_kwargs=self.sp_model_kwargs		,						legacy=__lowerCAmelCase		,						**__lowerCAmelCase		,						)

         UpperCAmelCase__										=     vocab_file
         UpperCAmelCase__										=     extra_ids

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






  @staticmethod
  def 			_UpperCAmelCase  (					_lowercase      :					str		,						_lowercase      :					List[str]		,						_lowercase      :					Optional[int] ):




         """simple docstring"""







         if pretrained_model_name_or_path in TaTokenizer.max_model_input_sizes:
                UpperCAmelCase__										=     TaTokenizer.max_model_input_sizes[pretrained_model_name_or_path]
                if init_max_model_length is not None and init_max_model_length != max_model_length:
                       return init_max_model_length
                elif init_max_model_length is None:
                       warnings.warn(
                           "This tokenizer was incorrectly instantiated with a model max length of"
                           F""" {deprecated_max_model_length} which will be corrected in Transformers v5.\nFor now, this"""
                           " behavior is kept to avoid breaking backwards compatibility when padding/encoding with"
                           " `truncation is True`.\n- Be aware that you SHOULD NOT rely on"
                           F""" {pretrained_model_name_or_path} automatically truncating your input to"""
                           F""" {deprecated_max_model_length} when padding/encoding.\n- If you want to encode/pad to sequences"""
                           F""" longer than {deprecated_max_model_length} you can either instantiate this tokenizer with"""
                           " `model_max_length` or pass `max_length` when encoding/padding.\n- To avoid this warning, please"
                           " instantiate this tokenizer with `model_max_length` set to your preferred value."		,						__lowerCAmelCase		,						)

         return max_model_length






  @property
  def 			_UpperCAmelCase  (					self      :					int ):




         """simple docstring"""







         return self.sp_model.get_piece_size() + self._extra_ids






  def 			_UpperCAmelCase  (					self      :					Optional[Any] ):




         """simple docstring"""







         UpperCAmelCase__										=     {self.convert_ids_to_tokens(__lowerCAmelCase ): i for i in range(self.vocab_size )}
         vocab.update(self.added_tokens_encoder )
         return vocab






  def 			_UpperCAmelCase  (					self      :					Tuple		,						_lowercase      :					List[int]		,						_lowercase      :					Optional[List[int]] = None		,						_lowercase      :					bool = False ):




         """simple docstring"""







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

         # normal case: some special tokens
         if token_ids_a is None:
                return ([0] * len(__lowerCAmelCase )) + [1]
         return ([0] * len(__lowerCAmelCase )) + [1] + ([0] * len(__lowerCAmelCase )) + [1]






  def 			_UpperCAmelCase  (					self      :					Dict ):




         """simple docstring"""







         return list(
             set(filter(lambda _lowercase : bool(re.search(r"<extra_id_\d+>"		,						__lowerCAmelCase ) ) is not None		,						self.additional_special_tokens ) ) )






  def 			_UpperCAmelCase  (					self      :					str ):




         """simple docstring"""







         return [self._convert_token_to_id(__lowerCAmelCase ) for token in self.get_sentinel_tokens()]






  def 			_UpperCAmelCase  (					self      :					Union[str, Any]		,						_lowercase      :					List[int] ):




         """simple docstring"""







         if len(__lowerCAmelCase ) > 0 and token_ids[-1] == self.eos_token_id:
                warnings.warn(
                    F"""This sequence already has {self.eos_token}. In future versions this behavior may lead to duplicated"""
                    " eos tokens being added." )
                return token_ids
         else:
                return token_ids + [self.eos_token_id]






  def 			_UpperCAmelCase  (					self      :					Dict		,						_lowercase      :					List[int]		,						_lowercase      :					Optional[List[int]] = None ):




         """simple docstring"""







         UpperCAmelCase__										=     [self.eos_token_id]

         if token_ids_a is None:
                return len(token_ids_a + eos ) * [0]
         return len(token_ids_a + eos + token_ids_a + eos ) * [0]






  def 			_UpperCAmelCase  (					self      :					List[str]		,						_lowercase      :					List[int]		,						_lowercase      :					Optional[List[int]] = None ):




         """simple docstring"""







         UpperCAmelCase__										=     self._add_eos_if_not_present(__lowerCAmelCase )
         if token_ids_a is None:
                return token_ids_a
         else:
                UpperCAmelCase__										=     self._add_eos_if_not_present(__lowerCAmelCase )
                return token_ids_a + token_ids_a






  def __getstate__(					self      :					List[Any] ):




