



from __future__ import annotations

import time

SCREAMING_SNAKE_CASE__       =      list[tuple[int, int]]

SCREAMING_SNAKE_CASE__       =      [
    [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],
]

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


class      __lowerCAmelCase     :
					"""simple docstring"""






					def __init__(     self					:       Dict				,					_snake_case					:       int				,					_snake_case					:       int				,					_snake_case					:       int				,					_snake_case					:       int				,					_snake_case					:       Node | None					):






								"""simple docstring"""


								A__       =    pos_x
								A__       =    pos_y
								A__       =    (pos_y, pos_x)
								A__       =    goal_x
								A__       =    goal_y
								A__       =    parent







class      __lowerCAmelCase     :
					"""simple docstring"""






					def __init__(     self					:       Any				,					_snake_case					:       tuple[int, int]				,					_snake_case					:       tuple[int, int]					):






								"""simple docstring"""


								A__       =    Node(start[1]				,					start[0]				,					goal[1]				,					goal[0]				,					_snake_case					)
								A__       =    Node(goal[1]				,					goal[0]				,					goal[1]				,					goal[0]				,					_snake_case					)

								A__       =    [self.start]
								A__       =    False



					def     _a							(     self					:       Tuple					):






								"""simple docstring"""


								while self.node_queue:
											A__       =    self.node_queue.pop(0					)

											if current_node.pos == self.target.pos:
														A__       =    True
														return self.retrace_path(_snake_case					)

											A__       =    self.get_successors(_snake_case					)

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

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



					def     _a							(     self					:       List[str]				,					_snake_case					:       Node					):






								"""simple docstring"""


								A__       =    []
								for action in delta:
											A__       =    parent.pos_x + action[1]
											A__       =    parent.pos_y + action[0]
											if not (0 <= pos_x <= len(grid[0]					) - 1 and 0 <= pos_y <= len(_snake_case					) - 1):
														continue

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

											successors.append(
											    Node(_snake_case				,					_snake_case				,					self.target.pos_y				,					self.target.pos_x				,					_snake_case					)					)
								return successors



					def     _a							(     self					:       Dict				,					_snake_case					:       Node | None					):






								"""simple docstring"""


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







class      __lowerCAmelCase     :
					"""simple docstring"""






					def __init__(     self					:       str				,					_snake_case					:       str				,					_snake_case					:       int					):






								"""simple docstring"""


								A__       =    BreadthFirstSearch(_snake_case				,					_snake_case					)
								A__       =    BreadthFirstSearch(_snake_case				,					_snake_case					)
								A__       =    False



					def     _a							(     self					:       List[str]					):






								"""simple docstring"""


								while self.fwd_bfs.node_queue or self.bwd_bfs.node_queue:
											A__       =    self.fwd_bfs.node_queue.pop(0					)
											A__       =    self.bwd_bfs.node_queue.pop(0					)

											if current_bwd_node.pos == current_fwd_node.pos:
														A__       =    True
														return self.retrace_bidirectional_path(
														    _snake_case				,					_snake_case					)

											A__       =    current_bwd_node
											A__       =    current_fwd_node

											A__       =    {
											    self.fwd_bfs: self.fwd_bfs.get_successors(_snake_case					),
											    self.bwd_bfs: self.bwd_bfs.get_successors(_snake_case					),
											}

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

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



					def     _a							(     self					:       Optional[Any]				,					_snake_case					:       Node				,					_snake_case					:       Node					):






								"""simple docstring"""


								A__       =    self.fwd_bfs.retrace_path(_snake_case					)
								A__       =    self.bwd_bfs.retrace_path(_snake_case					)
								bwd_path.pop()
								bwd_path.reverse()
								A__       =    fwd_path + bwd_path
								return path


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

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

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

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

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

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









from collections import OrderedDict
from typing import Mapping

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


SCREAMING_SNAKE_CASE__       =      logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__       =      {
    '''roberta-base''': '''https://huggingface.co/roberta-base/resolve/main/config.json''',
    '''roberta-large''': '''https://huggingface.co/roberta-large/resolve/main/config.json''',
    '''roberta-large-mnli''': '''https://huggingface.co/roberta-large-mnli/resolve/main/config.json''',
    '''distilroberta-base''': '''https://huggingface.co/distilroberta-base/resolve/main/config.json''',
    '''roberta-base-openai-detector''': '''https://huggingface.co/roberta-base-openai-detector/resolve/main/config.json''',
    '''roberta-large-openai-detector''': '''https://huggingface.co/roberta-large-openai-detector/resolve/main/config.json''',
}


class      __lowerCAmelCase     (		UpperCAmelCase_      ):
					"""simple docstring"""






					A__				:		List[str]			       =    "roberta"



					def __init__(     self					:       List[str]				,					_snake_case					:       Union[str, Any]=5_02_65				,					_snake_case					:       List[Any]=7_68				,					_snake_case					:       List[str]=12				,					_snake_case					:       List[str]=12				,					_snake_case					:       Any=30_72				,					_snake_case					:       Union[str, Any]="gelu"				,					_snake_case					:       int=0.1				,					_snake_case					:       Union[str, Any]=0.1				,					_snake_case					:       Tuple=5_12				,					_snake_case					:       Union[str, Any]=2				,					_snake_case					:       Any=0.02				,					_snake_case					:       Any=1E-12				,					_snake_case					:       List[Any]=1				,					_snake_case					:       int=0				,					_snake_case					:       Any=2				,					_snake_case					:       Optional[Any]="absolute"				,					_snake_case					:       int=True				,					_snake_case					:       Any=None				,					**_snake_case					:       Any				,					):






								"""simple docstring"""


								super().__init__(pad_token_id=_snake_case				,					bos_token_id=_snake_case				,					eos_token_id=_snake_case				,					**_snake_case					)

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







class      __lowerCAmelCase     (		UpperCAmelCase_      ):
					"""simple docstring"""






					@property
					def     _a							(     self					:       Dict					):






								"""simple docstring"""


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




