






"""simple docstring"""
import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class 			UpperCamelCase_       (__A				,						unittest.TestCase     ):
	__magic_name__	      =				RobertaTokenizer
	__magic_name__	      =				RobertaTokenizerFast
	__magic_name__	      =				True
	__magic_name__	      =				{'''cls_token''': '''<s>'''}





	def      _SCREAMING_SNAKE_CASE      (      self					: Optional[Any]						)						->			Tuple:
				super().setUp()

				# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
				UpperCAmelCase_     : Optional[Any]			     =					[
				    "l",
				    "o",
				    "w",
				    "e",
				    "r",
				    "s",
				    "t",
				    "i",
				    "d",
				    "n",
				    "\u0120",
				    "\u0120l",
				    "\u0120n",
				    "\u0120lo",
				    "\u0120low",
				    "er",
				    "\u0120lowest",
				    "\u0120newer",
				    "\u0120wider",
				    "<unk>",
				]
				UpperCAmelCase_     : str			     =					dict(zip(lowerCAmelCase_	,	range(len(lowerCAmelCase_						)						)						)						)
				UpperCAmelCase_     : Union[str, Any]			     =					["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
				UpperCAmelCase_     : Any			     =					{"unk_token": "<unk>"}

				UpperCAmelCase_     : int			     =					os.path.join(self.tmpdirname	,	VOCAB_FILES_NAMES["vocab_file"]						)
				UpperCAmelCase_     : Tuple			     =					os.path.join(self.tmpdirname	,	VOCAB_FILES_NAMES["merges_file"]						)
				with open(self.vocab_file	,	"w"	,	encoding="utf-8"						) as fp:
							fp.write(json.dumps(lowerCAmelCase_						) + "\n"						)
				with open(self.merges_file	,	"w"	,	encoding="utf-8"						) as fp:
							fp.write("\n".join(lowerCAmelCase_						)						)





	def      _SCREAMING_SNAKE_CASE      (      self					: Tuple	,	**lowerCAmelCase_					: int						)						->			List[Any]:
				kwargs.update(self.special_tokens_map						)
				return self.tokenizer_class.from_pretrained(self.tmpdirname	,	**lowerCAmelCase_						)





	def      _SCREAMING_SNAKE_CASE      (      self					: str	,	**lowerCAmelCase_					: int						)						->			Optional[int]:
				kwargs.update(self.special_tokens_map						)
				return RobertaTokenizerFast.from_pretrained(self.tmpdirname	,	**lowerCAmelCase_						)





	def      _SCREAMING_SNAKE_CASE      (      self					: Tuple	,	lowerCAmelCase_					: Union[str, Any]						)						->			Union[str, Any]:
				UpperCAmelCase_     : Optional[int]			     =					"lower newer"
				UpperCAmelCase_     : Any			     =					"lower newer"
				return input_text, output_text





	def      _SCREAMING_SNAKE_CASE      (      self					: Optional[Any]						)						->			str:
				UpperCAmelCase_     : Tuple			     =					self.tokenizer_class(self.vocab_file	,	self.merges_file	,	**self.special_tokens_map						)
				UpperCAmelCase_     : List[Any]			     =					"lower newer"
				UpperCAmelCase_     : Union[str, Any]			     =					["l", "o", "w", "er", "\u0120", "n", "e", "w", "er"]
				UpperCAmelCase_     : Dict			     =					tokenizer.tokenize(lowerCAmelCase_						)  # , add_prefix_space=True)
				self.assertListEqual(lowerCAmelCase_	,	lowerCAmelCase_						)

				UpperCAmelCase_     : List[Any]			     =					tokens + [tokenizer.unk_token]
				UpperCAmelCase_     : Tuple			     =					[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
				self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase_						)	,	lowerCAmelCase_						)





	def      _SCREAMING_SNAKE_CASE      (      self					: Dict						)						->			Union[str, Any]:
				UpperCAmelCase_     : Dict			     =					self.get_tokenizer()

				self.assertListEqual(tokenizer.encode("Hello world!"	,	add_special_tokens=lowerCAmelCase_						)	,	[0, 31_414, 232, 328, 2]						)
				self.assertListEqual(
				    tokenizer.encode("Hello world! cécé herlolip 418"	,	add_special_tokens=lowerCAmelCase_						)	,	[0, 31_414, 232, 328, 740, 1_140, 12_695, 69, 46_078, 1_588, 2]	,	)





