



import collections
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


_lowerCamelCase    :		str		      =    logging.get_logger(__name__)

_lowerCamelCase    :		List[Any]		      =    """▁"""

_lowerCamelCase    :		Tuple		      =    {"""vocab_file""": """prophetnet.tokenizer"""}

_lowerCamelCase    :		str		      =    {
    """vocab_file""": {
        """microsoft/xprophetnet-large-wiki100-cased""": (
            """https://huggingface.co/microsoft/xprophetnet-large-wiki100-cased/resolve/main/prophetnet.tokenizer"""
        ),
    }
}

_lowerCamelCase    :		Optional[int]		      =    {
    """microsoft/xprophetnet-large-wiki100-cased""": {"""do_lower_case""": False},
}

_lowerCamelCase    :		Any		      =    {
    """microsoft/xprophetnet-large-wiki100-cased""": 512,
}

def        __a			(   __lowerCAmelCase   )     ->     List[Any]:
					SCREAMING_SNAKE_CASE							:     int						=				collections.OrderedDict()
					with open(__lowerCAmelCase      ,	'r'      ,	encoding='utf-8'   ) as reader:
										SCREAMING_SNAKE_CASE							:     Tuple						=				reader.readlines()
					for index, token in enumerate(__lowerCAmelCase   ):
										SCREAMING_SNAKE_CASE							:     int						=				token.rstrip('\n'   )
										SCREAMING_SNAKE_CASE							:     str						=				index
					return vocab



class 						lowercase    (							SCREAMING_SNAKE_CASE_):
						'''simple docstring'''


						UpperCAmelCase			:		int		=		VOCAB_FILES_NAMES
						UpperCAmelCase			:		Dict		=		PRETRAINED_VOCAB_FILES_MAP
						UpperCAmelCase			:		List[Any]		=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						UpperCAmelCase			:		int		=		['input_ids', 'attention_mask']







						def __init__(  self    :				Optional[int]       ,	snake_case    :				Optional[int]       ,	snake_case    :				Any="[SEP]"       ,	snake_case    :				List[Any]="[SEP]"       ,	snake_case    :				List[str]="[SEP]"       ,	snake_case    :				List[str]="[UNK]"       ,	snake_case    :				int="[PAD]"       ,	snake_case    :				Tuple="[CLS]"       ,	snake_case    :				Tuple="[MASK]"       ,	snake_case    :				Optional[Dict[str, Any]] = None       ,	**snake_case    :				Any       ,	):



											'''simple docstring'''


											SCREAMING_SNAKE_CASE							:     Tuple						=				{} if sp_model_kwargs is None else sp_model_kwargs

											super().__init__(
											    bos_token=snake_case       ,	eos_token=snake_case       ,	sep_token=snake_case       ,	unk_token=snake_case       ,	pad_token=snake_case       ,	cls_token=snake_case       ,	mask_token=snake_case       ,	sp_model_kwargs=self.sp_model_kwargs       ,	**snake_case       ,	)

											try:
																import sentencepiece as spm
											except ImportError:
																logger.warning(
																    'You need to install SentencePiece to use XLMRobertaTokenizer: https://github.com/google/sentencepiece'
																    ' pip install sentencepiece'	)
																raise

											SCREAMING_SNAKE_CASE							:     str						=				spm.SentencePieceProcessor(**self.sp_model_kwargs	)
											self.sp_model.Load(str(snake_case	)	)
											SCREAMING_SNAKE_CASE							:     List[Any]						=				vocab_file

											# Original fairseq vocab and spm vocab must be "aligned":
											# Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
											# -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
											# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
											# spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

											# put special tokens and [unused] tokens into the vocab
											SCREAMING_SNAKE_CASE							:     List[str]						=				{'[PAD]': 0, '[CLS]': 1, '[SEP]': 2, '[UNK]': 3, '[MASK]': 4}

											for i in range(10	):
																SCREAMING_SNAKE_CASE							:     List[str]						=				f'''[unused{i}]'''
																SCREAMING_SNAKE_CASE							:     Any						=				5 + i

