
"""simple docstring"""





from __future__ import annotations

_a														=		list[list[int]]

# assigning initial values to the grid
_a														=		[
    [3, 0, 6, 5, 0, 8, 4, 0, 0],
    [5, 2, 0, 0, 0, 0, 0, 0, 0],
    [0, 8, 7, 0, 0, 0, 0, 3, 1],
    [0, 0, 3, 0, 1, 0, 0, 8, 0],
    [9, 0, 0, 8, 6, 3, 0, 0, 5],
    [0, 5, 0, 0, 9, 0, 6, 0, 0],
    [1, 3, 0, 0, 0, 0, 2, 5, 0],
    [0, 0, 0, 0, 0, 0, 0, 7, 4],
    [0, 0, 5, 2, 0, 6, 3, 0, 0],
]

# a grid with no solution
_a														=		[
    [5, 0, 6, 5, 0, 8, 4, 0, 3],
    [5, 2, 0, 0, 0, 0, 0, 0, 2],
    [1, 8, 7, 0, 0, 0, 0, 3, 1],
    [0, 0, 3, 0, 1, 0, 0, 8, 0],
    [9, 0, 0, 8, 6, 3, 0, 0, 5],
    [0, 5, 0, 0, 9, 0, 6, 0, 0],
    [1, 3, 0, 0, 0, 0, 2, 5, 0],
    [0, 0, 0, 0, 0, 0, 0, 7, 4],
    [0, 0, 5, 2, 0, 6, 3, 0, 0],
]



def 				lowerCamelCase__		(      __snake_case,					__snake_case,					__snake_case,					__snake_case     )							->		Any:


					"""simple docstring"""





					for i in range(9     ):
										if grid[row][i] == n or grid[i][column] == n:
															return False

					for i in range(3     ):
										for j in range(3     ):
															if grid[(row - row % 3) + i][(column - column % 3) + j] == n:
																				return False

					return True



def 				lowerCamelCase__		(      __snake_case     )							->		str:


					"""simple docstring"""





					for i in range(9     ):
										for j in range(9     ):
															if grid[i][j] == 0:
																				return i, j
					return None



def 				lowerCamelCase__		(      __snake_case     )							->		Any:


					"""simple docstring"""





					if location := find_empty_location(UpperCAmelCase_     ):
										_UpperCamelCase			,  _UpperCamelCase										=  location
					else:
										# If the location is ``None``, then the grid is solved.
										return grid

					for digit in range(1,					10     ):
										if is_safe(UpperCAmelCase_,					UpperCAmelCase_,					UpperCAmelCase_,					UpperCAmelCase_     ):
															_UpperCamelCase										=  digit

															if sudoku(UpperCAmelCase_     ) is not None:
																				return grid

															_UpperCamelCase										=  0

					return None



def 				lowerCamelCase__		(      __snake_case     )							->		Tuple:


					"""simple docstring"""





					for row in grid:
										for cell in row:
															print(UpperCAmelCase_,					end=''' '''     )
										print()


if __name__ == "__main__":
				# make a copy of grid so that you can compare with the unmodified grid
				for example_grid in (initial_grid, no_solution):
								print("""\nExample grid:\n""" + """=""" * 20)
								print_solution(example_grid)
								print("""\nExample grid solution:""")
								_a														=		sudoku(example_grid)
								if solution is not None:
												print_solution(solution)
								else:
												print("""Cannot find a solution.""")








"""simple docstring"""





from collections import OrderedDict
from typing import Mapping

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


_a														=		logging.get_logger(__name__)

_a														=		{
    """facebook/xlm-roberta-xl""": """https://huggingface.co/facebook/xlm-roberta-xl/resolve/main/config.json""",
    """facebook/xlm-roberta-xxl""": """https://huggingface.co/facebook/xlm-roberta-xxl/resolve/main/config.json""",
    # See all XLM-RoBERTa-XL models at https://huggingface.co/models?filter=xlm-roberta-xl
}






class    _UpperCAmelCase(   lowerCamelCase     ):
		lowercase__      =				'xlm-roberta-xl'



		def __init__( self    ,		__a=25_08_80    ,		__a=25_60    ,		__a=36    ,		__a=32    ,		__a=1_02_40    ,		__a="gelu"    ,		__a=0.1    ,		__a=0.1    ,		__a=5_14    ,		__a=1    ,		__a=0.02    ,		__a=1e-05    ,		__a=1    ,		__a=0    ,		__a=2    ,		__a="absolute"    ,		__a=True    ,		__a=None    ,		**__a    ,		)	->	Tuple:






							'''simple docstring'''
							super().__init__(pad_token_id=__a    ,		bos_token_id=__a    ,		eos_token_id=__a    ,		**__a)
							_UpperCamelCase										=  vocab_size
							_UpperCamelCase										=  hidden_size
							_UpperCamelCase										=  num_hidden_layers
							_UpperCamelCase										=  num_attention_heads
							_UpperCamelCase										=  hidden_act
							_UpperCamelCase										=  intermediate_size
							_UpperCamelCase										=  hidden_dropout_prob
							_UpperCamelCase										=  attention_probs_dropout_prob
							_UpperCamelCase										=  max_position_embeddings
							_UpperCamelCase										=  type_vocab_size
							_UpperCamelCase										=  initializer_range
							_UpperCamelCase										=  layer_norm_eps
							_UpperCamelCase										=  position_embedding_type
							_UpperCamelCase										=  use_cache
							_UpperCamelCase										=  classifier_dropout






class    _UpperCAmelCase(   lowerCamelCase     ):



		@property
		def 						UpperCAmelCase							( self)	->	Mapping[str, Mapping[int, str]]:






							'''simple docstring'''
							if self.task == "multiple-choice":
												_UpperCamelCase										=  {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
							else:
												_UpperCamelCase										=  {0: '''batch''', 1: '''sequence'''}
							return OrderedDict(
							    [
							        ('''input_ids''', dynamic_axis),
							        ('''attention_mask''', dynamic_axis),
							    ])






