



import json
import os
import unittest

from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class 				snake_case__(_UpperCamelCase    ,      unittest.TestCase      ):

					"""simple docstring"""






					lowercase_								=		OpenAIGPTTokenizer
					lowercase_								=		OpenAIGPTTokenizerFast
					lowercase_								=		True
					lowercase_								=		False







					def 			snake_case					(							self :     Dict					):
									super().setUp()

									# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
									lowercase__					:   Dict													=					[
									    "l",
									    "o",
									    "w",
									    "e",
									    "r",
									    "s",
									    "t",
									    "i",
									    "d",
									    "n",
									    "w</w>",
									    "r</w>",
									    "t</w>",
									    "lo",
									    "low",
									    "er</w>",
									    "low</w>",
									    "lowest</w>",
									    "newer</w>",
									    "wider</w>",
									    "<unk>",
									]
									lowercase__					:   List[Any]													=					dict(zip(SCREAMING_SNAKE_CASE				,       range(len(SCREAMING_SNAKE_CASE					)					)					)					)
									lowercase__					:   Dict													=					["#version: 0.2", "l o", "lo w", "e r</w>", ""]

									lowercase__					:   Optional[Any]													=					os.path.join(self.tmpdirname				,       VOCAB_FILES_NAMES["vocab_file"]					)
									lowercase__					:   str													=					os.path.join(self.tmpdirname				,       VOCAB_FILES_NAMES["merges_file"]					)
									with open(self.vocab_file				,       "w"					) as fp:
													fp.write(json.dumps(SCREAMING_SNAKE_CASE					)					)
									with open(self.merges_file				,       "w"					) as fp:
													fp.write("\n".join(SCREAMING_SNAKE_CASE					)					)







					def 			snake_case					(							self :     Dict				,       SCREAMING_SNAKE_CASE :     Tuple					):
									return "lower newer", "lower newer"







					def 			snake_case					(							self :     Optional[int]					):
									lowercase__					:   List[str]													=					OpenAIGPTTokenizer(self.vocab_file				,       self.merges_file					)

									lowercase__					:   int													=					"lower"
									lowercase__					:   List[str]													=					["low", "er</w>"]
									lowercase__					:   int													=					tokenizer.tokenize(SCREAMING_SNAKE_CASE					)
									self.assertListEqual(SCREAMING_SNAKE_CASE				,       SCREAMING_SNAKE_CASE					)

									lowercase__					:   Any													=					tokens + ["<unk>"]
									lowercase__					:   List[str]													=					[14, 15, 20]
									self.assertListEqual(tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE					)				,       SCREAMING_SNAKE_CASE					)







					def 			snake_case					(							self :     List[Any]				,       SCREAMING_SNAKE_CASE :     Any=15					):
									for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
													with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""					):
																	lowercase__					:   List[Any]													=					self.rust_tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE				,       **SCREAMING_SNAKE_CASE					)

																	# Simple input
																	lowercase__					:   Dict													=					"This is a simple input"
																	lowercase__					:   Tuple													=					["This is a simple input 1", "This is a simple input 2"]
																	lowercase__					:   Optional[Any]													=					("This is a simple input", "This is a pair")
																	lowercase__					:   Dict													=					[
																	    ("This is a simple input 1", "This is a simple input 2"),
																	    ("This is a simple pair 1", "This is a simple pair 2"),
																	]

																	# Simple input tests
																	self.assertRaises(SCREAMING_SNAKE_CASE				,       tokenizer_r.encode				,       SCREAMING_SNAKE_CASE				,       max_length=SCREAMING_SNAKE_CASE				,       padding="max_length"					)

																	# Simple input
																	self.assertRaises(SCREAMING_SNAKE_CASE				,       tokenizer_r.encode_plus				,       SCREAMING_SNAKE_CASE				,       max_length=SCREAMING_SNAKE_CASE				,       padding="max_length"					)

																	# Simple input
																	self.assertRaises(
																	    SCREAMING_SNAKE_CASE				,       tokenizer_r.batch_encode_plus				,       SCREAMING_SNAKE_CASE				,       max_length=SCREAMING_SNAKE_CASE				,       padding="max_length"				,       )

																	# Pair input
																	self.assertRaises(SCREAMING_SNAKE_CASE				,       tokenizer_r.encode				,       SCREAMING_SNAKE_CASE				,       max_length=SCREAMING_SNAKE_CASE				,       padding="max_length"					)

																	# Pair input
																	self.assertRaises(SCREAMING_SNAKE_CASE				,       tokenizer_r.encode_plus				,       SCREAMING_SNAKE_CASE				,       max_length=SCREAMING_SNAKE_CASE				,       padding="max_length"					)

																	# Pair input
																	self.assertRaises(
																	    SCREAMING_SNAKE_CASE				,       tokenizer_r.batch_encode_plus				,       SCREAMING_SNAKE_CASE				,       max_length=SCREAMING_SNAKE_CASE				,       padding="max_length"				,       )







