






'''simple docstring'''





import collections
import os
from typing import List, Optional, Tuple

from transformers.utils import is_jieba_available, requires_backends


if is_jieba_available():
	import jieba

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


__A							:							Dict  							=		logging.get_logger(__name__)

__A							:							Union[str, Any]  							=		{"""vocab_file""": """vocab.txt"""}

__A							:							int  							=		{
    """vocab_file""": {
        """openbmb/cpm-ant-10b""": """https://huggingface.co/openbmb/cpm-ant-10b/blob/main/vocab.txt""",
    },
}

__A							:							Any  							=		{
    """openbmb/cpm-ant-10b""": 10_24,
}






def    lowerCamelCase_     (    lowercase__):
	lowerCamelCase__  =     collections.OrderedDict()
	with open(lowercase__				,     "r"				,     encoding="utf-8") as reader:
		lowerCamelCase__  =     reader.readlines()
	for index, token in enumerate(lowercase__):
		lowerCamelCase__  =     token.rstrip("\n")
		lowerCamelCase__  =     index
	return vocab
class 				lowercase       (							__a      ):


				'''simple docstring'''

				def __init__(					self     :     Any				,     __lowerCamelCase     :     str				,     __lowerCamelCase     :     Any="<unk>"				,     __lowerCamelCase     :     Dict=200     )							->							Any:

					'''simple docstring'''




					lowerCamelCase__  =     vocab
					lowerCamelCase__  =     unk_token
					lowerCamelCase__  =     max_input_chars_per_word




				def    a__				(					self     :     Tuple				,     __lowerCamelCase     :     str     )							->							str:

					'''simple docstring'''




					lowerCamelCase__  =     list(A__     )
					if len(A__     ) > self.max_input_chars_per_word:
						return [self.unk_token]

					lowerCamelCase__  =     0
					lowerCamelCase__  =     []
					while start < len(A__     ):
						lowerCamelCase__  =     len(A__     )
						lowerCamelCase__  =     None
						while start < end:
							lowerCamelCase__  =     "".join(chars[start:end]     )
							if substr in self.vocab:
								lowerCamelCase__  =     substr
								break
							end -= 1
						if cur_substr is None:
							sub_tokens.append(self.unk_token     )
							start += 1
						else:
							sub_tokens.append(A__     )
							lowerCamelCase__  =     end

					return sub_tokens
class 				lowercase       (							__a      ):


				'''simple docstring'''

				lowerCAmelCase__      				=							VOCAB_FILES_NAMES
				lowerCAmelCase__      				=							PRETRAINED_VOCAB_FILES_MAP
				lowerCAmelCase__      				=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				lowerCAmelCase__      				=							["input_ids", "attention_mask"]
				lowerCAmelCase__      				=							False

				def __init__(					self     :     Tuple				,     __lowerCamelCase     :     Any				,     __lowerCamelCase     :     Optional[Any]="<d>"				,     __lowerCamelCase     :     Any="</d>"				,     __lowerCamelCase     :     int="<s>"				,     __lowerCamelCase     :     Dict="</s>"				,     __lowerCamelCase     :     Optional[int]="<pad>"				,     __lowerCamelCase     :     Dict="<unk>"				,     __lowerCamelCase     :     Optional[int]="</n>"				,     __lowerCamelCase     :     Tuple="</_>"				,     __lowerCamelCase     :     List[Any]="left"				,     **__lowerCamelCase     :     Any				,     )							->							Dict:

					'''simple docstring'''




					requires_backends(self				,     ["jieba"]     )
					super().__init__(
					    bod_token=A__				,     eod_token=A__				,     bos_token=A__				,     eos_token=A__				,     pad_token=A__				,     unk_token=A__				,     line_token=A__				,     space_token=A__				,     padding_side=A__				,     **A__				,     )
					lowerCamelCase__  =     bod_token
					lowerCamelCase__  =     eod_token
					lowerCamelCase__  =     load_vocab(A__     )
					lowerCamelCase__  =     self.encoder[space_token]
					lowerCamelCase__  =     self.encoder[line_token]

					del self.encoder[space_token]
					del self.encoder[line_token]

					lowerCamelCase__  =     collections.OrderedDict(sorted(self.encoder.items()				,     key=lambda __lowerCamelCase     : x[1]     )     )
					lowerCamelCase__  =     {v: k for k, v in self.encoder.items()}

					lowerCamelCase__  =     WordpieceTokenizer(vocab=self.encoder				,     unk_token=self.unk_token     )