											# The first "real" token "," has position 15 in the embedding vocab and position 3 in the spm vocab
											SCREAMING_SNAKE_CASE							:     Tuple						=				12
											SCREAMING_SNAKE_CASE							:     Optional[int]						=				{v: k for k, v in self.fairseq_tokens_to_ids.items()}
											for k in self.fairseq_tokens_to_ids.keys():
																self.unique_no_split_tokens.append(snake_case	)







						def __getstate__(  self    :				List[Any]	):



											'''simple docstring'''


											SCREAMING_SNAKE_CASE							:     Optional[int]						=				self.__dict__.copy()
											SCREAMING_SNAKE_CASE							:     Any						=				None
											return state







						def __setstate__(  self    :				Union[str, Any]       ,	snake_case    :				str	):



											'''simple docstring'''


											SCREAMING_SNAKE_CASE							:     Dict						=				d
											try:
																import sentencepiece as spm
											except ImportError:
																logger.warning(
																    'You need to install SentencePiece to use XLMRobertaTokenizer: https://github.com/google/sentencepiece'
																    ' pip install sentencepiece'	)
																raise

											# for backward compatibility
											if not hasattr(self       ,	'sp_model_kwargs'	):
																SCREAMING_SNAKE_CASE							:     List[str]						=				{}

											SCREAMING_SNAKE_CASE							:     List[str]						=				spm.SentencePieceProcessor(**self.sp_model_kwargs	)
											self.sp_model.Load(self.vocab_file	)







						def       lowerCamelCase_				(  self    :				List[Any]       ,	snake_case    :				List[int]       ,	snake_case    :				Optional[List[int]] = None       ,	snake_case    :				bool = False	):



											'''simple docstring'''


											if already_has_special_tokens:
																return super().get_special_tokens_mask(
																    token_ids_a=snake_case       ,	token_ids_a=snake_case       ,	already_has_special_tokens=snake_case	)

											if token_ids_a is None:
																return ([0] * len(snake_case	)) + [1]
											return ([0] * len(snake_case	)) + [1] + ([0] * len(snake_case	)) + [1]







						def       lowerCamelCase_				(  self    :				Dict       ,	snake_case    :				List[int]       ,	snake_case    :				Optional[List[int]] = None	):



											'''simple docstring'''


											SCREAMING_SNAKE_CASE							:     List[Any]						=				[self.sep_token_id]

											if token_ids_a is None:
																return len(token_ids_a + sep	) * [0]
											return len(token_ids_a + sep + sep + token_ids_a + sep	) * [0]







						@property
						def       lowerCamelCase_				(  self    :				List[Any]	):



											'''simple docstring'''


											return len(self.sp_model	) + self.fairseq_offset







						def       lowerCamelCase_				(  self    :				Optional[int]	):



											'''simple docstring'''


											SCREAMING_SNAKE_CASE							:     List[str]						=				{self.convert_ids_to_tokens(snake_case	): i for i in range(self.vocab_size	)}
											vocab.update(self.added_tokens_encoder	)
											return vocab







						def       lowerCamelCase_				(  self    :				Dict       ,	snake_case    :				str	):



											'''simple docstring'''


											return self.sp_model.encode(snake_case       ,	out_type=snake_case	)







						def       lowerCamelCase_				(  self    :				Any       ,	snake_case    :				Tuple	):



											'''simple docstring'''


											if token in self.fairseq_tokens_to_ids:
																return self.fairseq_tokens_to_ids[token]
											SCREAMING_SNAKE_CASE							:     Optional[Any]						=				self.sp_model.PieceToId(snake_case	)

											# Need to return unknown token if the SP model returned 0
											return spm_id + self.fairseq_offset if spm_id else self.unk_token_id







						def       lowerCamelCase_				(  self    :				List[Any]       ,	snake_case    :				int	):



											'''simple docstring'''


											if index in self.fairseq_ids_to_tokens:
																return self.fairseq_ids_to_tokens[index]
											return self.sp_model.IdToPiece(index - self.fairseq_offset	)







						def       lowerCamelCase_				(  self    :				Optional[Any]       ,	snake_case    :				Dict	):



											'''simple docstring'''