	@slow
	def      _SCREAMING_SNAKE_CASE      (      self					: Any						)						->			Dict:
				UpperCAmelCase_     : Optional[Any]			     =					self.tokenizer_class.from_pretrained("roberta-base"						)

				UpperCAmelCase_     : Optional[int]			     =					tokenizer.encode("sequence builders"	,	add_special_tokens=lowerCAmelCase_						)
				UpperCAmelCase_     : str			     =					tokenizer.encode("multi-sequence build"	,	add_special_tokens=lowerCAmelCase_						)

				UpperCAmelCase_     : List[str]			     =					tokenizer.encode(
				    "sequence builders"	,	add_special_tokens=lowerCAmelCase_	,	add_prefix_space=lowerCAmelCase_						)
				UpperCAmelCase_     : Tuple			     =					tokenizer.encode(
				    "sequence builders"	,	"multi-sequence build"	,	add_special_tokens=lowerCAmelCase_	,	add_prefix_space=lowerCAmelCase_						)

				UpperCAmelCase_     : Optional[int]			     =					tokenizer.build_inputs_with_special_tokens(lowerCAmelCase_						)
				UpperCAmelCase_     : List[Any]			     =					tokenizer.build_inputs_with_special_tokens(lowerCAmelCase_	,	lowerCAmelCase_						)

				assert encoded_sentence == encoded_text_from_decode
				assert encoded_pair == encoded_pair_from_decode





	def      _SCREAMING_SNAKE_CASE      (      self					: List[Any]						)						->			List[Any]:
				UpperCAmelCase_     : str			     =					self.get_tokenizer()

				UpperCAmelCase_     : Optional[int]			     =					"Encode this sequence."
				UpperCAmelCase_     : List[str]			     =					tokenizer.byte_encoder[" ".encode("utf-8"						)[0]]

				# Testing encoder arguments
				UpperCAmelCase_     : Dict			     =					tokenizer.encode(lowerCAmelCase_	,	add_special_tokens=lowerCAmelCase_	,	add_prefix_space=lowerCAmelCase_						)
				UpperCAmelCase_     : Optional[int]			     =					tokenizer.convert_ids_to_tokens(encoded[0]						)[0]
				self.assertNotEqual(lowerCAmelCase_	,	lowerCAmelCase_						)

				UpperCAmelCase_     : List[str]			     =					tokenizer.encode(lowerCAmelCase_	,	add_special_tokens=lowerCAmelCase_	,	add_prefix_space=lowerCAmelCase_						)
				UpperCAmelCase_     : Any			     =					tokenizer.convert_ids_to_tokens(encoded[0]						)[0]
				self.assertEqual(lowerCAmelCase_	,	lowerCAmelCase_						)

				tokenizer.add_special_tokens({"bos_token": "<s>"}						)
				UpperCAmelCase_     : Tuple			     =					tokenizer.encode(lowerCAmelCase_	,	add_special_tokens=lowerCAmelCase_						)
				UpperCAmelCase_     : int			     =					tokenizer.convert_ids_to_tokens(encoded[1]						)[0]
				self.assertNotEqual(lowerCAmelCase_	,	lowerCAmelCase_						)

				# Testing spaces after special tokens
				UpperCAmelCase_     : List[str]			     =					"<mask>"
				tokenizer.add_special_tokens(
				    {"mask_token": AddedToken(lowerCAmelCase_	,	lstrip=lowerCAmelCase_	,	rstrip=lowerCAmelCase_						)}						)  # mask token has a left space
				UpperCAmelCase_     : Any			     =					tokenizer.convert_tokens_to_ids(lowerCAmelCase_						)

