



"""simple docstring"""






from __future__ import annotations

import time
from math import sqrt

# 1 for manhattan, 0 for euclidean
_lowercase : Any      						=						0

_lowercase : List[Any]      						=						[
    [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],
]

_lowercase : str      						=						[[-1, 0], [0, -1], [1, 0], [0, 1]]  # up, left, down, right

_lowercase : Dict      						=						tuple[int, int]

class        __SCREAMING_SNAKE_CASE	:


					'''simple docstring'''





					def __init__(       self							:  Optional[Any],  lowerCamelCase							:  int,  lowerCamelCase							:  int,  lowerCamelCase							:  int,  lowerCamelCase							:  int,  lowerCamelCase							:  int,  lowerCamelCase							:  Node | None,  )->					None:
								lowerCamelCase__		:		Any			=pos_x
								lowerCamelCase__		:		int			=pos_y
								lowerCamelCase__		:		Dict			=(pos_y, pos_x)
								lowerCamelCase__		:		Tuple			=goal_x
								lowerCamelCase__		:		Any			=goal_y
								lowerCamelCase__		:		str			=g_cost
								lowerCamelCase__		:		Union[str, Any]			=parent
								lowerCamelCase__		:		Dict			=self.calculate_heuristic()
								lowerCamelCase__		:		List[Any]			=self.g_cost + self.h_cost



					def 		snake_case       (       self							:  Union[str, Any]     )->					float:
								lowerCamelCase__		:		Optional[int]			=self.pos_x - self.goal_x
								lowerCamelCase__		:		Optional[int]			=self.pos_y - self.goal_y
								if HEURISTIC == 1:
											return abs(lowerCamelCase     ) + abs(lowerCamelCase     )
								else:
											return sqrt(dy**2 + dx**2     )




					def __lt__(       self							:  Optional[int],  lowerCamelCase							:  Node     )->					bool:
								return self.f_cost < other.f_cost





class        __SCREAMING_SNAKE_CASE	:


					'''simple docstring'''





					def __init__(       self							:  Union[str, Any],  lowerCamelCase							:  TPosition,  lowerCamelCase							:  TPosition     )->					List[Any]:
								lowerCamelCase__		:		List[str]			=Node(start[1],  start[0],  goal[1],  goal[0],  0,  lowerCamelCase     )
								lowerCamelCase__		:		Any			=Node(goal[1],  goal[0],  goal[1],  goal[0],  9_9999,  lowerCamelCase     )

								lowerCamelCase__		:		int			=[self.start]
								lowerCamelCase__		:		list[Node]			=[]

								lowerCamelCase__		:		Union[str, Any]			=False



					def 		snake_case       (       self							:  List[Any]     )->					list[TPosition]:
								while self.open_nodes:
											# Open Nodes are sorted using __lt__
											self.open_nodes.sort()
											lowerCamelCase__		:		Union[str, Any]			=self.open_nodes.pop(0     )

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

											self.closed_nodes.append(lowerCamelCase     )
											lowerCamelCase__		:		Tuple			=self.get_successors(lowerCamelCase     )

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

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

								return [self.start.pos]



					def 		snake_case       (       self							:  Dict,  lowerCamelCase							:  Node     )->					list[Node]:
								lowerCamelCase__		:		List[str]			=[]
								for action in delta:
											lowerCamelCase__		:		List[Any]			=parent.pos_x + action[1]
											lowerCamelCase__		:		Any			=parent.pos_y + action[0]
											if not (0 <= pos_x <= len(grid[0]     ) - 1 and 0 <= pos_y <= len(lowerCamelCase     ) - 1):
														continue

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

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




					def 		snake_case       (       self							:  Any,  lowerCamelCase							:  Node | None     )->					list[TPosition]:
								lowerCamelCase__		:		Dict			=node
								lowerCamelCase__		:		List[str]			=[]
								while current_node is not None:
											path.append((current_node.pos_y, current_node.pos_x)     )
											lowerCamelCase__		:		List[str]			=current_node.parent
								path.reverse()
								return path





class        __SCREAMING_SNAKE_CASE	:


