




'''simple docstring'''




from __future__ import annotations





def      a_							(      __snake_case							:			list[list[int]]   )							->						bool:



       """simple docstring"""
       lowerCamelCase_							=len(__snake_case   )
       # We need to create solution object to save path.
       lowerCamelCase_							=[[0 for _ in range(__snake_case   )] for _ in range(__snake_case   )]
       lowerCamelCase_							=run_maze(__snake_case   ,       0   ,       0   ,       __snake_case   )
       if solved:
              print('''\n'''.join(str(__snake_case   ) for row in solutions   )   )
       else:
              print('''No solution exists!'''   )
       return solved





def      a_							(      __snake_case							:			list[list[int]]   ,       __snake_case							:			int   ,       __snake_case							:			int   ,       __snake_case							:			list[list[int]]   )							->						bool:



       """simple docstring"""
       lowerCamelCase_							=len(__snake_case   )
       # Final check point.
       if i == j == (size - 1):
              lowerCamelCase_							=1
              return True

       lowerCamelCase_							=(not i < 0) and (not j < 0)  # Check lower bounds
       lowerCamelCase_							=(i < size) and (j < size)  # Check upper bounds

       if lower_flag and upper_flag:
              # check for already visited and block points.
              lowerCamelCase_							=(not solutions[i][j]) and (not maze[i][j])
              if block_flag:
                     # check visited
                     lowerCamelCase_							=1

                     # check for directions
                     if (
                         run_maze(__snake_case   ,       i + 1   ,       __snake_case   ,       __snake_case   )
                         or run_maze(__snake_case   ,       __snake_case   ,       j + 1   ,       __snake_case   )
                         or run_maze(__snake_case   ,       i - 1   ,       __snake_case   ,       __snake_case   )
                         or run_maze(__snake_case   ,       __snake_case   ,       j - 1   ,       __snake_case   )
                     ):
                            return True

                     lowerCamelCase_							=0
                     return False
       return False


if __name__ == "__main__":
     import doctest

     doctest.testmod()











from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__UpperCAmelCase       :   Optional[int]				       =							logging.get_logger(__name__)

__UpperCAmelCase       :   Optional[int]				       =							{
    "kssteven/ibert-roberta-base": "https://huggingface.co/kssteven/ibert-roberta-base/resolve/main/config.json",
    "kssteven/ibert-roberta-large": "https://huggingface.co/kssteven/ibert-roberta-large/resolve/main/config.json",
    "kssteven/ibert-roberta-large-mnli": (
        "https://huggingface.co/kssteven/ibert-roberta-large-mnli/resolve/main/config.json"
    ),
}







class     __snake_case       (							__lowerCamelCase			):





       '''simple docstring'''







       lowerCAmelCase__      		=     """ibert"""




       def __init__(  self :    Dict							,				A :    Union[str, Any]=30_522							,				A :    List[Any]=768							,				A :    List[Any]=12							,				A :    Optional[int]=12							,				A :    Optional[Any]=3_072							,				A :    int="gelu"							,				A :    str=0.1							,				A :    List[Any]=0.1							,				A :    Optional[Any]=512							,				A :    int=2							,				A :    Union[str, Any]=0.02							,				A :    List[str]=1E-12							,				A :    Optional[int]=1							,				A :    Optional[int]=0							,				A :    List[str]=2							,				A :    str="absolute"							,				A :    Any=False							,				A :    Optional[Any]="none"							,				**A :    Any							,				):
         super().__init__(pad_token_id=A							,				bos_token_id=A							,				eos_token_id=A							,				**A		)

         __snake_case:						List[Any]   =						vocab_size
         __snake_case:						Optional[Any]   =						hidden_size
         __snake_case:						List[str]   =						num_hidden_layers
         __snake_case:						Tuple   =						num_attention_heads
         __snake_case:						List[str]   =						hidden_act
         __snake_case:						Optional[Any]   =						intermediate_size
         __snake_case:						Tuple   =						hidden_dropout_prob
         __snake_case:						List[str]   =						attention_probs_dropout_prob
         __snake_case:						Any   =						max_position_embeddings
         __snake_case:						int   =						type_vocab_size
         __snake_case:						List[str]   =						initializer_range
         __snake_case:						List[Any]   =						layer_norm_eps
         __snake_case:						Optional[int]   =						position_embedding_type
         __snake_case:						str   =						quant_mode
         __snake_case:						Optional[int]   =						force_dequant







class     __snake_case       (							__lowerCamelCase			):





       '''simple docstring'''







       @property
       def 							UpperCAmelCase__ (  self :    Tuple		):
         if self.task == "multiple-choice":
           __snake_case:						List[Any]   =						{0: """batch""", 1: """choice""", 2: """sequence"""}
         else:
           __snake_case:						List[str]   =						{0: """batch""", 1: """sequence"""}
         return OrderedDict(
             [
                 ("""input_ids""", dynamic_axis),
                 ("""attention_mask""", dynamic_axis),
             ]		)