				UpperCAmelCase_     : List[Any]			     =					"Encode <mask> sequence"
				UpperCAmelCase_     : List[Any]			     =					"Encode <mask>sequence"

				UpperCAmelCase_     : List[str]			     =					tokenizer.encode(lowerCAmelCase_						)
				UpperCAmelCase_     : int			     =					encoded.index(lowerCAmelCase_						)
				UpperCAmelCase_     : str			     =					tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]						)[0]
				self.assertEqual(lowerCAmelCase_	,	lowerCAmelCase_						)

				UpperCAmelCase_     : Union[str, Any]			     =					tokenizer.encode(lowerCAmelCase_						)
				UpperCAmelCase_     : Union[str, Any]			     =					encoded.index(lowerCAmelCase_						)
				UpperCAmelCase_     : Dict			     =					tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]						)[0]
				self.assertNotEqual(lowerCAmelCase_	,	lowerCAmelCase_						)





	def      _SCREAMING_SNAKE_CASE      (      self					: Optional[int]						)						->			List[Any]:
				pass





	def      _SCREAMING_SNAKE_CASE      (      self					: Optional[Any]						)						->			int:
				for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
							with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""						):
										UpperCAmelCase_     : Tuple			     =					self.rust_tokenizer_class.from_pretrained(lowerCAmelCase_	,	**lowerCAmelCase_						)
										UpperCAmelCase_     : int			     =					self.tokenizer_class.from_pretrained(lowerCAmelCase_	,	**lowerCAmelCase_						)
										UpperCAmelCase_     : Union[str, Any]			     =					"A, <mask> AllenNLP sentence."
										UpperCAmelCase_     : Union[str, Any]			     =					tokenizer_r.encode_plus(lowerCAmelCase_	,	add_special_tokens=lowerCAmelCase_	,	return_token_type_ids=lowerCAmelCase_						)
										UpperCAmelCase_     : Optional[Any]			     =					tokenizer_p.encode_plus(lowerCAmelCase_	,	add_special_tokens=lowerCAmelCase_	,	return_token_type_ids=lowerCAmelCase_						)

										# token_type_ids should put 0 everywhere
										self.assertEqual(sum(tokens_r["token_type_ids"]						)	,	sum(tokens_p["token_type_ids"]						)						)

										# attention_mask should put 1 everywhere, so sum over length should be 1
										self.assertEqual(
										    sum(tokens_r["attention_mask"]						) / len(tokens_r["attention_mask"]						)	,	sum(tokens_p["attention_mask"]						) / len(tokens_p["attention_mask"]						)	,	)

										UpperCAmelCase_     : Tuple			     =					tokenizer_r.convert_ids_to_tokens(tokens_r["input_ids"]						)
										UpperCAmelCase_     : Optional[int]			     =					tokenizer_p.convert_ids_to_tokens(tokens_p["input_ids"]						)

										# Rust correctly handles the space before the mask while python doesnt
										self.assertSequenceEqual(tokens_p["input_ids"]	,	[0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2]						)
										self.assertSequenceEqual(tokens_r["input_ids"]	,	[0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2]						)

										self.assertSequenceEqual(
										    lowerCAmelCase_	,	["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"]						)
										self.assertSequenceEqual(
										    lowerCAmelCase_	,	["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"]						)





	def      _SCREAMING_SNAKE_CASE      (      self					: str						)						->			Tuple:
				for trim_offsets, add_prefix_space in itertools.product([True, False]	,	repeat=2						):
							UpperCAmelCase_     : List[str]			     =					self.rust_tokenizer_class.from_pretrained(
							    self.tmpdirname	,	use_fast=lowerCAmelCase_	,	add_prefix_space=lowerCAmelCase_	,	trim_offsets=lowerCAmelCase_						)

