


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        lowerCamelCase      (     unittest.TestCase   ):


	def    A(						self):
							__UpperCAmelCase :       List[str]  						=  tempfile.mkdtemp()

							# fmt: off
							__UpperCAmelCase :       Tuple  						=  ['''''', '''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
							__UpperCAmelCase :       Dict  						=  dict(zip(lowercase__							,    range(len(lowercase__))))
							__UpperCAmelCase :       Dict  						=  ['''#version: 0.2''', '''l o''', '''lo w</w>''', '''e r</w>''', '''''']
							__UpperCAmelCase :       Tuple  						=  {'''unk_token''': '''<unk>'''}

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

							__UpperCAmelCase :       List[str]  						=  {
							    '''do_resize''': True,
							    '''size''': 2_0,
							    '''do_center_crop''': True,
							    '''crop_size''': 1_8,
							    '''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],
							}
							__UpperCAmelCase :       Any  						=  os.path.join(self.tmpdirname							,    lowercase__)
							with open(self.image_processor_file							,    '''w'''							,    encoding='''utf-8''') as fp:
													json.dump(lowercase__							,    lowercase__)


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


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


	def    A(						self							,    **lowercase__):
							return OwlViTImageProcessor.from_pretrained(self.tmpdirname							,    **lowercase__)


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


	def    A(						self):
							__UpperCAmelCase :       str  						=  [np.random.randint(2_5_5							,    size=(3, 3_0, 4_0_0)							,    dtype=np.uinta)]

							__UpperCAmelCase :       Dict  						=  [Image.fromarray(np.moveaxis(lowercase__							,    0							,    -1)) for x in image_inputs]

							return image_inputs


	def    A(						self):
							__UpperCAmelCase :       Any  						=  self.get_tokenizer()
							__UpperCAmelCase :       Dict  						=  self.get_rust_tokenizer()
							__UpperCAmelCase :       str  						=  self.get_image_processor()

							__UpperCAmelCase :       Dict  						=  OwlViTProcessor(tokenizer=lowercase__							,    image_processor=lowercase__)
							processor_slow.save_pretrained(self.tmpdirname)
							__UpperCAmelCase :       Optional[int]  						=  OwlViTProcessor.from_pretrained(self.tmpdirname							,    use_fast=lowercase__)

							__UpperCAmelCase :       List[str]  						=  OwlViTProcessor(tokenizer=lowercase__							,    image_processor=lowercase__)
							processor_fast.save_pretrained(self.tmpdirname)
							__UpperCAmelCase :       Union[str, 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							,    lowercase__)
							self.assertIsInstance(processor_fast.tokenizer							,    lowercase__)

							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							,    lowercase__)
							self.assertIsInstance(processor_fast.image_processor							,    lowercase__)


	def    A(						self):
							__UpperCAmelCase :       Any  						=  OwlViTProcessor(tokenizer=self.get_tokenizer()							,    image_processor=self.get_image_processor())
							processor.save_pretrained(self.tmpdirname)

							__UpperCAmelCase :       Optional[Any]  						=  self.get_tokenizer(bos_token='''(BOS)'''							,    eos_token='''(EOS)''')
							__UpperCAmelCase :       Tuple  						=  self.get_image_processor(do_normalize=lowercase__)

							__UpperCAmelCase :       Optional[int]  						=  OwlViTProcessor.from_pretrained(
							    self.tmpdirname							,    bos_token='''(BOS)'''							,    eos_token='''(EOS)'''							,    do_normalize=lowercase__)

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

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


	def    A(						self):
							__UpperCAmelCase :       int  						=  self.get_image_processor()
							__UpperCAmelCase :       List[str]  						=  self.get_tokenizer()

							__UpperCAmelCase :       Dict  						=  OwlViTProcessor(tokenizer=lowercase__							,    image_processor=lowercase__)

							__UpperCAmelCase :       Tuple  						=  self.prepare_image_inputs()

							__UpperCAmelCase :       int  						=  image_processor(lowercase__							,    return_tensors='''np''')
							__UpperCAmelCase :       Tuple  						=  processor(images=lowercase__							,    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    A(						self):
							__UpperCAmelCase :       Union[str, Any]  						=  self.get_image_processor()
							__UpperCAmelCase :       List[Any]  						=  self.get_tokenizer()

