
'''simple docstring'''






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     __snake_case		:
					def __init__(     self,    A,    A,    A,    A,    A,    A,    ):

									"""simple docstring"""


									lowerCamelCase					:			List[Any]									= pos_x
									lowerCamelCase					:			List[str]									= pos_y
									lowerCamelCase					:			Optional[Any]									= (pos_y, pos_x)
									lowerCamelCase					:			Dict									= goal_x
									lowerCamelCase					:			Tuple									= goal_y
									lowerCamelCase					:			Optional[Any]									= g_cost
									lowerCamelCase					:			int									= parent
									lowerCamelCase					:			Tuple									= self.calculate_heuristic()
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									lowerCamelCase					:			Optional[int]									= abs(self.pos_x - self.goal_x      )
									lowerCamelCase					:			Union[str, Any]									= abs(self.pos_y - self.goal_y      )
									return dx + dy




					def __lt__(     self,    A      ):

									"""simple docstring"""


									return self.f_cost < other.f_cost





class     __snake_case		:
					def __init__(     self,    A,    A      ):

									"""simple docstring"""


									lowerCamelCase					:			Dict									= Node(start[1],    start[0],    goal[1],    goal[0],    0,    A      )
									lowerCamelCase					:			Optional[Any]									= Node(goal[1],    goal[0],    goal[1],    goal[0],    9_9999,    A      )

									lowerCamelCase					:			str									= [self.start]
									lowerCamelCase					:			list[Node]									= []

									lowerCamelCase					:			Optional[Any]									= False
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									while self.open_nodes:
													# Open Nodes are sorted using __lt__
													self.open_nodes.sort()
													lowerCamelCase					:			Optional[int]									= self.open_nodes.pop(0      )

													if current_node.pos == self.target.pos:
																	lowerCamelCase					:			Tuple									= True
																	return self.retrace_path(A      )

													self.closed_nodes.append(A      )
													lowerCamelCase					:			Any									= self.get_successors(A      )

													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(A      )
																	else:
																					# retrieve the best current path
																					lowerCamelCase					:			Optional[Any]									= self.open_nodes.pop(self.open_nodes.index(A      )      )

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

									if not self.reached:
													return [self.start.pos]
									return None
					def     UpperCAmelCase_							(     self,    A      ):

									"""simple docstring"""


									lowerCamelCase					:			Any									= []
									for action in delta:
													lowerCamelCase					:			Any									= parent.pos_x + action[1]
													lowerCamelCase					:			Dict									= parent.pos_y + action[0]

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

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

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




					def     UpperCAmelCase_							(     self,    A      ):

									"""simple docstring"""


									lowerCamelCase					:			int									= node
									lowerCamelCase					:			Optional[Any]									= []
									while current_node is not None:
													path.append((current_node.pos_y, current_node.pos_x)      )
													lowerCamelCase					:			Any									= 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)


'''simple docstring'''






import warnings
from collections import OrderedDict
from typing import Mapping

from packaging import version

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


A			      =      logging.get_logger(__name__)

A			      =      {
    'nvidia/segformer-b0-finetuned-ade-512-512': (
        'https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512/resolve/main/config.json'
    ),
    # See all SegFormer models at https://huggingface.co/models?filter=segformer
}




class     __snake_case		(   a__):
					_lowerCAmelCase			     =	'''segformer'''
					def __init__(     self,    A=3,    A=4,    A=[2, 2, 2, 2],    A=[8, 4, 2, 1],    A=[32, 64, 160, 256],    A=[7, 3, 3, 3],    A=[4, 2, 2, 2],    A=[1, 2, 5, 8],    A=[4, 4, 4, 4],    A="gelu",    A=0.0,    A=0.0,    A=0.1,    A=0.02,    A=0.1,    A=1e-6,    A=256,    A=255,    **A,    ):

									"""simple docstring"""


									super().__init__(**A      )

									if "reshape_last_stage" in kwargs and kwargs["reshape_last_stage"] is False:
													warnings.warn(
													    'Reshape_last_stage is set to False in this config. This argument is deprecated and will soon be'
													    ' removed, as the behaviour will default to that of reshape_last_stage = True.',    A,    )

									lowerCamelCase					:			Tuple									= num_channels
									lowerCamelCase					:			Dict									= num_encoder_blocks
									lowerCamelCase					:			Dict									= depths
									lowerCamelCase					:			Any									= sr_ratios
									lowerCamelCase					:			List[Any]									= hidden_sizes
									lowerCamelCase					:			List[Any]									= patch_sizes
									lowerCamelCase					:			Tuple									= strides
									lowerCamelCase					:			int									= mlp_ratios
									lowerCamelCase					:			Dict									= num_attention_heads
									lowerCamelCase					:			Union[str, Any]									= hidden_act
									lowerCamelCase					:			Tuple									= hidden_dropout_prob
									lowerCamelCase					:			Optional[int]									= attention_probs_dropout_prob
									lowerCamelCase					:			List[str]									= classifier_dropout_prob
									lowerCamelCase					:			Union[str, Any]									= initializer_range
									lowerCamelCase					:			Union[str, Any]									= drop_path_rate
									lowerCamelCase					:			int									= layer_norm_eps
									lowerCamelCase					:			Any									= decoder_hidden_size
									lowerCamelCase					:			Optional[int]									= kwargs.get('reshape_last_stage',    A      )
									lowerCamelCase					:			Any									= semantic_loss_ignore_index





class     __snake_case		(   a__):
					_lowerCAmelCase			     =	version.parse('''1.11''')
					@property
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return OrderedDict(
									    [
									        ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
									    ]      )
					@property
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return 1e-4




					@property
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return 12
