
from __future__ import annotations

import time

_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    ,		__a    ,		__a    ,		__a    ,		__a    ,		__a)	->	Optional[Any]:






							'''simple docstring'''
							_UpperCamelCase										=  pos_x
							_UpperCamelCase										=  pos_y
							_UpperCamelCase										=  (pos_y, pos_x)
							_UpperCamelCase										=  goal_x
							_UpperCamelCase										=  goal_y
							_UpperCamelCase										=  parent






class    _UpperCAmelCase:



		def __init__( self    ,		__a    ,		__a)	->	Tuple:






							'''simple docstring'''
							_UpperCamelCase										=  Node(start[1]    ,		start[0]    ,		goal[1]    ,		goal[0]    ,		__A)
							_UpperCamelCase										=  Node(goal[1]    ,		goal[0]    ,		goal[1]    ,		goal[0]    ,		__A)

							_UpperCamelCase										=  [self.start]
							_UpperCamelCase										=  False



		def 						UpperCAmelCase							( self)	->	Path | None:






							'''simple docstring'''
							while self.node_queue:
												_UpperCamelCase										=  self.node_queue.pop(0)

												if current_node.pos == self.target.pos:
																	_UpperCamelCase										=  True
																	return self.retrace_path(__A)

												_UpperCamelCase										=  self.get_successors(__A)

												for node in successors:
																	self.node_queue.append(__A)

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



		def 						UpperCAmelCase							( self    ,		__a)	->	list[Node]:






							'''simple docstring'''
							_UpperCamelCase										=  []
							for action in delta:
												_UpperCamelCase										=  parent.pos_x + action[1]
												_UpperCamelCase										=  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    ,		__A))
							return successors




		def 						UpperCAmelCase							( self    ,		__a)	->	Path:






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






class    _UpperCAmelCase:



		def __init__( self    ,		__a    ,		__a)	->	str:






							'''simple docstring'''
							_UpperCamelCase										=  BreadthFirstSearch(__A    ,		__A)
							_UpperCamelCase										=  BreadthFirstSearch(__A    ,		__A)
							_UpperCamelCase										=  False



		def 						UpperCAmelCase							( self)	->	Path | None:






							'''simple docstring'''
							while self.fwd_bfs.node_queue or self.bwd_bfs.node_queue:
												_UpperCamelCase										=  self.fwd_bfs.node_queue.pop(0)
												_UpperCamelCase										=  self.bwd_bfs.node_queue.pop(0)

												if current_bwd_node.pos == current_fwd_node.pos:
																	_UpperCamelCase										=  True
																	return self.retrace_bidirectional_path(
																	    __A    ,		__A)

												_UpperCamelCase										=  current_bwd_node
												_UpperCamelCase										=  current_fwd_node

												_UpperCamelCase										=  {
												    self.fwd_bfs: self.fwd_bfs.get_successors(__A),
												    self.bwd_bfs: self.bwd_bfs.get_successors(__A),
												}

												for bfs in [self.fwd_bfs, self.bwd_bfs]:
																	for node in successors[bfs]:
																						bfs.node_queue.append(__A)

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




		def 						UpperCAmelCase							( self    ,		__a    ,		__a)	->	Path:






							'''simple docstring'''
							_UpperCamelCase										=  self.fwd_bfs.retrace_path(__A)
							_UpperCamelCase										=  self.bwd_bfs.retrace_path(__A)
							bwd_path.pop()
							bwd_path.reverse()
							_UpperCamelCase										=  fwd_path + bwd_path
							return path


if __name__ == "__main__":
				# all coordinates are given in format [y,x]
				import doctest

				doctest.testmod()
				_a														=		(0, 0)
				_a														=		(len(grid) - 1, len(grid[0]) - 1)
				for elem in grid:
								print(elem)

				_a														=		time.time()
				_a														=		BreadthFirstSearch(init, goal)
				_a														=		bfs.search()
				_a														=		time.time() - start_bfs_time

				print("""Unidirectional BFS computation time : """, bfs_time)

				_a														=		time.time()
				_a														=		BidirectionalBreadthFirstSearch(init, goal)
				_a														=		bd_bfs.search()
				_a														=		time.time() - start_bd_bfs_time

				print("""Bidirectional BFS computation time : """, bd_bfs_time)








"""simple docstring"""





from collections import OrderedDict
from typing import Mapping

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


_a														=		logging.get_logger(__name__)