							UpperCAmelCase_     : str			     =					json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()						)
							UpperCAmelCase_     : Optional[Any]			     =					json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()						)

							self.assertEqual(pre_tokenizer_state["add_prefix_space"]	,	lowerCAmelCase_						)

							self.assertEqual(post_processor_state["add_prefix_space"]	,	lowerCAmelCase_						)
							self.assertEqual(post_processor_state["trim_offsets"]	,	lowerCAmelCase_						)





	def      _SCREAMING_SNAKE_CASE      (      self					: List[str]						)						->			Union[str, Any]:
				# Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space` and
				# `trim_offsets`
				for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
							with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""						):
										UpperCAmelCase_     : List[str]			     =					"hello"  # `hello` is a token in the vocabulary of `pretrained_name`
										UpperCAmelCase_     : Optional[int]			     =					f"""{text_of_1_token} {text_of_1_token}"""

										UpperCAmelCase_     : Tuple			     =					self.rust_tokenizer_class.from_pretrained(
										    lowerCAmelCase_	,	use_fast=lowerCAmelCase_	,	add_prefix_space=lowerCAmelCase_	,	trim_offsets=lowerCAmelCase_						)
										UpperCAmelCase_     : Optional[Any]			     =					tokenizer_r(lowerCAmelCase_	,	return_offsets_mapping=lowerCAmelCase_	,	add_special_tokens=lowerCAmelCase_						)
										self.assertEqual(encoding.offset_mapping[0]	,	(0, len(lowerCAmelCase_						))						)
										self.assertEqual(
										    encoding.offset_mapping[1]	,	(len(lowerCAmelCase_						) + 1, len(lowerCAmelCase_						) + 1 + len(lowerCAmelCase_						))	,	)

										UpperCAmelCase_     : List[str]			     =					self.rust_tokenizer_class.from_pretrained(
										    lowerCAmelCase_	,	use_fast=lowerCAmelCase_	,	add_prefix_space=lowerCAmelCase_	,	trim_offsets=lowerCAmelCase_						)
										UpperCAmelCase_     : List[Any]			     =					tokenizer_r(lowerCAmelCase_	,	return_offsets_mapping=lowerCAmelCase_	,	add_special_tokens=lowerCAmelCase_						)
										self.assertEqual(encoding.offset_mapping[0]	,	(0, len(lowerCAmelCase_						))						)
										self.assertEqual(
										    encoding.offset_mapping[1]	,	(len(lowerCAmelCase_						) + 1, len(lowerCAmelCase_						) + 1 + len(lowerCAmelCase_						))	,	)

										UpperCAmelCase_     : Union[str, Any]			     =					self.rust_tokenizer_class.from_pretrained(
										    lowerCAmelCase_	,	use_fast=lowerCAmelCase_	,	add_prefix_space=lowerCAmelCase_	,	trim_offsets=lowerCAmelCase_						)
										UpperCAmelCase_     : List[str]			     =					tokenizer_r(lowerCAmelCase_	,	return_offsets_mapping=lowerCAmelCase_	,	add_special_tokens=lowerCAmelCase_						)
										self.assertEqual(encoding.offset_mapping[0]	,	(0, len(lowerCAmelCase_						))						)
										self.assertEqual(
										    encoding.offset_mapping[1]	,	(len(lowerCAmelCase_						), len(lowerCAmelCase_						) + 1 + len(lowerCAmelCase_						))	,	)

										UpperCAmelCase_     : Dict			     =					self.rust_tokenizer_class.from_pretrained(
										    lowerCAmelCase_	,	use_fast=lowerCAmelCase_	,	add_prefix_space=lowerCAmelCase_	,	trim_offsets=lowerCAmelCase_						)
										UpperCAmelCase_     : Optional[int]			     =					tokenizer_r(lowerCAmelCase_	,	return_offsets_mapping=lowerCAmelCase_	,	add_special_tokens=lowerCAmelCase_						)
										self.assertEqual(encoding.offset_mapping[0]	,	(0, len(lowerCAmelCase_						))						)
										self.assertEqual(
										    encoding.offset_mapping[1]	,	(len(lowerCAmelCase_						), len(lowerCAmelCase_						) + 1 + len(lowerCAmelCase_						))	,	)

