"""simple docstring"""







import json
import os
import unittest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
class  _lowerCamelCase			(__lowerCamelCase						,							unittest.TestCase     ):
				_snake_case     =  CLIPTokenizer
				_snake_case     =  CLIPTokenizerFast
				_snake_case     =  True
				_snake_case     =  {}
				_snake_case     =  False







				def 							__UpperCAmelCase					( self    :       Optional[Any]						):

					"""simple docstring"""






					super().setUp()

					# fmt: off
					_lowercase :    Union[str, Any]							=							['l', 'o', 'w', 'e', 'r', 's', 't', 'i', 'd', 'n', 'lo', 'l</w>', 'w</w>', 'r</w>', 't</w>', 'low</w>', 'er</w>', 'lowest</w>', 'newer</w>', 'wider', '<unk>', '<|startoftext|>', '<|endoftext|>']
					# fmt: on
					_lowercase :    Dict							=							dict(zip(lowerCamelCase_			,					range(len(lowerCamelCase_						)						)						)						)
					_lowercase :    str							=							['#version: 0.2', 'l o', 'lo w</w>', 'e r</w>']
					_lowercase :    Union[str, Any]							=							{'unk_token': '<unk>'}

					_lowercase :    Optional[int]							=							os.path.join(self.tmpdirname			,					VOCAB_FILES_NAMES['vocab_file']						)
					_lowercase :    int							=							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 							__UpperCAmelCase					( self    :       str			,					**lowerCamelCase_    :       List[str]						):

					"""simple docstring"""






					kwargs.update(self.special_tokens_map						)
					return CLIPTokenizer.from_pretrained(self.tmpdirname			,					**lowerCamelCase_						)







				def 							__UpperCAmelCase					( self    :       Optional[int]			,					**lowerCamelCase_    :       Optional[int]						):

					"""simple docstring"""






					kwargs.update(self.special_tokens_map						)
					return CLIPTokenizerFast.from_pretrained(self.tmpdirname			,					**lowerCamelCase_						)







				def 							__UpperCAmelCase					( self    :       Union[str, Any]			,					lowerCamelCase_    :       List[str]						):

					"""simple docstring"""






					_lowercase :    List[str]							=							'lower newer'
					_lowercase :    Any							=							'lower newer'
					return input_text, output_text







				def 							__UpperCAmelCase					( self    :       Tuple						):

					"""simple docstring"""






					_lowercase :    Optional[int]							=							CLIPTokenizer(self.vocab_file			,					self.merges_file			,					**self.special_tokens_map						)
					_lowercase :    Tuple							=							'lower newer'
					_lowercase :    Optional[int]							=							['lo', 'w', 'er</w>', 'n', 'e', 'w', 'er</w>']
					_lowercase :    List[Any]							=							tokenizer.tokenize(lowerCamelCase_						)
					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)

					_lowercase :    List[str]							=							tokens + [tokenizer.unk_token]
					_lowercase :    str							=							[1_0, 2, 1_6, 9, 3, 2, 1_6, 2_0]
					self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCamelCase_						)			,					lowerCamelCase_						)







				@require_ftfy
				def 							__UpperCAmelCase					( self    :       str						):

					"""simple docstring"""






					for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
						with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''						):
							_lowercase :    int							=							self.tokenizer_class.from_pretrained(lowerCamelCase_			,					**lowerCamelCase_						)
							_lowercase :    List[Any]							=							self.rust_tokenizer_class.from_pretrained(lowerCamelCase_			,					**lowerCamelCase_						)

							_lowercase :    Dict							=							'A\n\'ll 11p223RF☆ho!!to?\'d\'d\'\'d of a cat to-$\'\'d.'
							_lowercase :    List[Any]							=							tokenizer_s.tokenize(lowerCamelCase_						)
							_lowercase :    List[Any]							=							tokenizer_r.tokenize(lowerCamelCase_						)

							self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)

							# Test that the tokenization is identical on an example containing a character (Latin Small Letter A
							# with Tilde) encoded in 2 different ways
							_lowercase :    Tuple							=							'xa\u0303y' + ' ' + 'x\xe3y'
							_lowercase :    Union[str, Any]							=							tokenizer_s.tokenize(lowerCamelCase_						)
							_lowercase :    Optional[int]							=							tokenizer_r.tokenize(lowerCamelCase_						)

							self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)