							__UpperCAmelCase :       Any  						=  OwlViTProcessor(tokenizer=lowercase__							,    image_processor=lowercase__)

							__UpperCAmelCase :       List[str]  						=  '''lower newer'''

							__UpperCAmelCase :       Dict  						=  processor(text=lowercase__							,    return_tensors='''np''')

							__UpperCAmelCase :       Optional[int]  						=  tokenizer(lowercase__							,    return_tensors='''np''')

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


	def    A(						self):
							__UpperCAmelCase :       List[Any]  						=  self.get_image_processor()
							__UpperCAmelCase :       Dict  						=  self.get_tokenizer()

							__UpperCAmelCase :       List[Any]  						=  OwlViTProcessor(tokenizer=lowercase__							,    image_processor=lowercase__)

							__UpperCAmelCase :       Union[str, Any]  						=  '''lower newer'''
							__UpperCAmelCase :       Union[str, Any]  						=  self.prepare_image_inputs()

							__UpperCAmelCase :       Optional[Any]  						=  processor(text=lowercase__							,    images=lowercase__)

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

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


	def    A(						self):
							__UpperCAmelCase :       Tuple  						=  '''google/owlvit-base-patch32'''
							__UpperCAmelCase :       Tuple  						=  OwlViTProcessor.from_pretrained(lowercase__)

							__UpperCAmelCase :       Dict  						=  ['''cat''', '''nasa badge''']
							__UpperCAmelCase :       List[Any]  						=  processor(text=lowercase__)

							__UpperCAmelCase :       Any  						=  1_6
							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(lowercase__):
													processor()


	def    A(						self):
							__UpperCAmelCase :       List[str]  						=  '''google/owlvit-base-patch32'''
							__UpperCAmelCase :       Optional[Any]  						=  OwlViTProcessor.from_pretrained(lowercase__)

							__UpperCAmelCase :       Optional[int]  						=  [['''cat''', '''nasa badge'''], ['''person''']]
							__UpperCAmelCase :       Any  						=  processor(text=lowercase__)

							__UpperCAmelCase :       int  						=  1_6
							__UpperCAmelCase :       int  						=  len(lowercase__)
							__UpperCAmelCase :       int  						=  max([len(lowercase__) 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(lowercase__):
													processor()


	def    A(						self):
							__UpperCAmelCase :       List[Any]  						=  '''google/owlvit-base-patch32'''
							__UpperCAmelCase :       Tuple  						=  OwlViTProcessor.from_pretrained(lowercase__)

							__UpperCAmelCase :       Optional[int]  						=  ['''cat''', '''nasa badge''']
							__UpperCAmelCase :       List[Any]  						=  processor(text=lowercase__)

							__UpperCAmelCase :       Optional[int]  						=  1_6
							__UpperCAmelCase :       Optional[Any]  						=  inputs['''input_ids''']
							__UpperCAmelCase :       str  						=  [
							    [4_9_4_0_6, 2_3_6_8, 4_9_4_0_7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
							    [4_9_4_0_6, 6_8_4_1, 1_1_3_0_1, 4_9_4_0_7, 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    A(						self):
							__UpperCAmelCase :       Tuple  						=  self.get_image_processor()
							__UpperCAmelCase :       Union[str, Any]  						=  self.get_tokenizer()

							__UpperCAmelCase :       Optional[int]  						=  OwlViTProcessor(tokenizer=lowercase__							,    image_processor=lowercase__)

							__UpperCAmelCase :       str  						=  self.prepare_image_inputs()
							__UpperCAmelCase :       Dict  						=  self.prepare_image_inputs()

							__UpperCAmelCase :       int  						=  processor(images=lowercase__							,    query_images=lowercase__)

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

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


	def    A(						self):
							__UpperCAmelCase :       Tuple  						=  self.get_image_processor()
							__UpperCAmelCase :       int  						=  self.get_tokenizer()

