





from __future__ import annotations







def  _SCREAMING_SNAKE_CASE				(   a					,						a  )      ->      list[tuple[int, int]]:
					__A    ,				__A	:						Optional[Any]       =				position
					__A	:						Union[str, Any]       =				[
					    (y + 1, x + 2),
					    (y - 1, x + 2),
					    (y + 1, x - 2),
					    (y - 1, x - 2),
					    (y + 2, x + 1),
					    (y + 2, x - 1),
					    (y - 2, x + 1),
					    (y - 2, x - 1),
					]
					__A	:						int       =				[]

					for position in positions:
										__A    ,				__A	:						Tuple       =				position
										if 0 <= y_test < n and 0 <= x_test < n:
															permissible_positions.append(a  )

					return permissible_positions







def  _SCREAMING_SNAKE_CASE				(   a  )      ->      bool:
					return not any(elem == 0 for row in board for elem in row  )







def  _SCREAMING_SNAKE_CASE				(   a					,						a					,						a  )      ->      bool:

					if is_complete(a  ):
										return True

					for position in get_valid_pos(a					,						len(a  )  ):
										__A    ,				__A	:						Any       =				position

										if board[y][x] == 0:
															__A	:						List[str]       =				curr + 1
															if open_knight_tour_helper(a					,						a					,						curr + 1  ):
																				return True
															__A	:						Optional[Any]       =				0

					return False







def  _SCREAMING_SNAKE_CASE				(   a  )      ->      list[list[int]]:
					__A	:						Optional[int]       =				[[0 for i in range(a  )] for j in range(a  )]

					for i in range(a  ):
										for j in range(a  ):
															__A	:						Optional[Any]       =				1
															if open_knight_tour_helper(a					,						(i, j)					,						1  ):
																				return board
															__A	:						Any       =				0

					__A	:						List[str]       =				F"""Open Kight Tour cannot be performed on a board of size {n}"""
					raise ValueError(a  )


if __name__ == "__main__":
				import doctest

				doctest.testmod()











import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
				from PIL import Image

				from transformers import OwlViTImageProcessor, OwlViTProcessor





@require_vision
class 						_A(					unittest.TestCase   ):


				"""simple docstring"""


				def 					UpperCAmelCase_		(			self     ):
									__A	:						List[Any]       =				tempfile.mkdtemp()

									# fmt: off
									__A	:						List[str]       =				['', '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
									__A	:						Union[str, Any]       =				dict(zip(_A     ,					range(len(_A     )     )     )     )
									__A	:						Optional[int]       =				['#version: 0.2', 'l o', 'lo w</w>', 'e r</w>', '']
									__A	:						int       =				{'unk_token': '<unk>'}

									__A	:						Optional[int]       =				os.path.join(self.tmpdirname     ,					VOCAB_FILES_NAMES['vocab_file']     )
									__A	:						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(_A     ) + '\n'     )
									with open(self.merges_file     ,					'w'     ,					encoding='utf-8'     ) as fp:
														fp.write('\n'.join(_A     )     )

									__A	:						List[Any]       =				{
									    'do_resize': True,
									    'size': 20,
									    'do_center_crop': True,
									    'crop_size': 18,
									    'do_normalize': True,
									    'image_mean': [0.4_8_1_4_5_4_6_6, 0.4_5_7_8_2_7_5, 0.4_0_8_2_1_0_7_3],
									    'image_std': [0.2_6_8_6_2_9_5_4, 0.2_6_1_3_0_2_5_8, 0.2_7_5_7_7_7_1_1],
									}
									__A	:						Optional[int]       =				os.path.join(self.tmpdirname     ,					_A     )
									with open(self.image_processor_file     ,					'w'     ,					encoding='utf-8'     ) as fp:
														json.dump(_A     ,					_A     )



				def 					UpperCAmelCase_		(			self     ,					**_A     ):
									return CLIPTokenizer.from_pretrained(self.tmpdirname     ,					pad_token='!'     ,					**_A     )



				def 					UpperCAmelCase_		(			self     ,					**_A     ):
									return CLIPTokenizerFast.from_pretrained(self.tmpdirname     ,					pad_token='!'     ,					**_A     )



				def 					UpperCAmelCase_		(			self     ,					**_A     ):
									return OwlViTImageProcessor.from_pretrained(self.tmpdirname     ,					**_A     )



				def 					UpperCAmelCase_		(			self     ):
									shutil.rmtree(self.tmpdirname     )



				def 					UpperCAmelCase_		(			self     ):
									__A	:						int       =				[np.random.randint(255     ,					size=(3, 30, 400)     ,					dtype=np.uinta     )]

