






'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
 from .tokenization_rembert import RemBertTokenizer
else:
 UpperCamelCase__ =			None

UpperCamelCase__ =			logging.get_logger(__name__)
UpperCamelCase__ =			{'vocab_file': 'sentencepiece.model', 'tokenizer_file': 'tokenizer.json'}

UpperCamelCase__ =			{
    'vocab_file': {
        'google/rembert': 'https://huggingface.co/google/rembert/resolve/main/sentencepiece.model',
    },
    'tokenizer_file': {
        'google/rembert': 'https://huggingface.co/google/rembert/resolve/main/tokenizer.json',
    },
}

UpperCamelCase__ =			{
    'google/rembert': 256,
}

UpperCamelCase__ =			'▁'


class        _UpperCAmelCase						(		snake_case			):
    __lowerCamelCase:   Dict		       =    VOCAB_FILES_NAMES
    __lowerCamelCase:   Dict		       =    PRETRAINED_VOCAB_FILES_MAP
    __lowerCamelCase:   List[Any]		       =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    __lowerCamelCase:   int		       =    RemBertTokenizer




    def __init__(			self  :       Dict  ,     a  :       List[str]=None  ,     a  :       Optional[int]=None  ,     a  :       List[Any]=True  ,     a  :       List[str]=True  ,     a  :       Tuple=False  ,     a  :       Optional[int]="[CLS]"  ,     a  :       List[str]="[SEP]"  ,     a  :       Dict="<unk>"  ,     a  :       Tuple="[SEP]"  ,     a  :       Optional[int]="<pad>"  ,     a  :       Optional[int]="[CLS]"  ,     a  :       str="[MASK]"  ,     **a  :       Union[str, Any]  ,     ):






       '''simple docstring'''






       lowercase_	:    Any           =     AddedToken(a  ,     lstrip=a  ,     rstrip=a			) if isinstance(a  ,     a			) else mask_token

       super().__init__(
           a  ,     tokenizer_file=a  ,     do_lower_case=a  ,     remove_space=a  ,     keep_accents=a  ,     bos_token=a  ,     eos_token=a  ,     unk_token=a  ,     sep_token=a  ,     pad_token=a  ,     cls_token=a  ,     mask_token=a  ,     **a  ,     )

       lowercase_	:    List[str]           =     do_lower_case
       lowercase_	:    Union[str, Any]           =     remove_space
       lowercase_	:    Union[str, Any]           =     keep_accents
       lowercase_	:    Optional[Any]           =     vocab_file
       lowercase_	:    str           =     False if not self.vocab_file else True




    def 				lowerCAmelCase__				(			self  :       str  ,     a  :       List[int]  ,     a  :       Optional[List[int]] = None			):






       '''simple docstring'''






       lowercase_	:    Optional[int]           =     [self.sep_token_id]
       lowercase_	:    List[Any]           =     [self.cls_token_id]
       if token_ids_a is None:
          return cls + token_ids_a + sep
       return cls + token_ids_a + sep + token_ids_a + sep




    def 				lowerCAmelCase__				(			self  :       Union[str, Any]  ,     a  :       List[int]  ,     a  :       Optional[List[int]] = None  ,     a  :       bool = False			):






       '''simple docstring'''






       if already_has_special_tokens:
          if token_ids_a is not None:
             raise ValueError(
                 "You should not supply a second sequence if the provided sequence of "
                 "ids is already formatted with special tokens for the model."			)
          return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

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




    def 				lowerCAmelCase__				(			self  :       Dict  ,     a  :       List[int]  ,     a  :       Optional[List[int]] = None			):






       '''simple docstring'''






       lowercase_	:    List[Any]           =     [self.sep_token_id]
       lowercase_	:    Tuple           =     [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			) * [0] + len(token_ids_a + sep			) * [1]





    def 				lowerCAmelCase__				(			self  :       Tuple  ,     a  :       str  ,     a  :       Optional[str] = None			):






       '''simple docstring'''






       if not os.path.isdir(a			):
          logger.error("Vocabulary path ({}) should be a directory".format(a			)			)
          return
       lowercase_	:    Optional[int]           =     os.path.join(
           a  ,     (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]			)

       if os.path.abspath(self.vocab_file			) != os.path.abspath(a			):
          copyfile(self.vocab_file  ,     a			)

       return (out_vocab_file,)







'''simple docstring'''
def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase						,		_UpperCamelCase						,		_UpperCamelCase							):