					'''simple docstring'''





					def __init__(       self							:  int,  lowerCamelCase							:  TPosition,  lowerCamelCase							:  TPosition     )->					None:
								lowerCamelCase__		:		Dict			=AStar(lowerCamelCase,  lowerCamelCase     )
								lowerCamelCase__		:		int			=AStar(lowerCamelCase,  lowerCamelCase     )
								lowerCamelCase__		:		Tuple			=False



					def 		snake_case       (       self							:  Union[str, Any]     )->					list[TPosition]:
								while self.fwd_astar.open_nodes or self.bwd_astar.open_nodes:
											self.fwd_astar.open_nodes.sort()
											self.bwd_astar.open_nodes.sort()
											lowerCamelCase__		:		List[Any]			=self.fwd_astar.open_nodes.pop(0     )
											lowerCamelCase__		:		str			=self.bwd_astar.open_nodes.pop(0     )

											if current_bwd_node.pos == current_fwd_node.pos:
														return self.retrace_bidirectional_path(
														    lowerCamelCase,  lowerCamelCase     )

											self.fwd_astar.closed_nodes.append(lowerCamelCase     )
											self.bwd_astar.closed_nodes.append(lowerCamelCase     )

											lowerCamelCase__		:		Any			=current_bwd_node
											lowerCamelCase__		:		List[Any]			=current_fwd_node

											lowerCamelCase__		:		Union[str, Any]			={
											    self.fwd_astar: self.fwd_astar.get_successors(lowerCamelCase     ),
											    self.bwd_astar: self.bwd_astar.get_successors(lowerCamelCase     ),
											}

											for astar in [self.fwd_astar, self.bwd_astar]:
														for child_node in successors[astar]:
																	if child_node in astar.closed_nodes:
																				continue

																	if child_node not in astar.open_nodes:
																				astar.open_nodes.append(lowerCamelCase     )
																	else:
																				# retrieve the best current path
																				lowerCamelCase__		:		int			=astar.open_nodes.pop(
																				    astar.open_nodes.index(lowerCamelCase     )     )

																				if child_node.g_cost < better_node.g_cost:
																							astar.open_nodes.append(lowerCamelCase     )
																				else:
																							astar.open_nodes.append(lowerCamelCase     )

								return [self.fwd_astar.start.pos]




					def 		snake_case       (       self							:  List[Any],  lowerCamelCase							:  Node,  lowerCamelCase							:  Node     )->					list[TPosition]:
								lowerCamelCase__		:		int			=self.fwd_astar.retrace_path(lowerCamelCase     )
								lowerCamelCase__		:		int			=self.bwd_astar.retrace_path(lowerCamelCase     )
								bwd_path.pop()
								bwd_path.reverse()
								lowerCamelCase__		:		Tuple			=fwd_path + bwd_path
								return path


if __name__ == "__main__":
		# all coordinates are given in format [y,x]
		_lowercase : Union[str, Any]      						=						(0, 0)
		_lowercase : Optional[Any]      						=						(len(grid) - 1, len(grid[0]) - 1)
		for elem in grid:
				print(elem)

		_lowercase : List[str]      						=						time.time()
		_lowercase : List[str]      						=						AStar(init, goal)
		_lowercase : Any      						=						a_star.search()
		_lowercase : Union[str, Any]      						=						time.time() - start_time
		print(f'AStar execution time = {end_time:f} seconds')

		_lowercase : Any      						=						time.time()
		_lowercase : Any      						=						BidirectionalAStar(init, goal)
		_lowercase : List[str]      						=						time.time() - bd_start_time
		print(f'BidirectionalAStar execution time = {bd_end_time:f} seconds')