_a														=		{
    """bert-base-uncased""": """https://huggingface.co/bert-base-uncased/resolve/main/config.json""",
    """bert-large-uncased""": """https://huggingface.co/bert-large-uncased/resolve/main/config.json""",
    """bert-base-cased""": """https://huggingface.co/bert-base-cased/resolve/main/config.json""",
    """bert-large-cased""": """https://huggingface.co/bert-large-cased/resolve/main/config.json""",
    """bert-base-multilingual-uncased""": """https://huggingface.co/bert-base-multilingual-uncased/resolve/main/config.json""",
    """bert-base-multilingual-cased""": """https://huggingface.co/bert-base-multilingual-cased/resolve/main/config.json""",
    """bert-base-chinese""": """https://huggingface.co/bert-base-chinese/resolve/main/config.json""",
    """bert-base-german-cased""": """https://huggingface.co/bert-base-german-cased/resolve/main/config.json""",
    """bert-large-uncased-whole-word-masking""": (
        """https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/config.json"""
    ),
    """bert-large-cased-whole-word-masking""": (
        """https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/config.json"""
    ),
    """bert-large-uncased-whole-word-masking-finetuned-squad""": (
        """https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/config.json"""
    ),
    """bert-large-cased-whole-word-masking-finetuned-squad""": (
        """https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/config.json"""
    ),
    """bert-base-cased-finetuned-mrpc""": """https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/config.json""",
    """bert-base-german-dbmdz-cased""": """https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/config.json""",
    """bert-base-german-dbmdz-uncased""": """https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/config.json""",
    """cl-tohoku/bert-base-japanese""": """https://huggingface.co/cl-tohoku/bert-base-japanese/resolve/main/config.json""",
    """cl-tohoku/bert-base-japanese-whole-word-masking""": (
        """https://huggingface.co/cl-tohoku/bert-base-japanese-whole-word-masking/resolve/main/config.json"""
    ),
    """cl-tohoku/bert-base-japanese-char""": (
        """https://huggingface.co/cl-tohoku/bert-base-japanese-char/resolve/main/config.json"""
    ),
    """cl-tohoku/bert-base-japanese-char-whole-word-masking""": (
        """https://huggingface.co/cl-tohoku/bert-base-japanese-char-whole-word-masking/resolve/main/config.json"""
    ),
    """TurkuNLP/bert-base-finnish-cased-v1""": (
        """https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/config.json"""
    ),
    """TurkuNLP/bert-base-finnish-uncased-v1""": (
        """https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/config.json"""
    ),
    """wietsedv/bert-base-dutch-cased""": """https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/config.json""",
    # See all BERT models at https://huggingface.co/models?filter=bert
}






class    _UpperCAmelCase(   lowerCamelCase     ):
		lowercase__      =				'bert'



		def __init__( self    ,		__a=3_05_22    ,		__a=7_68    ,		__a=12    ,		__a=12    ,		__a=30_72    ,		__a="gelu"    ,		__a=0.1    ,		__a=0.1    ,		__a=5_12    ,		__a=2    ,		__a=0.02    ,		__a=1e-12    ,		__a=0    ,		__a="absolute"    ,		__a=True    ,		__a=None    ,		**__a    ,		)	->	Optional[Any]:






							'''simple docstring'''
							super().__init__(pad_token_id=__a    ,		**__a)

							_UpperCamelCase										=  vocab_size
							_UpperCamelCase										=  hidden_size
							_UpperCamelCase										=  num_hidden_layers
							_UpperCamelCase										=  num_attention_heads
							_UpperCamelCase										=  hidden_act
							_UpperCamelCase										=  intermediate_size
							_UpperCamelCase										=  hidden_dropout_prob
							_UpperCamelCase										=  attention_probs_dropout_prob
							_UpperCamelCase										=  max_position_embeddings
							_UpperCamelCase										=  type_vocab_size
							_UpperCamelCase										=  initializer_range
							_UpperCamelCase										=  layer_norm_eps
							_UpperCamelCase										=  position_embedding_type
							_UpperCamelCase										=  use_cache
							_UpperCamelCase										=  classifier_dropout






class    _UpperCAmelCase(   lowerCamelCase     ):



		@property
		def 						UpperCAmelCase							( self)	->	Mapping[str, Mapping[int, str]]:






							'''simple docstring'''
							if self.task == "multiple-choice":
												_UpperCamelCase										=  {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
							else:
												_UpperCamelCase										=  {0: '''batch''', 1: '''sequence'''}
							return OrderedDict(
							    [
							        ('''input_ids''', dynamic_axis),
							        ('''attention_mask''', dynamic_axis),
							        ('''token_type_ids''', dynamic_axis),
							    ])






