

from __future__ import annotations

A__						=							list[tuple[int, int]]

A__						=							[
    [0, 0, 0, 0, 0, 0, 0],
    [0, 1, 0, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 1, 0, 0, 0, 0],
    [1, 0, 1, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 1, 0, 0],
]

A__						=							([-1, 0], [0, -1], [1, 0], [0, 1])  # up, left, down, right

class 				__UpperCamelCase				:







	def __init__(   self: Any  , __UpperCamelCase: int  , __UpperCamelCase: int  , __UpperCamelCase: int  , __UpperCamelCase: int  , __UpperCamelCase: float  , __UpperCamelCase: Node | None  , ):

						'''simple docstring'''





						__magic_name__							=    pos_x
						__magic_name__							=    pos_y
						__magic_name__							=    (pos_y, pos_x)
						__magic_name__							=    goal_x
						__magic_name__							=    goal_y
						__magic_name__							=    g_cost
						__magic_name__							=    parent
						__magic_name__							=    self.calculate_heuristic()







	def 	_SCREAMING_SNAKE_CASE							(   self: int      ):

						'''simple docstring'''





						__magic_name__							=    abs(self.pos_x - self.goal_x      )
						__magic_name__							=    abs(self.pos_y - self.goal_y      )
						return dx + dy







	def __lt__(   self: Optional[int]  , __UpperCamelCase: int      ):

						'''simple docstring'''





						return self.f_cost < other.f_cost




class 				__UpperCamelCase				:







	def __init__(   self: List[str]  , __UpperCamelCase: tuple[int, int]  , __UpperCamelCase: tuple[int, int]      ):

						'''simple docstring'''





						__magic_name__							=    Node(start[1]  , start[0]  , goal[1]  , goal[0]  , 0  , __UpperCamelCase      )
						__magic_name__							=    Node(goal[1]  , goal[0]  , goal[1]  , goal[0]  , 9_99_99  , __UpperCamelCase      )

						__magic_name__							=    [self.start]
						__magic_name__							=    []

						__magic_name__							=    False







	def 	_SCREAMING_SNAKE_CASE							(   self: List[Any]      ):

						'''simple docstring'''





						while self.open_nodes:
											# Open Nodes are sorted using __lt__
											self.open_nodes.sort()
											__magic_name__							=    self.open_nodes.pop(0      )

											if current_node.pos == self.target.pos:
																__magic_name__							=    True
																return self.retrace_path(__UpperCamelCase      )

											self.closed_nodes.append(__UpperCamelCase      )
											__magic_name__							=    self.get_successors(__UpperCamelCase      )

											for child_node in successors:
																if child_node in self.closed_nodes:
																					continue

																if child_node not in self.open_nodes:
																					self.open_nodes.append(__UpperCamelCase      )
																else:
																					# retrieve the best current path
																					__magic_name__							=    self.open_nodes.pop(self.open_nodes.index(__UpperCamelCase      )      )

																					if child_node.g_cost < better_node.g_cost:
																										self.open_nodes.append(__UpperCamelCase      )
																					else:
																										self.open_nodes.append(__UpperCamelCase      )

						if not self.reached:
											return [self.start.pos]
						return None







	def 	_SCREAMING_SNAKE_CASE							(   self: List[str]  , __UpperCamelCase: Node      ):

						'''simple docstring'''





						__magic_name__							=    []
						for action in delta:
											__magic_name__							=    parent.pos_x + action[1]
											__magic_name__							=    parent.pos_y + action[0]

											if not (0 <= pos_x <= len(grid[0]      ) - 1 and 0 <= pos_y <= len(__UpperCamelCase      ) - 1):
																continue

											if grid[pos_y][pos_x] != 0:
																continue

											successors.append(
											    Node(
											        __UpperCamelCase  , __UpperCamelCase  , self.target.pos_y  , self.target.pos_x  , parent.g_cost + 1  , __UpperCamelCase  , )      )
						return successors







	def 	_SCREAMING_SNAKE_CASE							(   self: Tuple  , __UpperCamelCase: Node | None      ):

						'''simple docstring'''





						__magic_name__							=    node
						__magic_name__							=    []
						while current_node is not None:
											path.append((current_node.pos_y, current_node.pos_x)      )
											__magic_name__							=    current_node.parent
						path.reverse()
						return path


if __name__ == "__main__":
						A__						=							(0, 0)
						A__						=							(len(grid) - 1, len(grid[0]) - 1)
						for elem in grid:
												print(elem)

						print("------")

