





'''simple docstring'''






import shutil
import tempfile
import unittest

from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio

from .test_feature_extraction_clap import floats_list




@require_torchaudio
@require_sentencepiece
class  UpperCAmelCase     (			unittest.TestCase   ):




      def 				lowercase__    (			self			: Tuple  )				->      int:
            _lowerCAmelCase							     =							"""laion/clap-htsat-unfused"""
            _lowerCAmelCase							     =							tempfile.mkdtemp()




      def 				lowercase__    (			self			: int			,			**__snake_case			: Dict  )				->      List[Any]:
            return RobertaTokenizer.from_pretrained(self.checkpoint			,			**__snake_case  )




      def 				lowercase__    (			self			: int			,			**__snake_case			: List[Any]  )				->      Any:
            return ClapFeatureExtractor.from_pretrained(self.checkpoint			,			**__snake_case  )




      def 				lowercase__    (			self			: Any  )				->      List[str]:
            shutil.rmtree(self.tmpdirname  )




      def 				lowercase__    (			self			: Optional[int]  )				->      Dict:
            _lowerCAmelCase							     =							self.get_tokenizer()
            _lowerCAmelCase							     =							self.get_feature_extractor()

            _lowerCAmelCase							     =							ClapProcessor(tokenizer=__snake_case			,			feature_extractor=__snake_case  )

            processor.save_pretrained(self.tmpdirname  )
            _lowerCAmelCase							     =							ClapProcessor.from_pretrained(self.tmpdirname  )

            self.assertEqual(processor.tokenizer.get_vocab()			,			tokenizer.get_vocab()  )
            self.assertIsInstance(processor.tokenizer			,			__snake_case  )

            self.assertEqual(processor.feature_extractor.to_json_string()			,			feature_extractor.to_json_string()  )
            self.assertIsInstance(processor.feature_extractor			,			__snake_case  )




      def 				lowercase__    (			self			: int  )				->      List[str]:
            _lowerCAmelCase							     =							ClapProcessor(tokenizer=self.get_tokenizer()			,			feature_extractor=self.get_feature_extractor()  )
            processor.save_pretrained(self.tmpdirname  )

            _lowerCAmelCase							     =							self.get_tokenizer(bos_token="""(BOS)"""			,			eos_token="""(EOS)"""  )
            _lowerCAmelCase							     =							self.get_feature_extractor(do_normalize=__snake_case			,			padding_value=1.0  )

            _lowerCAmelCase							     =							ClapProcessor.from_pretrained(
                self.tmpdirname			,			bos_token="""(BOS)"""			,			eos_token="""(EOS)"""			,			do_normalize=__snake_case			,			padding_value=1.0  )

            self.assertEqual(processor.tokenizer.get_vocab()			,			tokenizer_add_kwargs.get_vocab()  )
            self.assertIsInstance(processor.tokenizer			,			__snake_case  )

            self.assertEqual(processor.feature_extractor.to_json_string()			,			feature_extractor_add_kwargs.to_json_string()  )
            self.assertIsInstance(processor.feature_extractor			,			__snake_case  )




      def 				lowercase__    (			self			: List[Any]  )				->      Union[str, Any]:
            _lowerCAmelCase							     =							self.get_feature_extractor()
            _lowerCAmelCase							     =							self.get_tokenizer()

            _lowerCAmelCase							     =							ClapProcessor(tokenizer=__snake_case			,			feature_extractor=__snake_case  )

            _lowerCAmelCase							     =							floats_list((3, 10_00)  )

            _lowerCAmelCase							     =							feature_extractor(__snake_case			,			return_tensors="""np"""  )
            _lowerCAmelCase							     =							processor(audios=__snake_case			,			return_tensors="""np"""  )

            for key in input_feat_extract.keys():
                  self.assertAlmostEqual(input_feat_extract[key].sum()			,			input_processor[key].sum()			,			delta=1E-2  )




      def 				lowercase__    (			self			: str  )				->      Any:
            _lowerCAmelCase							     =							self.get_feature_extractor()
            _lowerCAmelCase							     =							self.get_tokenizer()

            _lowerCAmelCase							     =							ClapProcessor(tokenizer=__snake_case			,			feature_extractor=__snake_case  )

            _lowerCAmelCase							     =							"""This is a test string"""

            _lowerCAmelCase							     =							processor(text=__snake_case  )

            _lowerCAmelCase							     =							tokenizer(__snake_case  )

            for key in encoded_tok.keys():
                  self.assertListEqual(encoded_tok[key]			,			encoded_processor[key]  )




      def 				lowercase__    (			self			: Optional[Any]  )				->      int:
            _lowerCAmelCase							     =							self.get_feature_extractor()
            _lowerCAmelCase							     =							self.get_tokenizer()

            _lowerCAmelCase							     =							ClapProcessor(tokenizer=__snake_case			,			feature_extractor=__snake_case  )

            _lowerCAmelCase							     =							[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

            _lowerCAmelCase							     =							processor.batch_decode(__snake_case  )
            _lowerCAmelCase							     =							tokenizer.batch_decode(__snake_case  )

            self.assertListEqual(__snake_case			,			__snake_case  )




      def 				lowercase__    (			self			: Any  )				->      Union[str, Any]:
            _lowerCAmelCase							     =							self.get_feature_extractor()
            _lowerCAmelCase							     =							self.get_tokenizer()

            _lowerCAmelCase							     =							ClapProcessor(tokenizer=__snake_case			,			feature_extractor=__snake_case  )

            self.assertListEqual(
                processor.model_input_names[2:]			,			feature_extractor.model_input_names			,			msg="""`processor` and `feature_extractor` model input names do not match"""			,			)














"""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)