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






@require_ftfy
@require_spacy
@require_tokenizers
class 				snake_case__(_UpperCamelCase      ):

					"""simple docstring"""






					pass









from __future__ import annotations

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


def  __lowerCamelCase (       lowerCamelCase__					,			lowerCamelCase__					,			lowerCamelCase__					,			lowerCamelCase__					,			lowerCamelCase__					,			):

				"""simple docstring"""


				lowercase__					:   Optional[int]													=					[
				    [0 for col in range(len(grid[0]						)						)] for row in range(len(lowerCamelCase__						)						)
				]  # the reference grid
				lowercase__					:   List[Any]													=					1
				lowercase__					:   Tuple													=					[
				    [0 for col in range(len(grid[0]						)						)] for row in range(len(lowerCamelCase__						)						)
				]  # the action grid

				lowercase__					:   Union[str, Any]													=					init[0]
				lowercase__					:   List[str]													=					init[1]
				lowercase__					:   Optional[Any]													=					0
				lowercase__					:   Optional[int]													=					g + heuristic[x][y]  # cost from starting cell to destination cell
				lowercase__					:   Tuple													=					[[f, g, x, y]]

				lowercase__					:   Union[str, Any]													=					False  # flag that is set when search is complete
				lowercase__					:   Any													=					False  # flag set if we can't find expand

				while not found and not resign:
								if len(lowerCamelCase__						) == 0:
												raise ValueError("Algorithm is unable to find solution"						)
								else:  # to choose the least costliest action so as to move closer to the goal
												cell.sort()
												cell.reverse()
												lowercase__					:   Tuple													=					cell.pop()
												lowercase__					:   Optional[Any]													=					next_cell[2]
												lowercase__					:   int													=					next_cell[3]
												lowercase__					:   Union[str, Any]													=					next_cell[1]

												if x == goal[0] and y == goal[1]:
																lowercase__					:   Tuple													=					True
												else:
																for i in range(len(lowerCamelCase__						)						):  # to try out different valid actions
																				lowercase__					:   Tuple													=					x + DIRECTIONS[i][0]
																				lowercase__					:   str													=					y + DIRECTIONS[i][1]
																				if xa >= 0 and xa < len(lowerCamelCase__						) and ya >= 0 and ya < len(grid[0]						):
																								if closed[xa][ya] == 0 and grid[xa][ya] == 0:
																												lowercase__					:   List[Any]													=					g + cost
																												lowercase__					:   Tuple													=					ga + heuristic[xa][ya]
																												cell.append([fa, ga, xa, ya]						)
																												lowercase__					:   Dict													=					1
																												lowercase__					:   Union[str, Any]													=					i
				lowercase__					:   Optional[int]													=					[]
				lowercase__					:   List[Any]													=					goal[0]
				lowercase__					:   Optional[int]													=					goal[1]
				invpath.append([x, y]						)  # we get the reverse path from here
				while x != init[0] or y != init[1]:
								lowercase__					:   int													=					x - DIRECTIONS[action[x][y]][0]
								lowercase__					:   List[Any]													=					y - DIRECTIONS[action[x][y]][1]
								lowercase__					:   Optional[Any]													=					xa
								lowercase__					:   Dict													=					ya
								invpath.append([x, y]						)

				lowercase__					:   List[str]													=					[]
				for i in range(len(lowerCamelCase__						)						):
								path.append(invpath[len(lowerCamelCase__						) - 1 - i]						)
				return path, action


if __name__ == "__main__":
				lowerCAmelCase__					  =  [
				    [0, 1, 0, 0, 0, 0],
				    [0, 1, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
				    [0, 1, 0, 0, 0, 0],
				    [0, 1, 0, 0, 1, 0],
				    [0, 0, 0, 0, 1, 0],
				]

				lowerCAmelCase__					  =  [0, 0]
				# all coordinates are given in format [y,x]
				lowerCAmelCase__					  =  [len(grid) - 1, len(grid[0]) - 1]
				lowerCAmelCase__					  =  1

				# the cost map which pushes the path closer to the goal
				lowerCAmelCase__					  =  [[0 for row in range(len(grid[0]))] for col in range(len(grid))]
				for i in range(len(grid)):
								for j in range(len(grid[0])):
												lowerCAmelCase__					  =  abs(i - goal[0]) + abs(j - goal[1])
												if grid[i][j] == 1:
																# added extra penalty in the heuristic map
																lowerCAmelCase__					  =  9_9

				lowerCAmelCase__  ,						lowerCAmelCase__					  =  search(grid, init, goal, cost, heuristic)

				print('''ACTION MAP''')
				for i in range(len(action)):
								print(action[i])

				for i in range(len(path)):
								print(path[i])




