"""simple docstring"""






from __future__ import annotations





class 					_A		:

      def __init__(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            lowercase								=      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(__lowerCAmelCase		) != 0:
                  lowercase								=      len(rows[0]		)
                  if cols == 0:
                        raise error
                  for row in rows:
                        if len(__lowerCAmelCase		) != cols:
                              raise error
                        for value in row:
                              if not isinstance(__lowerCAmelCase						,			(int, float)		):
                                    raise error
                  lowercase								=      rows
            else:
                  lowercase								=      []

      def 							A__			(		self		):







            """simple docstring"""



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

      @property
      def 							A__			(		self		):







            """simple docstring"""



            return len(self.rows		)

      @property
      def 							A__			(		self		):







            """simple docstring"""



            return len(self.rows[0]		)

      @property
      def 							A__			(		self		):







            """simple docstring"""



            return (self.num_rows, self.num_columns)

      @property
      def 							A__			(		self		):







            """simple docstring"""



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

      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      [
                [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(__lowerCAmelCase		)

      def 							A__			(		self		):







            """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 							A__			(		self		):







            """simple docstring"""



            return bool(self.determinant()		)

      def 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase		):







            """simple docstring"""



            lowercase								=      [
                [
                    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(__lowerCAmelCase		).determinant()

      def 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase		):







            """simple docstring"""



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

      def 							A__			(		self		):







            """simple docstring"""



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

      def 							A__			(		self		):







            """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 							A__			(		self		):







            """simple docstring"""



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

      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      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		):







            """simple docstring"""



            return str(self.rows		)

      def __str__(		self		):







            """simple docstring"""



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

      def 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase = None		):







            """simple docstring"""



            lowercase								=      TypeError("""Row must be a list containing all ints and/or floats"""		)
            if not isinstance(__lowerCAmelCase						,			__lowerCAmelCase		):
                  raise type_error
            for value in row:
                  if not isinstance(__lowerCAmelCase						,			(int, float)		):
                        raise type_error
            if len(__lowerCAmelCase		) != 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(__lowerCAmelCase		)
            else:
                  lowercase								=      self.rows[0:position] + [row] + self.rows[position:]

      def 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase = None		):







            """simple docstring"""



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

      def __eq__(		self						,			__lowerCAmelCase		):







            """simple docstring"""



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

      def __ne__(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            return not self == other

      def __neg__(		self		):







            """simple docstring"""



            return self * -1

      def __add__(		self						,			__lowerCAmelCase		):







            """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						,			__lowerCAmelCase		):







            """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						,			__lowerCAmelCase		):







            """simple docstring"""



            if isinstance(__lowerCAmelCase						,			(int, float)		):
                  return Matrix(
                      [[int(element * other		) for element in row] for row in self.rows]		)
            elif isinstance(__lowerCAmelCase						,			__lowerCAmelCase		):
                  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(__lowerCAmelCase						,			__lowerCAmelCase		) 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						,			__lowerCAmelCase		):







            """simple docstring"""



            if not isinstance(__lowerCAmelCase						,			__lowerCAmelCase		):
                  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"""		)
            lowercase								=      self
            for _ in range(other - 1		):
                  result *= self
            return result







      @classmethod
      def 							A__			(		cls						,			__lowerCAmelCase						,			__lowerCAmelCase		):







            """simple docstring"""



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


if __name__ == "__main__":
       import doctest

       doctest.testmod()




"""simple docstring"""






import os
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 logging


__lowerCAmelCase       :			List[str]   	=logging.get_logger(__name__)

__lowerCAmelCase       :			str   	={"""vocab_file""": """sentencepiece.bpe.model"""}

__lowerCAmelCase       :			Dict   	={
    """vocab_file""": {
        """moussaKam/mbarthez""": """https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model""",
        """moussaKam/barthez""": """https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model""",
        """moussaKam/barthez-orangesum-title""": (
            """https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model"""
        ),
    },
}