"""simple docstring"""






import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List

import git
import torch
from torch.utils.data import Dataset

from transformers import BartTokenizer, RagTokenizer, TaTokenizer






def      snake_case__   (		__lowerCamelCase				:    Union[str, Any]							,		__lowerCamelCase				:    Tuple							,		__lowerCamelCase				:    Any							,		__lowerCamelCase				:    Tuple							,		__lowerCamelCase				:    Tuple=True							,		__lowerCamelCase				:    Dict="pt"	):
			"""simple docstring"""
			lowerCamelCase__		:		str			={'''add_prefix_space''': True} if isinstance(__lowerCamelCase							,		__lowerCamelCase	) and not line.startswith(''' '''	) else {}
			lowerCamelCase__		:		int			=padding_side
			return tokenizer(
			    [line]							,		max_length=__lowerCamelCase							,		padding='''max_length''' if pad_to_max_length else None							,		truncation=__lowerCamelCase							,		return_tensors=__lowerCamelCase							,		add_special_tokens=__lowerCamelCase							,		**__lowerCamelCase							,		)






def      snake_case__   (		__lowerCamelCase				:    str							,		__lowerCamelCase				:    List[Any]							,		__lowerCamelCase				:    Optional[int]=None							,		):
			"""simple docstring"""
			lowerCamelCase__		:		Any			=input_ids.ne(__lowerCamelCase	).any(dim=0	)
			if attention_mask is None:
						return input_ids[:, keep_column_mask]
			else:
						return (input_ids[:, keep_column_mask], attention_mask[:, keep_column_mask])

class        __SCREAMING_SNAKE_CASE	(      lowerCAmelCase_   ):


					'''simple docstring'''





					def __init__(       self							:  str,  lowerCamelCase							:  Union[str, Any],  lowerCamelCase							:  Dict,  lowerCamelCase							:  Union[str, Any],  lowerCamelCase							:  Dict,  lowerCamelCase							:  str="train",  lowerCamelCase							:  List[Any]=None,  lowerCamelCase							:  Tuple=None,  lowerCamelCase							:  List[str]=None,  lowerCamelCase							:  int="",  )->					List[Any]:
								super().__init__()
								lowerCamelCase__		:		Tuple			=Path(lowerCamelCase     ).joinpath(type_path + '''.source'''     )
								lowerCamelCase__		:		str			=Path(lowerCamelCase     ).joinpath(type_path + '''.target'''     )
								lowerCamelCase__		:		Dict			=self.get_char_lens(self.src_file     )
								lowerCamelCase__		:		Tuple			=max_source_length
								lowerCamelCase__		:		Optional[int]			=max_target_length
								assert min(self.src_lens     ) > 0, F'''found empty line in {self.src_file}'''
								lowerCamelCase__		:		Dict			=tokenizer
								lowerCamelCase__		:		List[str]			=prefix
								if n_obs is not None:
											lowerCamelCase__		:		int			=self.src_lens[:n_obs]
								lowerCamelCase__		:		Dict			=src_lang
								lowerCamelCase__		:		Tuple			=tgt_lang



					def __len__(       self							:  Dict     )->					Optional[int]:
								return len(self.src_lens     )



					def __getitem__(       self							:  List[str],  lowerCamelCase							:  Optional[int]     )->					Dict[str, torch.Tensor]:
								lowerCamelCase__		:		List[Any]			=index + 1  # linecache starts at 1
								lowerCamelCase__		:		Optional[int]			=self.prefix + linecache.getline(str(self.src_file     ),  lowerCamelCase     ).rstrip('''\n'''     )
								lowerCamelCase__		:		Optional[Any]			=linecache.getline(str(self.tgt_file     ),  lowerCamelCase     ).rstrip('''\n'''     )
								assert source_line, F'''empty source line for index {index}'''
								assert tgt_line, F'''empty tgt line for index {index}'''

								# Need to add eos token manually for T5
								if isinstance(self.tokenizer,  lowerCamelCase     ):
											source_line += self.tokenizer.eos_token
											tgt_line += self.tokenizer.eos_token

								# Pad source and target to the right
								lowerCamelCase__		:		Optional[int]			=(
								    self.tokenizer.question_encoder if isinstance(self.tokenizer,  lowerCamelCase     ) else self.tokenizer
								)
								lowerCamelCase__		:		Tuple			=self.tokenizer.generator if isinstance(self.tokenizer,  lowerCamelCase     ) else self.tokenizer

								lowerCamelCase__		:		Optional[int]			=encode_line(lowerCamelCase,  lowerCamelCase,  self.max_source_length,  '''right'''     )
								lowerCamelCase__		:		str			=encode_line(lowerCamelCase,  lowerCamelCase,  self.max_target_length,  '''right'''     )

								lowerCamelCase__		:		str			=source_inputs['''input_ids'''].squeeze()
								lowerCamelCase__		:		str			=target_inputs['''input_ids'''].squeeze()
								lowerCamelCase__		:		Union[str, Any]			=source_inputs['''attention_mask'''].squeeze()
								return {
								    "input_ids": source_ids,
								    "attention_mask": src_mask,
								    "decoder_input_ids": target_ids,
								}



