



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase__					  =  {
    '''configuration_instructblip''': [
        '''INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''InstructBlipConfig''',
        '''InstructBlipQFormerConfig''',
        '''InstructBlipVisionConfig''',
    ],
    '''processing_instructblip''': ['''InstructBlipProcessor'''],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowerCAmelCase__					  =  [
				    '''INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''InstructBlipQFormerModel''',
				    '''InstructBlipPreTrainedModel''',
				    '''InstructBlipForConditionalGeneration''',
				    '''InstructBlipVisionModel''',
				]

if TYPE_CHECKING:
				from .configuration_instructblip import (
				    INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    InstructBlipConfig,
				    InstructBlipQFormerConfig,
				    InstructBlipVisionConfig,
				)
				from .processing_instructblip import InstructBlipProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_instructblip import (
								    INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
								    InstructBlipForConditionalGeneration,
								    InstructBlipPreTrainedModel,
								    InstructBlipQFormerModel,
								    InstructBlipVisionModel,
								)

else:
				import sys

				lowerCAmelCase__					  =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)









from __future__ import annotations

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


def  __lowerCamelCase (       lowerCamelCase__					,			lowerCamelCase__					,			lowerCamelCase__					,			lowerCamelCase__					,			lowerCamelCase__					,			):

				"""simple docstring"""


				lowercase__					:   Optional[int]													=					[
				    [0 for col in range(len(grid[0]						)						)] for row in range(len(lowerCamelCase__						)						)
				]  # the reference grid
				lowercase__					:   List[Any]													=					1
				lowercase__					:   Tuple													=					[
				    [0 for col in range(len(grid[0]						)						)] for row in range(len(lowerCamelCase__						)						)
				]  # the action grid

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

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

				while not found and not resign:
								if len(lowerCamelCase__						) == 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()
												lowercase__					:   Tuple													=					cell.pop()
												lowercase__					:   Optional[Any]													=					next_cell[2]
												lowercase__					:   int													=					next_cell[3]
												lowercase__					:   Union[str, Any]													=					next_cell[1]

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

				lowercase__					:   List[str]													=					[]
				for i in range(len(lowerCamelCase__						)						):
								path.append(invpath[len(lowerCamelCase__						) - 1 - i]						)
				return path, action


if __name__ == "__main__":
				lowerCAmelCase__					  =  [
				    [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],
				]

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

				# the cost map which pushes the path closer to the goal
				lowerCAmelCase__					  =  [[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])):
												lowerCAmelCase__					  =  abs(i - goal[0]) + abs(j - goal[1])
												if grid[i][j] == 1:
																# added extra penalty in the heuristic map
																lowerCAmelCase__					  =  9_9

				lowerCAmelCase__  ,						lowerCAmelCase__					  =  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])