									__A	:						Optional[int]       =				[Image.fromarray(np.moveaxis(_A     ,					0     ,					-1     )     ) for x in image_inputs]

									return image_inputs



				def 					UpperCAmelCase_		(			self     ):
									__A	:						List[Any]       =				self.get_tokenizer()
									__A	:						str       =				self.get_rust_tokenizer()
									__A	:						List[str]       =				self.get_image_processor()

									__A	:						Optional[int]       =				OwlViTProcessor(tokenizer=_A     ,					image_processor=_A     )
									processor_slow.save_pretrained(self.tmpdirname     )
									__A	:						int       =				OwlViTProcessor.from_pretrained(self.tmpdirname     ,					use_fast=_A     )

									__A	:						Optional[Any]       =				OwlViTProcessor(tokenizer=_A     ,					image_processor=_A     )
									processor_fast.save_pretrained(self.tmpdirname     )
									__A	:						Optional[Any]       =				OwlViTProcessor.from_pretrained(self.tmpdirname     )

									self.assertEqual(processor_slow.tokenizer.get_vocab()     ,					tokenizer_slow.get_vocab()     )
									self.assertEqual(processor_fast.tokenizer.get_vocab()     ,					tokenizer_fast.get_vocab()     )
									self.assertEqual(tokenizer_slow.get_vocab()     ,					tokenizer_fast.get_vocab()     )
									self.assertIsInstance(processor_slow.tokenizer     ,					_A     )
									self.assertIsInstance(processor_fast.tokenizer     ,					_A     )

									self.assertEqual(processor_slow.image_processor.to_json_string()     ,					image_processor.to_json_string()     )
									self.assertEqual(processor_fast.image_processor.to_json_string()     ,					image_processor.to_json_string()     )
									self.assertIsInstance(processor_slow.image_processor     ,					_A     )
									self.assertIsInstance(processor_fast.image_processor     ,					_A     )



				def 					UpperCAmelCase_		(			self     ):
									__A	:						List[str]       =				OwlViTProcessor(tokenizer=self.get_tokenizer()     ,					image_processor=self.get_image_processor()     )
									processor.save_pretrained(self.tmpdirname     )

									__A	:						Optional[int]       =				self.get_tokenizer(bos_token='(BOS)'     ,					eos_token='(EOS)'     )
									__A	:						Optional[int]       =				self.get_image_processor(do_normalize=_A     )

									__A	:						Any       =				OwlViTProcessor.from_pretrained(
									    self.tmpdirname     ,					bos_token='(BOS)'     ,					eos_token='(EOS)'     ,					do_normalize=_A     )

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

									self.assertEqual(processor.image_processor.to_json_string()     ,					image_processor_add_kwargs.to_json_string()     )
									self.assertIsInstance(processor.image_processor     ,					_A     )



				def 					UpperCAmelCase_		(			self     ):
									__A	:						Optional[Any]       =				self.get_image_processor()
									__A	:						Optional[Any]       =				self.get_tokenizer()

									__A	:						Union[str, Any]       =				OwlViTProcessor(tokenizer=_A     ,					image_processor=_A     )

									__A	:						Union[str, Any]       =				self.prepare_image_inputs()

									__A	:						int       =				image_processor(_A     ,					return_tensors='np'     )
									__A	:						str       =				processor(images=_A     ,					return_tensors='np'     )

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



				def 					UpperCAmelCase_		(			self     ):
									__A	:						str       =				self.get_image_processor()
									__A	:						str       =				self.get_tokenizer()

									__A	:						Tuple       =				OwlViTProcessor(tokenizer=_A     ,					image_processor=_A     )

									__A	:						str       =				'lower newer'

									__A	:						str       =				processor(text=_A     ,					return_tensors='np'     )

									__A	:						List[str]       =				tokenizer(_A     ,					return_tensors='np'     )

									for key in encoded_tok.keys():
														self.assertListEqual(encoded_tok[key][0].tolist()     ,					encoded_processor[key][0].tolist()     )



				def 					UpperCAmelCase_		(			self     ):
									__A	:						int       =				self.get_image_processor()
									__A	:						Optional[int]       =				self.get_tokenizer()