					@staticmethod
					def 		snake_case       (       lowerCamelCase							:  Union[str, Any]     )->					Optional[int]:
								return [len(lowerCamelCase     ) for x in Path(lowerCamelCase     ).open().readlines()]




					def 		snake_case       (       self							:  str,  lowerCamelCase							:  str     )->					Dict[str, torch.Tensor]:
								lowerCamelCase__		:		List[Any]			=torch.stack([x['''input_ids'''] for x in batch]     )
								lowerCamelCase__		:		int			=torch.stack([x['''attention_mask'''] for x in batch]     )
								lowerCamelCase__		:		Union[str, Any]			=torch.stack([x['''decoder_input_ids'''] for x in batch]     )
								lowerCamelCase__		:		str			=(
								    self.tokenizer.generator.pad_token_id
								    if isinstance(self.tokenizer,  lowerCamelCase     )
								    else self.tokenizer.pad_token_id
								)
								lowerCamelCase__		:		List[str]			=(
								    self.tokenizer.question_encoder.pad_token_id
								    if isinstance(self.tokenizer,  lowerCamelCase     )
								    else self.tokenizer.pad_token_id
								)
								lowerCamelCase__		:		Optional[int]			=trim_batch(lowerCamelCase,  lowerCamelCase     )
								lowerCamelCase__	,   lowerCamelCase__		:		Any			=trim_batch(lowerCamelCase,  lowerCamelCase,  attention_mask=lowerCamelCase     )
								lowerCamelCase__		:		List[str]			={
								    '''input_ids''': source_ids,
								    '''attention_mask''': source_mask,
								    '''decoder_input_ids''': y,
								}
								return batch





_lowercase : Any      						=						getLogger(__name__)






def      snake_case__   (		__lowerCamelCase				:    List[List]	):
			"""simple docstring"""
			return list(itertools.chain.from_iterable(__lowerCamelCase	)	)






def      snake_case__   (		__lowerCamelCase				:    str	):
			"""simple docstring"""
			lowerCamelCase__		:		Dict			=get_git_info()
			save_json(__lowerCamelCase							,		os.path.join(__lowerCamelCase							,		'''git_log.json'''	)	)






def      snake_case__   (		__lowerCamelCase				:    Union[str, Any]							,		__lowerCamelCase				:    Optional[int]							,		__lowerCamelCase				:    Dict=4							,		**__lowerCamelCase				:    int	):
			"""simple docstring"""
			with open(__lowerCamelCase							,		'''w'''	) as f:
						json.dump(__lowerCamelCase							,		__lowerCamelCase							,		indent=__lowerCamelCase							,		**__lowerCamelCase	)






def      snake_case__   (		__lowerCamelCase				:    List[Any]	):
			"""simple docstring"""
			with open(__lowerCamelCase	) as f:
						return json.load(__lowerCamelCase	)






def      snake_case__   (		):
			"""simple docstring"""
			lowerCamelCase__		:		List[Any]			=git.Repo(search_parent_directories=__lowerCamelCase	)
			lowerCamelCase__		:		Union[str, Any]			={
			    '''repo_id''': str(__lowerCamelCase	),
			    '''repo_sha''': str(repo.head.object.hexsha	),
			    '''repo_branch''': str(repo.active_branch	),
			    '''hostname''': str(socket.gethostname()	),
			}
			return repo_infos






def      snake_case__   (		__lowerCamelCase				:    Callable							,		__lowerCamelCase				:    Iterable	):
			"""simple docstring"""
			return list(map(__lowerCamelCase							,		__lowerCamelCase	)	)