__lowerCAmelCase       :			Tuple   	={
    """moussaKam/mbarthez""": 1_0_2_4,
    """moussaKam/barthez""": 1_0_2_4,
    """moussaKam/barthez-orangesum-title""": 1_0_2_4,
}

__lowerCAmelCase       :			Optional[int]   	="""▁"""





class 					_A		(			lowerCAmelCase      ):
      snake_case__     :  Tuple				    =      VOCAB_FILES_NAMES
      snake_case__     :  Optional[Any]				    =      PRETRAINED_VOCAB_FILES_MAP
      snake_case__     :  Dict				    =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      snake_case__     :  Optional[Any]				    =      ['input_ids', 'attention_mask']

      def __init__(		self						,			__lowerCAmelCase						,			__lowerCAmelCase="<s>"						,			__lowerCAmelCase="</s>"						,			__lowerCAmelCase="</s>"						,			__lowerCAmelCase="<s>"						,			__lowerCAmelCase="<unk>"						,			__lowerCAmelCase="<pad>"						,			__lowerCAmelCase="<mask>"						,			__lowerCAmelCase = None						,			**__lowerCAmelCase						,			):







            """simple docstring"""



            lowercase								=      AddedToken(__lowerCAmelCase						,			lstrip=__lowerCAmelCase						,			rstrip=__lowerCAmelCase		) if isinstance(__lowerCAmelCase						,			__lowerCAmelCase		) else mask_token

            lowercase								=      {} if sp_model_kwargs is None else sp_model_kwargs

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

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

            lowercase								=      {"""<s>""": 0, """<pad>""": 1, """</s>""": 2, """<unk>""": 3}

            lowercase								=      len(self.sp_model		) - 1
            lowercase								=      {v: k for k, v in self.fairseq_tokens_to_ids.items()}

      def 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase = None		):







            """simple docstring"""



            if token_ids_a is None:
                  return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
            lowercase								=      [self.cls_token_id]
            lowercase								=      [self.sep_token_id]
            return cls + token_ids_a + sep + sep + token_ids_a + sep

      def 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase = None						,			__lowerCAmelCase = 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		)

            if token_ids_a is None:
                  return [1] + ([0] * len(__lowerCAmelCase		)) + [1]
            return [1] + ([0] * len(__lowerCAmelCase		)) + [1, 1] + ([0] * len(__lowerCAmelCase		)) + [1]

      def 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase = None		):







            """simple docstring"""



            lowercase								=      [self.sep_token_id]
            lowercase								=      [self.cls_token_id]

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

      @property
      def 							A__			(		self		):







            """simple docstring"""



            return len(self.sp_model		)

      def 							A__			(		self		):







            """simple docstring"""



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

      def 							A__			(		self						,			__lowerCAmelCase		):







            """simple docstring"""



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

      def 							A__			(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            if token in self.fairseq_tokens_to_ids:
                  return self.fairseq_tokens_to_ids[token]
            lowercase								=      self.sp_model.PieceToId(__lowerCAmelCase		)

            return spm_id if spm_id else self.unk_token_id

      def 							A__			(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            if index in self.fairseq_ids_to_tokens:
                  return self.fairseq_ids_to_tokens[index]
            return self.sp_model.IdToPiece(__lowerCAmelCase		)

      def 							A__			(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            lowercase								=      []
            lowercase								=      """"""
            lowercase								=      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
                        lowercase								=      True
                        lowercase								=      []
                  else:
                        current_sub_tokens.append(__lowerCAmelCase		)
                        lowercase								=      False
            out_string += self.sp_model.decode(__lowerCAmelCase		)
            return out_string.strip()

      def __getstate__(		self		):







            """simple docstring"""



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

      def __setstate__(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            lowercase								=      d

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

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







      def 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase = None		):







            """simple docstring"""



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

            return (out_vocab_file,)