											SCREAMING_SNAKE_CASE							:     int						=				''.join(snake_case	).replace(snake_case       ,	' '	).strip()
											return out_string







						def       lowerCamelCase_				(  self    :				Optional[int]       ,	snake_case    :				str       ,	snake_case    :				Optional[str] = None	):



											'''simple docstring'''


											if not os.path.isdir(snake_case	):
																logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''	)
																return
											SCREAMING_SNAKE_CASE							:     int						=				os.path.join(
											    snake_case       ,	(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']	)

											if os.path.abspath(self.vocab_file	) != os.path.abspath(snake_case	) and os.path.isfile(self.vocab_file	):
																copyfile(self.vocab_file       ,	snake_case	)
											elif not os.path.isfile(self.vocab_file	):
																with open(snake_case       ,	'wb'	) as fi:
																					SCREAMING_SNAKE_CASE							:     Union[str, Any]						=				self.sp_model.serialized_model_proto()
																					fi.write(snake_case	)

											return (out_vocab_file,)







						def       lowerCamelCase_				(  self    :				List[str]       ,	snake_case    :				List[int]       ,	snake_case    :				Optional[List[int]] = None	):



											'''simple docstring'''


											if token_ids_a is None:
																return token_ids_a + [self.sep_token_id]
											SCREAMING_SNAKE_CASE							:     Dict						=				[self.sep_token_id]
											return token_ids_a + sep + token_ids_a + sep




from __future__ import annotations

import time
from math import sqrt

# 1 for manhattan, 0 for euclidean
_lowerCamelCase    :		List[str]		      =    0

_lowerCamelCase    :		Tuple		      =    [
    [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],
]

_lowerCamelCase    :		Tuple		      =    [[-1, 0], [0, -1], [1, 0], [0, 1]]  # up, left, down, right

_lowerCamelCase    :		Union[str, Any]		      =    tuple[int, int]


class 						lowercase    :
						'''simple docstring'''


						def __init__(  self    :				Optional[Any]       ,	snake_case    :				int       ,	snake_case    :				int       ,	snake_case    :				int       ,	snake_case    :				int       ,	snake_case    :				int       ,	snake_case    :				Node | None       ,	):



											'''simple docstring'''


											SCREAMING_SNAKE_CASE							:     Tuple						=				pos_x
											SCREAMING_SNAKE_CASE							:     str						=				pos_y
											SCREAMING_SNAKE_CASE							:     Any						=				(pos_y, pos_x)
											SCREAMING_SNAKE_CASE							:     List[str]						=				goal_x
											SCREAMING_SNAKE_CASE							:     Optional[Any]						=				goal_y
											SCREAMING_SNAKE_CASE							:     int						=				g_cost
											SCREAMING_SNAKE_CASE							:     Any						=				parent
											SCREAMING_SNAKE_CASE							:     List[Any]						=				self.calculate_heuristic()
											SCREAMING_SNAKE_CASE							:     str						=				self.g_cost + self.h_cost







						def       lowerCamelCase_				(  self    :				Optional[int]	):



											'''simple docstring'''


											SCREAMING_SNAKE_CASE							:     int						=				self.pos_x - self.goal_x
											SCREAMING_SNAKE_CASE							:     str						=				self.pos_y - self.goal_y
											if HEURISTIC == 1:
																return abs(snake_case	) + abs(snake_case	)
											else:
																return sqrt(dy**2 + dx**2	)







						def __lt__(  self    :				Any       ,	snake_case    :				Node	):



											'''simple docstring'''


											return self.f_cost < other.f_cost


class 						lowercase    :
						'''simple docstring'''


						def __init__(  self    :				Optional[Any]       ,	snake_case    :				TPosition       ,	snake_case    :				TPosition	):



											'''simple docstring'''


											SCREAMING_SNAKE_CASE							:     Union[str, Any]						=				Node(start[1]       ,	start[0]       ,	goal[1]       ,	goal[0]       ,	0       ,	snake_case	)
											SCREAMING_SNAKE_CASE							:     int						=				Node(goal[1]       ,	goal[0]       ,	goal[1]       ,	goal[0]       ,	99999       ,	snake_case	)

											SCREAMING_SNAKE_CASE							:     Any						=				[self.start]
											SCREAMING_SNAKE_CASE							:     list[Node]						=				[]