										UpperCAmelCase_     : Optional[int]			     =					f""" {text}"""

										# tokenizer_r = self.rust_tokenizer_class.from_pretrained(
										#     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
										# )
										# encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
										# self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
										# self.assertEqual(
										#     encoding.offset_mapping[1],
										#     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
										# )

										UpperCAmelCase_     : str			     =					self.rust_tokenizer_class.from_pretrained(
										    lowerCAmelCase_	,	use_fast=lowerCAmelCase_	,	add_prefix_space=lowerCAmelCase_	,	trim_offsets=lowerCAmelCase_						)
										UpperCAmelCase_     : str			     =					tokenizer_r(lowerCAmelCase_	,	return_offsets_mapping=lowerCAmelCase_	,	add_special_tokens=lowerCAmelCase_						)
										self.assertEqual(encoding.offset_mapping[0]	,	(1, 1 + len(lowerCAmelCase_						))						)
										self.assertEqual(
										    encoding.offset_mapping[1]	,	(1 + len(lowerCAmelCase_						) + 1, 1 + len(lowerCAmelCase_						) + 1 + len(lowerCAmelCase_						))	,	)

										UpperCAmelCase_     : Tuple			     =					self.rust_tokenizer_class.from_pretrained(
										    lowerCAmelCase_	,	use_fast=lowerCAmelCase_	,	add_prefix_space=lowerCAmelCase_	,	trim_offsets=lowerCAmelCase_						)
										UpperCAmelCase_     : Any			     =					tokenizer_r(lowerCAmelCase_	,	return_offsets_mapping=lowerCAmelCase_	,	add_special_tokens=lowerCAmelCase_						)
										self.assertEqual(encoding.offset_mapping[0]	,	(0, 1 + len(lowerCAmelCase_						))						)
										self.assertEqual(
										    encoding.offset_mapping[1]	,	(1 + len(lowerCAmelCase_						), 1 + len(lowerCAmelCase_						) + 1 + len(lowerCAmelCase_						))	,	)

										UpperCAmelCase_     : str			     =					self.rust_tokenizer_class.from_pretrained(
										    lowerCAmelCase_	,	use_fast=lowerCAmelCase_	,	add_prefix_space=lowerCAmelCase_	,	trim_offsets=lowerCAmelCase_						)
										UpperCAmelCase_     : List[Any]			     =					tokenizer_r(lowerCAmelCase_	,	return_offsets_mapping=lowerCAmelCase_	,	add_special_tokens=lowerCAmelCase_						)
										self.assertEqual(encoding.offset_mapping[0]	,	(0, 1 + len(lowerCAmelCase_						))						)
										self.assertEqual(
										    encoding.offset_mapping[1]	,	(1 + len(lowerCAmelCase_						), 1 + len(lowerCAmelCase_						) + 1 + len(lowerCAmelCase_						))	,	)











"""simple docstring"""
from __future__ import annotations

import time

lowerCamelCase_					=      list[tuple[int, int]]

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







class 			UpperCamelCase_       :





	def __init__(      self					: Optional[int]	,	lowerCAmelCase_					: int	,	lowerCAmelCase_					: int	,	lowerCAmelCase_					: int	,	lowerCAmelCase_					: int	,	lowerCAmelCase_					: Node | None						)						->			Dict:
				UpperCAmelCase_     : Any			     =					pos_x
				UpperCAmelCase_     : str			     =					pos_y
				UpperCAmelCase_     : int			     =					(pos_y, pos_x)
				UpperCAmelCase_     : int			     =					goal_x
				UpperCAmelCase_     : Tuple			     =					goal_y
				UpperCAmelCase_     : Union[str, Any]			     =					parent







class 			UpperCamelCase_       :





	def __init__(      self					: List[Any]	,	lowerCAmelCase_					: tuple[int, int]	,	lowerCAmelCase_					: tuple[int, int]						)						->			Tuple:
				UpperCAmelCase_     : List[str]			     =					Node(start[1]	,	start[0]	,	goal[1]	,	goal[0]	,	lowerCAmelCase_						)
				UpperCAmelCase_     : int			     =					Node(goal[1]	,	goal[0]	,	goal[1]	,	goal[0]	,	lowerCAmelCase_						)