						A__						=							GreedyBestFirst(init, goal)
						A__						=							greedy_bf.search()
						if path:
												for pos_x, pos_y in path:
																		A__						=							2

												for elem in grid:
																		print(elem)







import unittest

from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow


if is_flax_available():
						import jax

						from transformers.models.auto.modeling_flax_auto import FlaxAutoModel
						from transformers.models.bert.modeling_flax_bert import FlaxBertModel
						from transformers.models.roberta.modeling_flax_roberta import FlaxRobertaModel

@require_flax
class 				__UpperCamelCase				(					unittest.TestCase			):







	@slow
	def 	_SCREAMING_SNAKE_CASE							(   self: Any      ):

						'''simple docstring'''





						for model_name in ["bert-base-cased", "bert-large-uncased"]:
											with self.subTest(__UpperCamelCase      ):
																__magic_name__							=    AutoConfig.from_pretrained(__UpperCamelCase      )
																self.assertIsNotNone(__UpperCamelCase      )
																self.assertIsInstance(__UpperCamelCase  , __UpperCamelCase      )

																__magic_name__							=    FlaxAutoModel.from_pretrained(__UpperCamelCase      )
																self.assertIsNotNone(__UpperCamelCase      )
																self.assertIsInstance(__UpperCamelCase  , __UpperCamelCase      )







	@slow
	def 	_SCREAMING_SNAKE_CASE							(   self: Tuple      ):

						'''simple docstring'''





						for model_name in ["roberta-base", "roberta-large"]:
											with self.subTest(__UpperCamelCase      ):
																__magic_name__							=    AutoConfig.from_pretrained(__UpperCamelCase      )
																self.assertIsNotNone(__UpperCamelCase      )
																self.assertIsInstance(__UpperCamelCase  , __UpperCamelCase      )

																__magic_name__							=    FlaxAutoModel.from_pretrained(__UpperCamelCase      )
																self.assertIsNotNone(__UpperCamelCase      )
																self.assertIsInstance(__UpperCamelCase  , __UpperCamelCase      )







	@slow
	def 	_SCREAMING_SNAKE_CASE							(   self: Dict      ):

						'''simple docstring'''





						for model_name in ["bert-base-cased", "bert-large-uncased"]:
											__magic_name__							=    AutoTokenizer.from_pretrained(__UpperCamelCase      )
											__magic_name__							=    FlaxBertModel.from_pretrained(__UpperCamelCase      )
											__magic_name__							=    tokenizer('Do you support jax jitted function?'  , return_tensors=TensorType.JAX      )

											@jax.jit
											def eval(**__UpperCamelCase: Optional[Any]      ):
																return model(**__UpperCamelCase      )

											eval(**__UpperCamelCase      ).block_until_ready()







	@slow
	def 	_SCREAMING_SNAKE_CASE							(   self: int      ):

						'''simple docstring'''





						for model_name in ["roberta-base", "roberta-large"]:
											__magic_name__							=    AutoTokenizer.from_pretrained(__UpperCamelCase      )
											__magic_name__							=    FlaxRobertaModel.from_pretrained(__UpperCamelCase      )
											__magic_name__							=    tokenizer('Do you support jax jitted function?'  , return_tensors=TensorType.JAX      )

											@jax.jit
											def eval(**__UpperCamelCase: Any      ):
																return model(**__UpperCamelCase      )

											eval(**__UpperCamelCase      ).block_until_ready()







	def 	_SCREAMING_SNAKE_CASE							(   self: Tuple      ):

						'''simple docstring'''





						with self.assertRaisesRegex(
						    __UpperCamelCase  , 'bert-base is not a local folder and is not a valid model identifier'      ):
											__magic_name__							=    FlaxAutoModel.from_pretrained('bert-base'      )







	def 	_SCREAMING_SNAKE_CASE							(   self: List[Any]      ):

						'''simple docstring'''





						with self.assertRaisesRegex(
						    __UpperCamelCase  , r'aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'      ):
											__magic_name__							=    FlaxAutoModel.from_pretrained(__UpperCamelCase  , revision='aaaaaa'      )







	def 	_SCREAMING_SNAKE_CASE							(   self: str      ):

						'''simple docstring'''





						with self.assertRaisesRegex(
						    __UpperCamelCase  , 'hf-internal-testing/config-no-model does not appear to have a file named flax_model.msgpack'  , ):
											__magic_name__							=    FlaxAutoModel.from_pretrained('hf-internal-testing/config-no-model'      )







	def 	_SCREAMING_SNAKE_CASE							(   self: int      ):

						'''simple docstring'''





						with self.assertRaisesRegex(__UpperCamelCase  , 'Use `from_pt=True` to load this model'      ):
											__magic_name__							=    FlaxAutoModel.from_pretrained('hf-internal-testing/tiny-bert-pt-only'      )




