





from __future__ import annotations

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




def  __UpperCAmelCase(   lowercase_			,     lowercase_			,     lowercase_			,     lowercase_			,     lowercase_			,     ):
       _lowerCamelCase				:  Optional[int]						=		[
           [0 for col in range(len(grid[0]   )   )] for row in range(len(lowercase_   )   )
       ]  # the reference grid
       _lowerCamelCase				:  Optional[Any]						=		1
       _lowerCamelCase				:  str						=		[
           [0 for col in range(len(grid[0]   )   )] for row in range(len(lowercase_   )   )
       ]  # the action grid

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

       _lowerCamelCase				:  List[str]						=		False  # flag that is set when search is complete
       _lowerCamelCase				:  List[str]						=		False  # flag set if we can't find expand

       while not found and not resign:
              if len(lowercase_   ) == 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()
                     _lowerCamelCase				:  str						=		cell.pop()
                     _lowerCamelCase				:  List[Any]						=		next_cell[2]
                     _lowerCamelCase				:  Optional[Any]						=		next_cell[3]
                     _lowerCamelCase				:  Any						=		next_cell[1]

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

       _lowerCamelCase				:  Tuple						=		[]
       for i in range(len(lowercase_   )   ):
              path.append(invpath[len(lowercase_   ) - 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      							=   99

       _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])








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       __A							(   lowerCamelCase__			,unittest.TestCase	):




      """simple docstring"""







      UpperCAmelCase__							=   OpenAIGPTTokenizer
      UpperCAmelCase__							=   OpenAIGPTTokenizerFast
      UpperCAmelCase__							=   True
      UpperCAmelCase__							=   False


      def 					__snake_case      (		self):



             """simple docstring"""





             super().setUp()

             # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
             _lowerCamelCase				:  Tuple						=		[
                 '''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>''',
             ]
             _lowerCamelCase				:  Any						=		dict(zip(a__   ,				range(len(a__))))
             _lowerCamelCase				:  List[str]						=		['''#version: 0.2''', '''l o''', '''lo w''', '''e r</w>''', '''''']

             _lowerCamelCase				:  str						=		os.path.join(self.tmpdirname   ,				VOCAB_FILES_NAMES['''vocab_file'''])
             _lowerCamelCase				:  int						=		os.path.join(self.tmpdirname   ,				VOCAB_FILES_NAMES['''merges_file'''])
             with open(self.vocab_file   ,				'''w''') as fp:
                    fp.write(json.dumps(a__))
             with open(self.merges_file   ,				'''w''') as fp:
                    fp.write('''\n'''.join(a__))


      def 					__snake_case      (		self   ,				a__):



             """simple docstring"""





             return "lower newer", "lower newer"


      def 					__snake_case      (		self):



             """simple docstring"""





             _lowerCamelCase				:  Optional[Any]						=		OpenAIGPTTokenizer(self.vocab_file   ,				self.merges_file)

             _lowerCamelCase				:  Dict						=		'''lower'''
             _lowerCamelCase				:  Optional[Any]						=		['''low''', '''er</w>''']
             _lowerCamelCase				:  List[Any]						=		tokenizer.tokenize(a__)
             self.assertListEqual(a__   ,				a__)

             _lowerCamelCase				:  Any						=		tokens + ['''<unk>''']
             _lowerCamelCase				:  Optional[int]						=		[14, 15, 20]
             self.assertListEqual(tokenizer.convert_tokens_to_ids(a__)   ,				a__)


      def 					__snake_case      (		self   ,				a__=15):



             """simple docstring"""





             for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                    with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""):
                           _lowerCamelCase				:  Dict						=		self.rust_tokenizer_class.from_pretrained(a__   ,				**a__)

                           # Simple input
                           _lowerCamelCase				:  Optional[int]						=		'''This is a simple input'''
                           _lowerCamelCase				:  Optional[Any]						=		['''This is a simple input 1''', '''This is a simple input 2''']
                           _lowerCamelCase				:  Optional[int]						=		('''This is a simple input''', '''This is a pair''')
                           _lowerCamelCase				:  List[Any]						=		[
                               ('''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(a__   ,				tokenizer_r.encode   ,				a__   ,				max_length=a__   ,				padding='''max_length''')

                           # Simple input
                           self.assertRaises(a__   ,				tokenizer_r.encode_plus   ,				a__   ,				max_length=a__   ,				padding='''max_length''')

                           # Simple input
                           self.assertRaises(
                               a__   ,				tokenizer_r.batch_encode_plus   ,				a__   ,				max_length=a__   ,				padding='''max_length'''   ,				)

                           # Pair input
                           self.assertRaises(a__   ,				tokenizer_r.encode   ,				a__   ,				max_length=a__   ,				padding='''max_length''')

                           # Pair input
                           self.assertRaises(a__   ,				tokenizer_r.encode_plus   ,				a__   ,				max_length=a__   ,				padding='''max_length''')

                           # Pair input
                           self.assertRaises(
                               a__   ,				tokenizer_r.batch_encode_plus   ,				a__   ,				max_length=a__   ,				padding='''max_length'''   ,				)



      def 					__snake_case      (		self):



             """simple docstring"""





             pass







@require_ftfy
@require_spacy
@require_tokenizers
class       __A							(   lowerCamelCase__	):




      """simple docstring"""







      pass