							# Test that the tokenization is identical on unicode of space type
							_lowercase :    str							=							[
							    '\u0009',  # (horizontal tab, '\t')
							    '\u000B',  # (vertical tab)
							    '\u000C',  # (form feed)
							    '\u0020',  # (space, ' ')
							    '\u200E',  # (left-to-right mark):w
							    '\u200F',  # (right-to-left mark)
							]
							for unicode_seq in spaces_unicodes:
								_lowercase :    Union[str, Any]							=							tokenizer_s.tokenize(lowerCamelCase_						)
								_lowercase :    Optional[Any]							=							tokenizer_r.tokenize(lowerCamelCase_						)

								self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)

							# Test that the tokenization is identical on unicode of line break type
							_lowercase :    str							=							[
							    '\u000A',  # (line feed, '\n')
							    '\r\n',  # (carriage return and line feed, '\r\n')
							    '\u000D',  # (carriage return, '\r')
							    '\r',  # (carriage return, '\r')
							    '\u000D',  # (carriage return, '\r')
							    '\u2028',  # (line separator)
							    '\u2029',  # (paragraph separator)
							    # "\u0085", # (next line)
							]

							# The tokenization is not identical for the character "\u0085" (next line). The slow version using ftfy transforms
							# it into the Horizontal Ellipsis character "…" ("\u2026") while the fast version transforms it into a
							# space (and thus into an empty list).

							for unicode_seq in line_break_unicodes:
								_lowercase :    Union[str, Any]							=							tokenizer_s.tokenize(lowerCamelCase_						)
								_lowercase :    Tuple							=							tokenizer_r.tokenize(lowerCamelCase_						)

								self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)







				def 							__UpperCAmelCase					( self    :       Tuple						):

					"""simple docstring"""






					for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
						with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''						):
							_lowercase :    List[Any]							=							'hello'  # `hello` is a token in the vocabulary of `pretrained_name`
							_lowercase :    Union[str, Any]							=							F'''{text_of_1_token} {text_of_1_token}'''

							_lowercase :    Any							=							self.rust_tokenizer_class.from_pretrained(
							    lowerCamelCase_			,					use_fast=lowerCamelCase_			,					)
							_lowercase :    Tuple							=							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_						))			,					)

							_lowercase :    Dict							=							F''' {text}'''

							_lowercase :    Optional[int]							=							self.rust_tokenizer_class.from_pretrained(
							    lowerCamelCase_			,					use_fast=lowerCamelCase_			,					)
							_lowercase :    Optional[Any]							=							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_						))			,					)







				def 							__UpperCAmelCase					( self    :       List[str]						):

					"""simple docstring"""






					with self.assertRaises(lowerCamelCase_						) as context:
						self.rust_tokenizer_class.from_pretrained('robot-test/old-clip-tokenizer'						)

					self.assertTrue(
					    context.exception.args[0].startswith(
					        'The `backend_tokenizer` provided does not match the expected format.'						)						)







				@require_ftfy
				def 							__UpperCAmelCase					( self    :       Dict						):

					"""simple docstring"""






					super().test_tokenization_python_rust_equals()







				def 							__UpperCAmelCase					( self    :       str						):

					"""simple docstring"""






					pass




"""simple docstring"""







from __future__ import annotations

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


def      __lowerCAmelCase(		__UpperCAmelCase     ,__UpperCAmelCase     ,__UpperCAmelCase     ,__UpperCAmelCase     ,__UpperCAmelCase     ,):






	"""simple docstring"""





	_lowercase :    List[str]							=							[
	    [0 for col in range(len(grid[0]			)			)] for row in range(len(__UpperCAmelCase			)			)
	]  # the reference grid
	_lowercase :    Optional[Any]							=							1
	_lowercase :    Any							=							[
	    [0 for col in range(len(grid[0]			)			)] for row in range(len(__UpperCAmelCase			)			)
	]  # the action grid

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

	_lowercase :    Tuple							=							False  # flag that is set when search is complete
	_lowercase :    Tuple							=							False  # flag set if we can't find expand

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

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

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


if __name__ == "__main__":
						SCREAMING_SNAKE_CASE									=						[
						    [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],
						]

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

						# the cost map which pushes the path closer to the goal
						SCREAMING_SNAKE_CASE									=						[[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])):
																		SCREAMING_SNAKE_CASE									=						abs(i - goal[0]) + abs(j - goal[1])
																		if grid[i][j] == 1:
																								# added extra penalty in the heuristic map
																								SCREAMING_SNAKE_CASE									=						99

						SCREAMING_SNAKE_CASE							,    SCREAMING_SNAKE_CASE									=						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])



