



'''simple docstring'''

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


snake_case_			=     logging.get_logger(__name__)

snake_case_			=     {
    """google/bit-50""": """https://huggingface.co/google/bit-50/resolve/main/config.json""",
}


class 		a__     (				_lowercase,			_lowercase	):
	__magic_name__		:    int	    =     "bit"
	__magic_name__		:    List[Any]	    =     ["preactivation", "bottleneck"]
	__magic_name__		:    int	    =     ["SAME", "VALID"]


	def __init__(self : Union[str, Any],					__UpperCAmelCase : Tuple=3,					__UpperCAmelCase : Optional[int]=64,					__UpperCAmelCase : Union[str, Any]=[256, 512, 1024, 2048],					__UpperCAmelCase : int=[3, 4, 6, 3],					__UpperCAmelCase : Any="preactivation",					__UpperCAmelCase : List[Any]="relu",					__UpperCAmelCase : Optional[Any]=None,					__UpperCAmelCase : int=32,					__UpperCAmelCase : int=0.0,					__UpperCAmelCase : Union[str, Any]=False,					__UpperCAmelCase : int=32,					__UpperCAmelCase : List[Any]=1,					__UpperCAmelCase : str=None,					__UpperCAmelCase : str=None,					**__UpperCAmelCase : Optional[Any],					)     ->			str:

					"""simple docstring"""

					super().__init__(**__UpperCAmelCase      )
					if layer_type not in self.layer_types:
									raise ValueError(F'''layer_type={layer_type} is not one of {",".join(self.layer_types      )}'''      )
					if global_padding is not None:
									if global_padding.upper() in self.supported_padding:
													SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= global_padding.upper()
									else:
													raise ValueError(F'''Padding strategy {global_padding} not supported'''      )
					SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= num_channels
					SCREAMING_SNAKE_CASE  :						Any      					= embedding_size
					SCREAMING_SNAKE_CASE  :						int      					= hidden_sizes
					SCREAMING_SNAKE_CASE  :						Dict      					= depths
					SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= layer_type
					SCREAMING_SNAKE_CASE  :						Optional[Any]      					= hidden_act
					SCREAMING_SNAKE_CASE  :						int      					= global_padding
					SCREAMING_SNAKE_CASE  :						Tuple      					= num_groups
					SCREAMING_SNAKE_CASE  :						int      					= drop_path_rate
					SCREAMING_SNAKE_CASE  :						Any      					= embedding_dynamic_padding
					SCREAMING_SNAKE_CASE  :						Any      					= output_stride
					SCREAMING_SNAKE_CASE  :						str      					= width_factor

					SCREAMING_SNAKE_CASE  :						List[str]      					= ['''stem'''] + [F'''stage{idx}''' for idx in range(1,					len(__UpperCAmelCase      ) + 1      )]
					SCREAMING_SNAKE_CASE  :						Any      					= get_aligned_output_features_output_indices(
					    out_features=__UpperCAmelCase,					out_indices=__UpperCAmelCase,					stage_names=self.stage_names      )









'''simple docstring'''

from __future__ import annotations

snake_case_			=     [
    [-1, 0],  # left
    [0, -1],  # down
    [1, 0],  # right
    [0, 1],  # up
]






def       __lowercase  (_SCREAMING_SNAKE_CASE      :list[list[int]]    ,	_SCREAMING_SNAKE_CASE      :list[int]    ,	_SCREAMING_SNAKE_CASE      :list[int]    ,	_SCREAMING_SNAKE_CASE      :int    ,	_SCREAMING_SNAKE_CASE      :list[list[int]]    ,	):
				SCREAMING_SNAKE_CASE  :						Optional[Any]      					= [
				    [0 for col in range(len(grid[0]       )       )] for row in range(len(_SCREAMING_SNAKE_CASE       )       )
				]  # the reference grid
				SCREAMING_SNAKE_CASE  :						Dict      					= 1
				SCREAMING_SNAKE_CASE  :						Optional[Any]      					= [
				    [0 for col in range(len(grid[0]       )       )] for row in range(len(_SCREAMING_SNAKE_CASE       )       )
				]  # the action grid

				SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= init[0]
				SCREAMING_SNAKE_CASE  :						Optional[Any]      					= init[1]
				SCREAMING_SNAKE_CASE  :						Any      					= 0
				SCREAMING_SNAKE_CASE  :						List[Any]      					= g + heuristic[x][y]  # cost from starting cell to destination cell
				SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= [[f, g, x, y]]

				SCREAMING_SNAKE_CASE  :						List[str]      					= False  # flag that is set when search is complete
				SCREAMING_SNAKE_CASE  :						Any      					= False  # flag set if we can't find expand

				while not found and not resign:
								if len(_SCREAMING_SNAKE_CASE       ) == 0:
												raise ValueError('''Algorithm is unable to find solution'''       )
								else:  # to choose the least costliest action so as to move closer to the goal
												cell.sort()
												cell.reverse()
												SCREAMING_SNAKE_CASE  :						List[str]      					= cell.pop()
												SCREAMING_SNAKE_CASE  :						List[str]      					= next_cell[2]
												SCREAMING_SNAKE_CASE  :						Dict      					= next_cell[3]
												SCREAMING_SNAKE_CASE  :						str      					= next_cell[1]

												if x == goal[0] and y == goal[1]:
																SCREAMING_SNAKE_CASE  :						Dict      					= True
												else:
																for i in range(len(_SCREAMING_SNAKE_CASE       )       ):  # to try out different valid actions
																				SCREAMING_SNAKE_CASE  :						Optional[Any]      					= x + DIRECTIONS[i][0]
																				SCREAMING_SNAKE_CASE  :						Tuple      					= y + DIRECTIONS[i][1]
																				if xa >= 0 and xa < len(_SCREAMING_SNAKE_CASE       ) and ya >= 0 and ya < len(grid[0]       ):
																								if closed[xa][ya] == 0 and grid[xa][ya] == 0:
																												SCREAMING_SNAKE_CASE  :						Optional[Any]      					= g + cost
																												SCREAMING_SNAKE_CASE  :						Any      					= ga + heuristic[xa][ya]
																												cell.append([fa, ga, xa, ya]       )
																												SCREAMING_SNAKE_CASE  :						List[Any]      					= 1
																												SCREAMING_SNAKE_CASE  :						Optional[int]      					= i
				SCREAMING_SNAKE_CASE  :						Dict      					= []
				SCREAMING_SNAKE_CASE  :						List[Any]      					= goal[0]
				SCREAMING_SNAKE_CASE  :						Optional[int]      					= goal[1]
				invpath.append([x, y]       )  # we get the reverse path from here
				while x != init[0] or y != init[1]:
								SCREAMING_SNAKE_CASE  :						str      					= x - DIRECTIONS[action[x][y]][0]
								SCREAMING_SNAKE_CASE  :						str      					= y - DIRECTIONS[action[x][y]][1]
								SCREAMING_SNAKE_CASE  :						Tuple      					= xa
								SCREAMING_SNAKE_CASE  :						Dict      					= ya
								invpath.append([x, y]       )

				SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= []
				for i in range(len(_SCREAMING_SNAKE_CASE       )       ):
								path.append(invpath[len(_SCREAMING_SNAKE_CASE       ) - 1 - i]       )
				return path, action


if __name__ == "__main__":
	snake_case_			=     [
	    [0, 1, 0, 0, 0, 0],
	    [0, 1, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
	    [0, 1, 0, 0, 0, 0],
	    [0, 1, 0, 0, 1, 0],
	    [0, 0, 0, 0, 1, 0],
	]

	snake_case_			=     [0, 0]
	# all coordinates are given in format [y,x]
	snake_case_			=     [len(grid) - 1, len(grid[0]) - 1]
	snake_case_			=     1

	# the cost map which pushes the path closer to the goal
	snake_case_			=     [[0 for row in range(len(grid[0]))] for col in range(len(grid))]
	for i in range(len(grid)):
		for j in range(len(grid[0])):
			snake_case_			=     abs(i - goal[0]) + abs(j - goal[1])
			if grid[i][j] == 1:
				# added extra penalty in the heuristic map
				snake_case_			=     99

	snake_case_			,				snake_case_			=     search(grid, init, goal, cost, heuristic)

	print("""ACTION MAP""")
	for i in range(len(action)):
		print(action[i])

	for i in range(len(path)):
		print(path[i])