def      snake_case__   (		__lowerCamelCase				:    Any							,		__lowerCamelCase				:    List[Any]	):
			"""simple docstring"""
			with open(__lowerCamelCase							,		'''wb'''	) as f:
						return pickle.dump(__lowerCamelCase							,		__lowerCamelCase	)






def      snake_case__   (		__lowerCamelCase				:    str	):
			"""simple docstring"""

			def remove_articles(__lowerCamelCase				:    List[Any]	):
						return re.sub(R'''\b(a|an|the)\b'''							,		''' '''							,		__lowerCamelCase	)

			def white_space_fix(__lowerCamelCase				:    Any	):
						return " ".join(text.split()	)

			def remove_punc(__lowerCamelCase				:    Optional[Any]	):
						lowerCamelCase__		:		Tuple			=set(string.punctuation	)
						return "".join(ch for ch in text if ch not in exclude	)

			def lower(__lowerCamelCase				:    Any	):
						return text.lower()

			return white_space_fix(remove_articles(remove_punc(lower(__lowerCamelCase	)	)	)	)






def      snake_case__   (		__lowerCamelCase				:    List[str]							,		__lowerCamelCase				:    List[str]	):
			"""simple docstring"""
			lowerCamelCase__		:		List[str]			=normalize_answer(__lowerCamelCase	).split()
			lowerCamelCase__		:		List[str]			=normalize_answer(__lowerCamelCase	).split()
			lowerCamelCase__		:		Optional[int]			=Counter(__lowerCamelCase	) & Counter(__lowerCamelCase	)
			lowerCamelCase__		:		Union[str, Any]			=sum(common.values()	)
			if num_same == 0:
						return 0
			lowerCamelCase__		:		Dict			=1.0 * num_same / len(__lowerCamelCase	)
			lowerCamelCase__		:		List[str]			=1.0 * num_same / len(__lowerCamelCase	)
			lowerCamelCase__		:		Union[str, Any]			=(2 * precision * recall) / (precision + recall)
			return fa






def      snake_case__   (		__lowerCamelCase				:    Dict							,		__lowerCamelCase				:    int	):
			"""simple docstring"""
			return normalize_answer(__lowerCamelCase	) == normalize_answer(__lowerCamelCase	)






def      snake_case__   (		__lowerCamelCase				:    List[str]							,		__lowerCamelCase				:    List[str]	):
			"""simple docstring"""
			assert len(__lowerCamelCase	) == len(__lowerCamelCase	)
			lowerCamelCase__		:		Any			=0
			for hypo, pred in zip(__lowerCamelCase							,		__lowerCamelCase	):
						em += exact_match_score(__lowerCamelCase							,		__lowerCamelCase	)
			if len(__lowerCamelCase	) > 0:
						em /= len(__lowerCamelCase	)
			return {"em": em}






def      snake_case__   (		__lowerCamelCase				:    List[str]	):
			"""simple docstring"""
			return model_prefix.startswith('''rag'''	)






def      snake_case__   (		__lowerCamelCase				:    Any							,		__lowerCamelCase				:    List[str]							,		__lowerCamelCase				:    str	):
			"""simple docstring"""
			lowerCamelCase__		:		Any			={p: p for p in extra_params}
			# T5 models don't have `dropout` param, they have `dropout_rate` instead
			lowerCamelCase__		:		Optional[int]			='''dropout_rate'''
			for p in extra_params:
						if getattr(__lowerCamelCase							,		__lowerCamelCase							,		__lowerCamelCase	):
									if not hasattr(__lowerCamelCase							,		__lowerCamelCase	) and not hasattr(__lowerCamelCase							,		equivalent_param[p]	):
												logger.info('''config doesn\'t have a `{}` attribute'''.format(__lowerCamelCase	)	)
												delattr(__lowerCamelCase							,		__lowerCamelCase	)
												continue
									lowerCamelCase__		:		List[Any]			=p if hasattr(__lowerCamelCase							,		__lowerCamelCase	) else equivalent_param[p]
									setattr(__lowerCamelCase							,		__lowerCamelCase							,		getattr(__lowerCamelCase							,		__lowerCamelCase	)	)
									delattr(__lowerCamelCase							,		__lowerCamelCase	)
			return hparams, config