         """simple docstring"""







         UpperCAmelCase__										=     self.__dict__.copy()
         UpperCAmelCase__										=     None
         return state






  def __setstate__(					self      :					str		,						_lowercase      :					List[Any] ):




         """simple docstring"""







         UpperCAmelCase__										=     d

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

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






  def 			_UpperCAmelCase  (					self      :					Any		,						_lowercase      :					"TextInput"		,						**_lowercase      :					Dict ):




         """simple docstring"""







         if not self.legacy:
                UpperCAmelCase__										=     SPIECE_UNDERLINE + text.replace(__lowerCAmelCase		,						" " )
         return super().tokenize(__lowerCAmelCase		,						**__lowerCAmelCase )






  def 			_UpperCAmelCase  (					self      :					List[Any]		,						_lowercase      :					Tuple		,						**_lowercase      :					Dict ):




         """simple docstring"""







         if not self.legacy:
                UpperCAmelCase__										=     text.startswith(__lowerCAmelCase )
                if is_first:
                       UpperCAmelCase__										=     text[1:]

         UpperCAmelCase__										=     self.sp_model.encode(__lowerCAmelCase		,						out_type=__lowerCAmelCase )

         if not self.legacy and not is_first and not text.startswith(" " ) and tokens[0].startswith(__lowerCAmelCase ):
                UpperCAmelCase__										=     ([tokens[0][1:]] if len(tokens[0] ) > 1 else []) + tokens[1:]
         return tokens






  def 			_UpperCAmelCase  (					self      :					List[str]		,						_lowercase      :					List[str] ):




         """simple docstring"""







         if token.startswith("<extra_id_" ):
                UpperCAmelCase__										=     re.match(r"<extra_id_(\d+)>"		,						__lowerCAmelCase )
                UpperCAmelCase__										=     int(match.group(1 ) )
                return self.vocab_size - num - 1
         return self.sp_model.piece_to_id(__lowerCAmelCase )






  def 			_UpperCAmelCase  (					self      :					List[Any]		,						_lowercase      :					Optional[Any] ):




         """simple docstring"""







         if index < self.sp_model.get_piece_size():
                UpperCAmelCase__										=     self.sp_model.IdToPiece(__lowerCAmelCase )
         else:
                UpperCAmelCase__										=     F"""<extra_id_{self.vocab_size - 1 - index}>"""
         return token






  def 			_UpperCAmelCase  (					self      :					Dict		,						_lowercase      :					str ):




         """simple docstring"""







         UpperCAmelCase__										=     []
         UpperCAmelCase__										=     ""
         UpperCAmelCase__										=     False
         for token in tokens:
                # make sure that special tokens are not decoded using sentencepiece model
                if token in self.all_special_tokens:
                       if not prev_is_special:
                              out_string += " "
                       out_string += self.sp_model.decode(__lowerCAmelCase ) + token
                       UpperCAmelCase__										=     True
                       UpperCAmelCase__										=     []
                else:
                       current_sub_tokens.append(__lowerCAmelCase )
                       UpperCAmelCase__										=     False
         out_string += self.sp_model.decode(__lowerCAmelCase )
         return out_string.strip()






  def 			_UpperCAmelCase  (					self      :					Dict		,						_lowercase      :					str		,						_lowercase      :					Optional[str] = None ):




         """simple docstring"""







         if not os.path.isdir(__lowerCAmelCase ):
                logger.error(F"""Vocabulary path ({save_directory}) should be a directory""" )
                return
         UpperCAmelCase__										=     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:
                       UpperCAmelCase__										=     self.sp_model.serialized_model_proto()
                       fi.write(__lowerCAmelCase )

         return (out_vocab_file,)









from __future__ import annotations


class     lowercase__  :






  def __init__(					self      :					int		,						_lowercase      :					list[list[int]] ):




         """simple docstring"""







         UpperCAmelCase__										=     TypeError(
             "Matrices must be formed from a list of zero or more lists containing at "
             "least one and the same number of values, each of which must be of type "
             "int or float." )
         if len(_lowercase ) != 0:
                UpperCAmelCase__										=     len(rows[0] )
                if cols == 0:
                       raise error
                for row in rows:
                       if len(_lowercase ) != cols:
                              raise error
                       for value in row:
                              if not isinstance(_lowercase		,						(int, float) ):
                                     raise error
                UpperCAmelCase__										=     rows
         else:
                UpperCAmelCase__										=     []






  def 			_UpperCAmelCase  (					self      :					Dict ):