				UpperCAmelCase_     : Union[str, Any]			     =					[self.start]
				UpperCAmelCase_     : int			     =					False





	def      _SCREAMING_SNAKE_CASE      (      self					: Any						)						->			Path | None:
				while self.node_queue:
							UpperCAmelCase_     : str			     =					self.node_queue.pop(0						)

							if current_node.pos == self.target.pos:
										UpperCAmelCase_     : Optional[Any]			     =					True
										return self.retrace_path(lowerCAmelCase_						)

							UpperCAmelCase_     : Optional[Any]			     =					self.get_successors(lowerCAmelCase_						)

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

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





	def      _SCREAMING_SNAKE_CASE      (      self					: Optional[int]	,	lowerCAmelCase_					: Node						)						->			list[Node]:
				UpperCAmelCase_     : List[str]			     =					[]
				for action in delta:
							UpperCAmelCase_     : List[Any]			     =					parent.pos_x + action[1]
							UpperCAmelCase_     : List[str]			     =					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	,	lowerCAmelCase_						)						)
				return successors





	def      _SCREAMING_SNAKE_CASE      (      self					: List[str]	,	lowerCAmelCase_					: Node | None						)						->			Path:
				UpperCAmelCase_     : Union[str, Any]			     =					node
				UpperCAmelCase_     : Union[str, Any]			     =					[]
				while current_node is not None:
							path.append((current_node.pos_y, current_node.pos_x)						)
							UpperCAmelCase_     : Tuple			     =					current_node.parent
				path.reverse()
				return path







class 			UpperCamelCase_       :





	def __init__(      self					: str	,	lowerCAmelCase_					: List[str]	,	lowerCAmelCase_					: Tuple						)						->			Union[str, Any]:
				UpperCAmelCase_     : Optional[int]			     =					BreadthFirstSearch(lowerCAmelCase_	,	lowerCAmelCase_						)
				UpperCAmelCase_     : str			     =					BreadthFirstSearch(lowerCAmelCase_	,	lowerCAmelCase_						)
				UpperCAmelCase_     : Optional[Any]			     =					False





	def      _SCREAMING_SNAKE_CASE      (      self					: Tuple						)						->			Path | None:
				while self.fwd_bfs.node_queue or self.bwd_bfs.node_queue:
							UpperCAmelCase_     : int			     =					self.fwd_bfs.node_queue.pop(0						)
							UpperCAmelCase_     : Dict			     =					self.bwd_bfs.node_queue.pop(0						)

							if current_bwd_node.pos == current_fwd_node.pos:
										UpperCAmelCase_     : str			     =					True
										return self.retrace_bidirectional_path(
										    lowerCAmelCase_	,	lowerCAmelCase_						)

							UpperCAmelCase_     : str			     =					current_bwd_node
							UpperCAmelCase_     : List[str]			     =					current_fwd_node

							UpperCAmelCase_     : Tuple			     =					{
							    self.fwd_bfs: self.fwd_bfs.get_successors(lowerCAmelCase_						),
							    self.bwd_bfs: self.bwd_bfs.get_successors(lowerCAmelCase_						),
							}

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

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





	def      _SCREAMING_SNAKE_CASE      (      self					: List[str]	,	lowerCAmelCase_					: Node	,	lowerCAmelCase_					: Node						)						->			Path:
				UpperCAmelCase_     : Optional[Any]			     =					self.fwd_bfs.retrace_path(lowerCAmelCase_						)
				UpperCAmelCase_     : Dict			     =					self.bwd_bfs.retrace_path(lowerCAmelCase_						)
				bwd_path.pop()
				bwd_path.reverse()
				UpperCAmelCase_     : str			     =					fwd_path + bwd_path
				return path


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

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

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

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

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

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