   """simple docstring"""




   def update_area_of_max_square(_UpperCamelCase						,		_UpperCamelCase							) -> int:
      # BASE CASE
      if row >= rows or col >= cols:
         return 0

      lowercase_	:    List[str]           =     update_area_of_max_square(_UpperCamelCase						,		col + 1							)
      lowercase_	:    List[Any]           =     update_area_of_max_square(row + 1						,		col + 1							)
      lowercase_	:    Tuple           =     update_area_of_max_square(row + 1						,		_UpperCamelCase							)

      if mat[row][col]:
         lowercase_	:    Optional[int]           =     1 + min([right, diagonal, down]							)
         lowercase_	:    Any           =     max(largest_square_area[0]						,		_UpperCamelCase							)
         return sub_problem_sol
      else:
         return 0

   lowercase_	:    int           =     [0]
   update_area_of_max_square(0						,		0							)
   return largest_square_area[0]




def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase						,		_UpperCamelCase						,		_UpperCamelCase							):


   """simple docstring"""




   def update_area_of_max_square_using_dp_array(
       _UpperCamelCase						,		_UpperCamelCase						,		_UpperCamelCase							) -> int:
      if row >= rows or col >= cols:
         return 0
      if dp_array[row][col] != -1:
         return dp_array[row][col]

      lowercase_	:    Dict           =     update_area_of_max_square_using_dp_array(_UpperCamelCase						,		col + 1						,		_UpperCamelCase							)
      lowercase_	:    str           =     update_area_of_max_square_using_dp_array(row + 1						,		col + 1						,		_UpperCamelCase							)
      lowercase_	:    Optional[Any]           =     update_area_of_max_square_using_dp_array(row + 1						,		_UpperCamelCase						,		_UpperCamelCase							)

      if mat[row][col]:
         lowercase_	:    Tuple           =     1 + min([right, diagonal, down]							)
         lowercase_	:    int           =     max(largest_square_area[0]						,		_UpperCamelCase							)
         lowercase_	:    Dict           =     sub_problem_sol
         return sub_problem_sol
      else:
         return 0

   lowercase_	:    Any           =     [0]
   lowercase_	:    Optional[int]           =     [[-1] * cols for _ in range(_UpperCamelCase							)]
   update_area_of_max_square_using_dp_array(0						,		0						,		_UpperCamelCase							)

   return largest_square_area[0]




def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase						,		_UpperCamelCase						,		_UpperCamelCase							):


   """simple docstring"""




   lowercase_	:    str           =     [[0] * (cols + 1) for _ in range(rows + 1							)]
   lowercase_	:    List[Any]           =     0
   for row in range(rows - 1						,		-1						,		-1							):
      for col in range(cols - 1						,		-1						,		-1							):
         lowercase_	:    Tuple           =     dp_array[row][col + 1]
         lowercase_	:    List[str]           =     dp_array[row + 1][col + 1]
         lowercase_	:    List[Any]           =     dp_array[row + 1][col]

         if mat[row][col] == 1:
            lowercase_	:    Any           =     1 + min(_UpperCamelCase						,		_UpperCamelCase						,		_UpperCamelCase							)
            lowercase_	:    Any           =     max(dp_array[row][col]						,		_UpperCamelCase							)
         else:
            lowercase_	:    int           =     0

   return largest_square_area




def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase						,		_UpperCamelCase						,		_UpperCamelCase							):


   """simple docstring"""




   lowercase_	:    Optional[int]           =     [0] * (cols + 1)
   lowercase_	:    Union[str, Any]           =     [0] * (cols + 1)
   lowercase_	:    int           =     0
   for row in range(rows - 1						,		-1						,		-1							):
      for col in range(cols - 1						,		-1						,		-1							):
         lowercase_	:    Dict           =     current_row[col + 1]
         lowercase_	:    List[Any]           =     next_row[col + 1]
         lowercase_	:    Tuple           =     next_row[col]

         if mat[row][col] == 1:
            lowercase_	:    Dict           =     1 + min(_UpperCamelCase						,		_UpperCamelCase						,		_UpperCamelCase							)
            lowercase_	:    int           =     max(current_row[col]						,		_UpperCamelCase							)
         else:
            lowercase_	:    Tuple           =     0
      lowercase_	:    Optional[Any]           =     current_row

   return largest_square_area


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 print(largest_square_area_in_matrix_bottom_up(2, 2, [[1, 1], [1, 1]]))