         """simple docstring"""







         return [[row[i] for row in self.rows] for i in range(len(self.rows[0] ) )]






  @property
  def 			_UpperCAmelCase  (					self      :					str ):




         """simple docstring"""







         return len(self.rows )






  @property
  def 			_UpperCAmelCase  (					self      :					Optional[Any] ):




         """simple docstring"""







         return len(self.rows[0] )






  @property
  def 			_UpperCAmelCase  (					self      :					Optional[Any] ):




         """simple docstring"""







         return (self.num_rows, self.num_columns)






  @property
  def 			_UpperCAmelCase  (					self      :					Tuple ):




         """simple docstring"""







         return self.order[0] == self.order[1]






  def 			_UpperCAmelCase  (					self      :					Optional[Any] ):




         """simple docstring"""







         UpperCAmelCase__										=     [
             [0 if column_num != row_num else 1 for column_num in range(self.num_rows )]
             for row_num in range(self.num_rows )
         ]
         return Matrix(_lowercase )






  def 			_UpperCAmelCase  (					self      :					Tuple ):




         """simple docstring"""







         if not self.is_square:
                return 0
         if self.order == (0, 0):
                return 1
         if self.order == (1, 1):
                return int(self.rows[0][0] )
         if self.order == (2, 2):
                return int(
                    (self.rows[0][0] * self.rows[1][1])
                    - (self.rows[0][1] * self.rows[1][0]) )
         else:
                return sum(
                    self.rows[0][column] * self.cofactors().rows[0][column]
                    for column in range(self.num_columns ) )






  def 			_UpperCAmelCase  (					self      :					Any ):




         """simple docstring"""







         return bool(self.determinant() )






  def 			_UpperCAmelCase  (					self      :					Optional[Any]		,						_lowercase      :					int		,						_lowercase      :					int ):




         """simple docstring"""







         UpperCAmelCase__										=     [
             [
                 self.rows[other_row][other_column]
                 for other_column in range(self.num_columns )
                 if other_column != column
             ]
             for other_row in range(self.num_rows )
             if other_row != row
         ]
         return Matrix(_lowercase ).determinant()






  def 			_UpperCAmelCase  (					self      :					str		,						_lowercase      :					int		,						_lowercase      :					int ):




         """simple docstring"""







         if (row + column) % 2 == 0:
                return self.get_minor(_lowercase		,						_lowercase )
         return -1 * self.get_minor(_lowercase		,						_lowercase )






  def 			_UpperCAmelCase  (					self      :					Optional[Any] ):




         """simple docstring"""







         return Matrix(
             [
                 [self.get_minor(_lowercase		,						_lowercase ) for column in range(self.num_columns )]
                 for row in range(self.num_rows )
             ] )






  def 			_UpperCAmelCase  (					self      :					List[str] ):




         """simple docstring"""







         return Matrix(
             [
                 [
                     self.minors().rows[row][column]
                     if (row + column) % 2 == 0
                     else self.minors().rows[row][column] * -1
                     for column in range(self.minors().num_columns )
                 ]
                 for row in range(self.minors().num_rows )
             ] )






  def 			_UpperCAmelCase  (					self      :					str ):




         """simple docstring"""







         UpperCAmelCase__										=     [
             [self.cofactors().rows[column][row] for column in range(self.num_columns )]
             for row in range(self.num_rows )
         ]
         return Matrix(_lowercase )






  def 			_UpperCAmelCase  (					self      :					List[str] ):




         """simple docstring"""







         UpperCAmelCase__										=     self.determinant()
         if not determinant:
                raise TypeError("Only matrices with a non-zero determinant have an inverse" )
         return self.adjugate() * (1 / determinant)






  def __repr__(					self      :					Dict ):




         """simple docstring"""







         return str(self.rows )






  def __str__(					self      :					Tuple ):




         """simple docstring"""







         if self.num_rows == 0:
                return "[]"
         if self.num_rows == 1:
                return "[[" + ". ".join(str(self.rows[0] ) ) + "]]"
         return (
             "["
             + "\n ".join(
                 [
                     "[" + ". ".join([str(_lowercase ) for value in row] ) + ".]"
                     for row in self.rows
                 ] )
             + "]"
         )






  def 			_UpperCAmelCase  (					self      :					Any		,						_lowercase      :					list[int]		,						_lowercase      :					int | None = None ):