							__UpperCAmelCase :       List[Any]  						=  OwlViTProcessor(tokenizer=lowercase__							,    image_processor=lowercase__)

							__UpperCAmelCase :       Dict  						=  [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

							__UpperCAmelCase :       int  						=  processor.batch_decode(lowercase__)
							__UpperCAmelCase :       Union[str, Any]  						=  tokenizer.batch_decode(lowercase__)

							self.assertListEqual(lowercase__							,    lowercase__)





def 						__SCREAMING_SNAKE_CASE       (					)		->    list[list[int]]:




						'''simple docstring'''







						return [list(range(1000 - i			,					-1000 - i			,					-1			)			) for i in range(1000			)]


lowerCAmelCase							=						generate_large_matrix()
lowerCAmelCase							=						(
    [[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]],
    [[3, 2], [1, 0]],
    [[7, 7, 6]],
    [[7, 7, 6], [-1, -2, -3]],
    grid,
)




def 						__SCREAMING_SNAKE_CASE       (					lowercase_			)		->    None:




						'''simple docstring'''







						assert all(row == sorted(lowercase_			,					reverse=lowercase_			) for row in grid			)
						assert all(list(lowercase_			) == sorted(lowercase_			,					reverse=lowercase_			) for col in zip(*lowercase_			)			)




def 						__SCREAMING_SNAKE_CASE       (					lowercase_			)		->    int:




						'''simple docstring'''







						__UpperCAmelCase :       Dict  						=  0
						__UpperCAmelCase :       List[Any]  						=  len(lowercase_			) - 1

						# Edge cases such as no values or all numbers are negative.
						if not array or array[0] < 0:
												return 0

						while right + 1 > left:
												__UpperCAmelCase :       List[Any]  						=  (left + right) // 2
												__UpperCAmelCase :       Dict  						=  array[mid]

												# Num must be negative and the index must be greater than or equal to 0.
												if num < 0 and array[mid - 1] >= 0:
																		return mid

												if num >= 0:
																		__UpperCAmelCase :       Dict  						=  mid + 1
												else:
																		__UpperCAmelCase :       Optional[Any]  						=  mid - 1
    # No negative numbers so return the last index of the array + 1 which is the length.
						return len(lowercase_			)




def 						__SCREAMING_SNAKE_CASE       (					lowercase_			)		->    int:




						'''simple docstring'''







						__UpperCAmelCase :       int  						=  0
						__UpperCAmelCase :       Dict  						=  len(grid[0]			)

						for i in range(len(lowercase_			)			):
												__UpperCAmelCase :       Any  						=  find_negative_index(grid[i][:bound]			)
												total += bound
						return (len(lowercase_			) * len(grid[0]			)) - total




def 						__SCREAMING_SNAKE_CASE       (					lowercase_			)		->    int:




						'''simple docstring'''







						return len([number for row in grid for number in row if number < 0]			)




def 						__SCREAMING_SNAKE_CASE       (					lowercase_			)		->    int:




						'''simple docstring'''







						__UpperCAmelCase :       List[Any]  						=  0
						for row in grid:
												for i, number in enumerate(lowercase_			):
																		if number < 0:
																								total += len(lowercase_			) - i
																								break
						return total




def 						__SCREAMING_SNAKE_CASE       (					)		->    None:




						'''simple docstring'''







						from timeit import timeit

						print('''Running benchmarks'''			)
						__UpperCAmelCase :       Tuple  						=  (
						    '''from __main__ import count_negatives_binary_search, '''
						    '''count_negatives_brute_force, count_negatives_brute_force_with_break, grid'''
						)
						for func in (
						    "count_negatives_binary_search",  # took 0.7727 seconds
						    "count_negatives_brute_force_with_break",  # took 4.6505 seconds
						    "count_negatives_brute_force",  # took 12.8160 seconds
						):
												__UpperCAmelCase :       Union[str, Any]  						=  timeit(f"{func}(grid=grid)"			,					setup=lowercase_			,					number=500			)
												print(f"{func}() took {time:0.4f} seconds"			)


if __name__ == "__main__":
				import doctest

				doctest.testmod()
				benchmark()