									__A	:						List[str]       =				OwlViTProcessor(tokenizer=_A     ,					image_processor=_A     )

									__A	:						Any       =				'lower newer'
									__A	:						Optional[Any]       =				self.prepare_image_inputs()

									__A	:						List[Any]       =				processor(text=_A     ,					images=_A     )

									self.assertListEqual(list(inputs.keys()     )     ,					['input_ids', 'attention_mask', 'pixel_values']     )

									# test if it raises when no input is passed
									with pytest.raises(_A     ):
														processor()



				def 					UpperCAmelCase_		(			self     ):
									__A	:						Any       =				'google/owlvit-base-patch32'
									__A	:						int       =				OwlViTProcessor.from_pretrained(_A     )

									__A	:						Dict       =				['cat', 'nasa badge']
									__A	:						Optional[Any]       =				processor(text=_A     )

									__A	:						Optional[int]       =				16
									self.assertListEqual(list(inputs.keys()     )     ,					['input_ids', 'attention_mask']     )
									self.assertEqual(inputs['input_ids'].shape     ,					(2, seq_length)     )

									# test if it raises when no input is passed
									with pytest.raises(_A     ):
														processor()



				def 					UpperCAmelCase_		(			self     ):
									__A	:						Tuple       =				'google/owlvit-base-patch32'
									__A	:						Any       =				OwlViTProcessor.from_pretrained(_A     )

									__A	:						Dict       =				[['cat', 'nasa badge'], ['person']]
									__A	:						Dict       =				processor(text=_A     )

									__A	:						Optional[int]       =				16
									__A	:						Any       =				len(_A     )
									__A	:						Union[str, Any]       =				max([len(_A     ) for texts in input_texts]     )

									self.assertListEqual(list(inputs.keys()     )     ,					['input_ids', 'attention_mask']     )
									self.assertEqual(inputs['input_ids'].shape     ,					(batch_size * num_max_text_queries, seq_length)     )

									# test if it raises when no input is passed
									with pytest.raises(_A     ):
														processor()



				def 					UpperCAmelCase_		(			self     ):
									__A	:						List[Any]       =				'google/owlvit-base-patch32'
									__A	:						str       =				OwlViTProcessor.from_pretrained(_A     )

									__A	:						Union[str, Any]       =				['cat', 'nasa badge']
									__A	:						Tuple       =				processor(text=_A     )

									__A	:						str       =				16
									__A	:						int       =				inputs['input_ids']
									__A	:						List[Any]       =				[
									    [49406, 2368, 49407, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
									    [49406, 6841, 11301, 49407, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
									]

									self.assertListEqual(list(inputs.keys()     )     ,					['input_ids', 'attention_mask']     )
									self.assertEqual(inputs['input_ids'].shape     ,					(2, seq_length)     )
									self.assertListEqual(list(input_ids[0]     )     ,					predicted_ids[0]     )
									self.assertListEqual(list(input_ids[1]     )     ,					predicted_ids[1]     )



				def 					UpperCAmelCase_		(			self     ):
									__A	:						Optional[Any]       =				self.get_image_processor()
									__A	:						List[str]       =				self.get_tokenizer()

									__A	:						Optional[Any]       =				OwlViTProcessor(tokenizer=_A     ,					image_processor=_A     )

									__A	:						Optional[int]       =				self.prepare_image_inputs()
									__A	:						Optional[int]       =				self.prepare_image_inputs()

									__A	:						Optional[int]       =				processor(images=_A     ,					query_images=_A     )

									self.assertListEqual(list(inputs.keys()     )     ,					['query_pixel_values', 'pixel_values']     )

									# test if it raises when no input is passed
									with pytest.raises(_A     ):
														processor()





				def 					UpperCAmelCase_		(			self     ):
									__A	:						Optional[Any]       =				self.get_image_processor()
									__A	:						Union[str, Any]       =				self.get_tokenizer()

									__A	:						str       =				OwlViTProcessor(tokenizer=_A     ,					image_processor=_A     )

									__A	:						Optional[Any]       =				[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

									__A	:						Any       =				processor.batch_decode(_A     )
									__A	:						Tuple       =				tokenizer.batch_decode(_A     )

									self.assertListEqual(_A     ,					_A     )