         """simple docstring"""







         UpperCAmelCase__										=     TypeError("Row must be a list containing all ints and/or floats" )
         if not isinstance(_lowercase		,						_lowercase ):
                raise type_error
         for value in row:
                if not isinstance(_lowercase		,						(int, float) ):
                       raise type_error
         if len(_lowercase ) != self.num_columns:
                raise ValueError(
                    "Row must be equal in length to the other rows in the matrix" )
         if position is None:
                self.rows.append(_lowercase )
         else:
                UpperCAmelCase__										=     self.rows[0:position] + [row] + self.rows[position:]






  def 			_UpperCAmelCase  (					self      :					Optional[Any]		,						_lowercase      :					list[int]		,						_lowercase      :					int | None = None ):




         """simple docstring"""







         UpperCAmelCase__										=     TypeError(
             "Column must be a list containing all ints and/or floats" )
         if not isinstance(_lowercase		,						_lowercase ):
                raise type_error
         for value in column:
                if not isinstance(_lowercase		,						(int, float) ):
                       raise type_error
         if len(_lowercase ) != self.num_rows:
                raise ValueError(
                    "Column must be equal in length to the other columns in the matrix" )
         if position is None:
                UpperCAmelCase__										=     [self.rows[i] + [column[i]] for i in range(self.num_rows )]
         else:
                UpperCAmelCase__										=     [
                    self.rows[i][0:position] + [column[i]] + self.rows[i][position:]
                    for i in range(self.num_rows )
                ]






  def __eq__(					self      :					Dict		,						_lowercase      :					object ):




         """simple docstring"""







         if not isinstance(_lowercase		,						_lowercase ):
                return NotImplemented
         return self.rows == other.rows






  def __ne__(					self      :					List[Any]		,						_lowercase      :					object ):




         """simple docstring"""







         return not self == other






  def __neg__(					self      :					int ):




         """simple docstring"""







         return self * -1






  def __add__(					self      :					List[Any]		,						_lowercase      :					Matrix ):




         """simple docstring"""







         if self.order != other.order:
                raise ValueError("Addition requires matrices of the same order" )
         return Matrix(
             [
                 [self.rows[i][j] + other.rows[i][j] for j in range(self.num_columns )]
                 for i in range(self.num_rows )
             ] )






  def __sub__(					self      :					Optional[int]		,						_lowercase      :					Matrix ):




         """simple docstring"""







         if self.order != other.order:
                raise ValueError("Subtraction requires matrices of the same order" )
         return Matrix(
             [
                 [self.rows[i][j] - other.rows[i][j] for j in range(self.num_columns )]
                 for i in range(self.num_rows )
             ] )






  def __mul__(					self      :					int		,						_lowercase      :					Matrix | int | float ):




         """simple docstring"""







         if isinstance(_lowercase		,						(int, float) ):
                return Matrix(
                    [[int(element * other ) for element in row] for row in self.rows] )
         elif isinstance(_lowercase		,						_lowercase ):
                if self.num_columns != other.num_rows:
                       raise ValueError(
                           "The number of columns in the first matrix must "
                           "be equal to the number of rows in the second" )
                return Matrix(
                    [
                        [Matrix.dot_product(_lowercase		,						_lowercase ) for column in other.columns()]
                        for row in self.rows
                    ] )
         else:
                raise TypeError(
                    "A Matrix can only be multiplied by an int, float, or another matrix" )






  def __pow__(					self      :					Optional[Any]		,						_lowercase      :					int ):




         """simple docstring"""







         if not isinstance(_lowercase		,						_lowercase ):
                raise TypeError("A Matrix can only be raised to the power of an int" )
         if not self.is_square:
                raise ValueError("Only square matrices can be raised to a power" )
         if other == 0:
                return self.identity()
         if other < 0:
                if self.is_invertable():
                       return self.inverse() ** (-other)
                raise ValueError(
                    "Only invertable matrices can be raised to a negative power" )
         UpperCAmelCase__										=     self
         for _ in range(other - 1 ):
                result *= self
         return result






  @classmethod
  def 			_UpperCAmelCase  (					cls      :					List[Any]		,						_lowercase      :					list[int]		,						_lowercase      :					list[int] ):




         """simple docstring"""







         return sum(row[i] * column[i] for i in range(len(_lowercase ) ) )


if __name__ == "__main__":
    import doctest

    doctest.testmod()





