



from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase__					  =  logging.get_logger(__name__)

lowerCAmelCase__					  =  {
    '''microsoft/trocr-base-handwritten''': (
        '''https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json'''
    ),
    # See all TrOCR models at https://huggingface.co/models?filter=trocr
}

class 				snake_case__(lowercase__      ):

					"""simple docstring"""






					lowercase_								=		"""trocr"""
					lowercase_								=		["""past_key_values"""]
					lowercase_								=		{
					    """num_attention_heads""": """decoder_attention_heads""",
					    """hidden_size""": """d_model""",
					    """num_hidden_layers""": """decoder_layers""",
					}







					def __init__(							self :     Tuple				,       SCREAMING_SNAKE_CASE :     Any=50_265				,       SCREAMING_SNAKE_CASE :     Optional[int]=1_024				,       SCREAMING_SNAKE_CASE :     Tuple=12				,       SCREAMING_SNAKE_CASE :     str=16				,       SCREAMING_SNAKE_CASE :     Tuple=4_096				,       SCREAMING_SNAKE_CASE :     Tuple="gelu"				,       SCREAMING_SNAKE_CASE :     Tuple=512				,       SCREAMING_SNAKE_CASE :     int=0.1				,       SCREAMING_SNAKE_CASE :     List[str]=0.0				,       SCREAMING_SNAKE_CASE :     str=0.0				,       SCREAMING_SNAKE_CASE :     int=2				,       SCREAMING_SNAKE_CASE :     Any=0.02				,       SCREAMING_SNAKE_CASE :     List[Any]=0.0				,       SCREAMING_SNAKE_CASE :     str=True				,       SCREAMING_SNAKE_CASE :     List[Any]=False				,       SCREAMING_SNAKE_CASE :     Optional[int]=True				,       SCREAMING_SNAKE_CASE :     Union[str, Any]=True				,       SCREAMING_SNAKE_CASE :     Any=1				,       SCREAMING_SNAKE_CASE :     Tuple=0				,       SCREAMING_SNAKE_CASE :     Dict=2				,       **SCREAMING_SNAKE_CASE :     Any				,       ):
									lowercase__					:   Optional[Any]													=					vocab_size
									lowercase__					:   Optional[Any]													=					d_model
									lowercase__					:   Optional[int]													=					decoder_layers
									lowercase__					:   Any													=					decoder_attention_heads
									lowercase__					:   Optional[int]													=					decoder_ffn_dim
									lowercase__					:   Any													=					activation_function
									lowercase__					:   int													=					max_position_embeddings
									lowercase__					:   Union[str, Any]													=					dropout
									lowercase__					:   List[Any]													=					attention_dropout
									lowercase__					:   List[Any]													=					activation_dropout
									lowercase__					:   List[str]													=					init_std
									lowercase__					:   Tuple													=					decoder_layerdrop
									lowercase__					:   Any													=					use_cache
									lowercase__					:   Union[str, Any]													=					scale_embedding
									lowercase__					:   Dict													=					use_learned_position_embeddings
									lowercase__					:   List[str]													=					layernorm_embedding

									super().__init__(
									    pad_token_id=lowercase_				,       bos_token_id=lowercase_				,       eos_token_id=lowercase_				,       decoder_start_token_id=lowercase_				,       **lowercase_				,       )











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])