											SCREAMING_SNAKE_CASE							:     int						=				False







						def       lowerCamelCase_				(  self    :				str	):



											'''simple docstring'''


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

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

																self.closed_nodes.append(snake_case	)
																SCREAMING_SNAKE_CASE							:     int						=				self.get_successors(snake_case	)

																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(snake_case	)
																					else:
																										# retrieve the best current path
																										SCREAMING_SNAKE_CASE							:     Union[str, Any]						=				self.open_nodes.pop(self.open_nodes.index(snake_case	)	)

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

											return [self.start.pos]







						def       lowerCamelCase_				(  self    :				str       ,	snake_case    :				Node	):



											'''simple docstring'''


											SCREAMING_SNAKE_CASE							:     Tuple						=				[]
											for action in delta:
																SCREAMING_SNAKE_CASE							:     Optional[Any]						=				parent.pos_x + action[1]
																SCREAMING_SNAKE_CASE							:     Union[str, Any]						=				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       ,	parent.g_cost + 1       ,	snake_case       ,	)	)
											return successors







						def       lowerCamelCase_				(  self    :				Optional[int]       ,	snake_case    :				Node | None	):



											'''simple docstring'''


											SCREAMING_SNAKE_CASE							:     Optional[int]						=				node
											SCREAMING_SNAKE_CASE							:     List[Any]						=				[]
											while current_node is not None:
																path.append((current_node.pos_y, current_node.pos_x)	)
																SCREAMING_SNAKE_CASE							:     Dict						=				current_node.parent
											path.reverse()
											return path


class 						lowercase    :
						'''simple docstring'''


						def __init__(  self    :				str       ,	snake_case    :				TPosition       ,	snake_case    :				TPosition	):



											'''simple docstring'''


											SCREAMING_SNAKE_CASE							:     Any						=				AStar(snake_case       ,	snake_case	)
											SCREAMING_SNAKE_CASE							:     Optional[int]						=				AStar(snake_case       ,	snake_case	)
											SCREAMING_SNAKE_CASE							:     str						=				False







						def       lowerCamelCase_				(  self    :				Optional[int]	):



											'''simple docstring'''


											while self.fwd_astar.open_nodes or self.bwd_astar.open_nodes:
																self.fwd_astar.open_nodes.sort()
																self.bwd_astar.open_nodes.sort()
																SCREAMING_SNAKE_CASE							:     Dict						=				self.fwd_astar.open_nodes.pop(0	)
																SCREAMING_SNAKE_CASE							:     Any						=				self.bwd_astar.open_nodes.pop(0	)

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

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

																SCREAMING_SNAKE_CASE							:     str						=				current_bwd_node
																SCREAMING_SNAKE_CASE							:     int						=				current_fwd_node

																SCREAMING_SNAKE_CASE							:     str						=				{
																    self.fwd_astar: self.fwd_astar.get_successors(snake_case	),
																    self.bwd_astar: self.bwd_astar.get_successors(snake_case	),
																}

																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(snake_case	)
																										else:
																															# retrieve the best current path
																															SCREAMING_SNAKE_CASE							:     List[Any]						=				astar.open_nodes.pop(
																															    astar.open_nodes.index(snake_case	)	)

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

											return [self.fwd_astar.start.pos]







						def       lowerCamelCase_				(  self    :				str       ,	snake_case    :				Node       ,	snake_case    :				Node	):



											'''simple docstring'''


											SCREAMING_SNAKE_CASE							:     Union[str, Any]						=				self.fwd_astar.retrace_path(snake_case	)
											SCREAMING_SNAKE_CASE							:     Optional[Any]						=				self.bwd_astar.retrace_path(snake_case	)
											bwd_path.pop()
											bwd_path.reverse()
											SCREAMING_SNAKE_CASE							:     Union[str, Any]						=				fwd_path + bwd_path
											return path


if __name__ == "__main__":
			# all coordinates are given in format [y,x]
			_lowerCamelCase    :		Tuple		      =    (0, 0)
			_lowerCamelCase    :		Dict		      =    (len(grid) - 1, len(grid[0]) - 1)
			for elem in grid:
						print(elem)

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

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