				@property
				def    a__				(					self     :     Tuple     )							->							Any:

					'''simple docstring'''




					return self.encoder[self.bod_token]

				@property
				def    a__				(					self     :     Optional[int]     )							->							int:

					'''simple docstring'''




					return self.encoder[self.eod_token]

				@property
				def    a__				(					self     :     List[Any]     )							->							List[str]:

					'''simple docstring'''




					return self.encoder["\n"]

				@property
				def    a__				(					self     :     List[Any]     )							->							int:

					'''simple docstring'''




					return len(self.encoder     )

				def    a__				(					self     :     Any     )							->							int:

					'''simple docstring'''




					return dict(self.encoder				,     **self.added_tokens_encoder     )

				def    a__				(					self     :     int				,     __lowerCamelCase     :     List[Any]     )							->							List[Any]:

					'''simple docstring'''




					lowerCamelCase__  =     []
					for x in jieba.cut(A__				,     cut_all=A__     ):
						output_tokens.extend(self.wordpiece_tokenizer.tokenize(A__     )     )
					return output_tokens

				def    a__				(					self     :     Any				,     __lowerCamelCase     :     Any				,     **__lowerCamelCase     :     Optional[Any]     )							->							Optional[Any]:

					'''simple docstring'''




					lowerCamelCase__  =     [i for i in token_ids if i >= 0]
					lowerCamelCase__  =     [
					    x for x in token_ids if x != self.pad_token_id and x != self.eos_token_id and x != self.bos_token_id
					]
					return super()._decode(A__				,     **A__     )

				def    a__				(					self     :     Optional[Any]				,     __lowerCamelCase     :     Union[str, Any]     )							->							Dict:

					'''simple docstring'''




					return token in self.encoder

				def    a__				(					self     :     Tuple				,     __lowerCamelCase     :     str     )							->							str:

					'''simple docstring'''




					return "".join(A__     )

				def    a__				(					self     :     Tuple				,     __lowerCamelCase     :     Union[str, Any]     )							->							int:

					'''simple docstring'''




					return self.encoder.get(A__				,     self.encoder.get(self.unk_token     )     )

				def    a__				(					self     :     Optional[Any]				,     __lowerCamelCase     :     Dict     )							->							int:

					'''simple docstring'''




					return self.decoder.get(A__				,     self.unk_token     )

				def    a__				(					self     :     Optional[int]				,     __lowerCamelCase     :     Optional[Any]				,     __lowerCamelCase     :     Union[str, Any] = None     )							->							Tuple[str]:

					'''simple docstring'''




					if os.path.isdir(A__     ):
						lowerCamelCase__  =     os.path.join(
						    A__				,     (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]     )
					else:
						lowerCamelCase__  =     (filename_prefix + "-" if filename_prefix else "") + save_directory
					lowerCamelCase__  =     0
					if " " in self.encoder:
						lowerCamelCase__  =     self.encoder[" "]
						del self.encoder[" "]
					if "\n" in self.encoder:
						lowerCamelCase__  =     self.encoder["\n"]
						del self.encoder["\n"]
					lowerCamelCase__  =     collections.OrderedDict(sorted(self.encoder.items()				,     key=lambda __lowerCamelCase     : x[1]     )     )
					with open(A__				,     "w"				,     encoding="utf-8"     ) as writer:
						for token, token_index in self.encoder.items():
							if index != token_index:
								logger.warning(
								    f'''Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive.'''
								    " Please check that the vocabulary is not corrupted!"     )
								lowerCamelCase__  =     token_index
							writer.write(token + "\n"     )
							index += 1
					return (vocab_file,)

				def    a__				(					self     :     Dict				,     __lowerCamelCase     :     Tuple				,     __lowerCamelCase     :     int = None     )							->							List[int]:

					'''simple docstring'''




					if token_ids_a is None:
						return [self.bos_token_id] + token_ids_a
					return [self.bos_token_id] + token_ids_a + [self.bos_token_id] + token_ids_a




				def    a__				(					self     :     Any				,     __lowerCamelCase     :     Dict				,     __lowerCamelCase     :     str = None				,     __lowerCamelCase     :     Tuple = False     )							->							List[int]:

					'''simple docstring'''




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

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









'''simple docstring'''





def    lowerCamelCase_     (    lowercase__				,     lowercase__				,     lowercase__):

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

  lowerCamelCase__  =     update_area_of_max_square(lowercase__				,     col + 1)
  lowerCamelCase__  =     update_area_of_max_square(row + 1				,     col + 1)
  lowerCamelCase__  =     update_area_of_max_square(row + 1				,     lowercase__)

  if mat[row][col]:
   lowerCamelCase__  =     1 + min([right, diagonal, down])
   lowerCamelCase__  =     max(largest_square_area[0]				,     lowercase__)
   return sub_problem_sol
  else:
   return 0

 lowerCamelCase__  =     [0]
 update_area_of_max_square(0				,     0)
 return largest_square_area[0]






def    lowerCamelCase_     (    lowercase__				,     lowercase__				,     lowercase__):

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

  lowerCamelCase__  =     update_area_of_max_square_using_dp_array(lowercase__				,     col + 1				,     lowercase__)
  lowerCamelCase__  =     update_area_of_max_square_using_dp_array(row + 1				,     col + 1				,     lowercase__)
  lowerCamelCase__  =     update_area_of_max_square_using_dp_array(row + 1				,     lowercase__				,     lowercase__)

  if mat[row][col]:
   lowerCamelCase__  =     1 + min([right, diagonal, down])
   lowerCamelCase__  =     max(largest_square_area[0]				,     lowercase__)
   lowerCamelCase__  =     sub_problem_sol
   return sub_problem_sol
  else:
   return 0

 lowerCamelCase__  =     [0]
 lowerCamelCase__  =     [[-1] * cols for _ in range(lowercase__)]
 update_area_of_max_square_using_dp_array(0				,     0				,     lowercase__)

 return largest_square_area[0]






def    lowerCamelCase_     (    lowercase__				,     lowercase__				,     lowercase__):
 lowerCamelCase__  =     [[0] * (cols + 1) for _ in range(rows + 1)]
 lowerCamelCase__  =     0
 for row in range(rows - 1				,     -1				,     -1):
  for col in range(cols - 1				,     -1				,     -1):
   lowerCamelCase__  =     dp_array[row][col + 1]
   lowerCamelCase__  =     dp_array[row + 1][col + 1]
   lowerCamelCase__  =     dp_array[row + 1][col]

   if mat[row][col] == 1:
    lowerCamelCase__  =     1 + min(lowercase__				,     lowercase__				,     lowercase__)
    lowerCamelCase__  =     max(dp_array[row][col]				,     lowercase__)
   else:
    lowerCamelCase__  =     0

 return largest_square_area






def    lowerCamelCase_     (    lowercase__				,     lowercase__				,     lowercase__):
 lowerCamelCase__  =     [0] * (cols + 1)
 lowerCamelCase__  =     [0] * (cols + 1)
 lowerCamelCase__  =     0
 for row in range(rows - 1				,     -1				,     -1):
  for col in range(cols - 1				,     -1				,     -1):
   lowerCamelCase__  =     current_row[col + 1]
   lowerCamelCase__  =     next_row[col + 1]
   lowerCamelCase__  =     next_row[col]

   if mat[row][col] == 1:
    lowerCamelCase__  =     1 + min(lowercase__				,     lowercase__				,     lowercase__)
    lowerCamelCase__  =     max(current_row[col]				,     lowercase__)
   else:
    lowerCamelCase__  =     0
  lowerCamelCase__  =     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]]))

