
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     lowercase		( unittest.TestCase		):




							def 			A__				(    self):
												lowercase						     =						tempfile.mkdtemp()

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

												lowercase						     =						os.path.join(self.tmpdirname       ,VOCAB_FILES_NAMES['''vocab_file'''])
												lowercase						     =						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__))

												lowercase						     =						{
												    '''do_resize''': True,
												    '''size''': 2_0,
												    '''do_center_crop''': True,
												    '''crop_size''': 1_8,
												    '''do_normalize''': True,
												    '''image_mean''': [0.48145466, 0.4578275, 0.40821073],
												    '''image_std''': [0.26862954, 0.26130258, 0.27577711],
												}
												lowercase						     =						os.path.join(self.tmpdirname       ,A__)
												with open(self.image_processor_file       ,'''w'''       ,encoding='''utf-8''') as fp:
																	json.dump(A__       ,A__)




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




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




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




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




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

												lowercase						     =						[Image.fromarray(np.moveaxis(A__       ,0       ,-1)) for x in image_inputs]

												return image_inputs




							def 			A__				(    self):
												lowercase						     =						self.get_tokenizer()
												lowercase						     =						self.get_rust_tokenizer()
												lowercase						     =						self.get_image_processor()

												lowercase						     =						OwlViTProcessor(tokenizer=A__       ,image_processor=A__)
												processor_slow.save_pretrained(self.tmpdirname)
												lowercase						     =						OwlViTProcessor.from_pretrained(self.tmpdirname       ,use_fast=A__)

												lowercase						     =						OwlViTProcessor(tokenizer=A__       ,image_processor=A__)
												processor_fast.save_pretrained(self.tmpdirname)
												lowercase						     =						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 			A__				(    self):
												lowercase						     =						OwlViTProcessor(tokenizer=self.get_tokenizer()       ,image_processor=self.get_image_processor())
												processor.save_pretrained(self.tmpdirname)

												lowercase						     =						self.get_tokenizer(bos_token='''(BOS)'''       ,eos_token='''(EOS)''')
												lowercase						     =						self.get_image_processor(do_normalize=A__)

												lowercase						     =						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 			A__				(    self):
												lowercase						     =						self.get_image_processor()
												lowercase						     =						self.get_tokenizer()

												lowercase						     =						OwlViTProcessor(tokenizer=A__       ,image_processor=A__)

												lowercase						     =						self.prepare_image_inputs()

												lowercase						     =						image_processor(A__       ,return_tensors='''np''')
												lowercase						     =						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 			A__				(    self):
												lowercase						     =						self.get_image_processor()
												lowercase						     =						self.get_tokenizer()

												lowercase						     =						OwlViTProcessor(tokenizer=A__       ,image_processor=A__)

												lowercase						     =						'''lower newer'''

												lowercase						     =						processor(text=A__       ,return_tensors='''np''')

												lowercase						     =						tokenizer(A__       ,return_tensors='''np''')

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




							def 			A__				(    self):
												lowercase						     =						self.get_image_processor()
												lowercase						     =						self.get_tokenizer()

												lowercase						     =						OwlViTProcessor(tokenizer=A__       ,image_processor=A__)

												lowercase						     =						'''lower newer'''
												lowercase						     =						self.prepare_image_inputs()

												lowercase						     =						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 			A__				(    self):
												lowercase						     =						'''google/owlvit-base-patch32'''
												lowercase						     =						OwlViTProcessor.from_pretrained(A__)

												lowercase						     =						['''cat''', '''nasa badge''']
												lowercase						     =						processor(text=A__)

												lowercase						     =						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(A__):
																	processor()




							def 			A__				(    self):
												lowercase						     =						'''google/owlvit-base-patch32'''
												lowercase						     =						OwlViTProcessor.from_pretrained(A__)

												lowercase						     =						[['''cat''', '''nasa badge'''], ['''person''']]
												lowercase						     =						processor(text=A__)

												lowercase						     =						1_6
												lowercase						     =						len(A__)
												lowercase						     =						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 			A__				(    self):
												lowercase						     =						'''google/owlvit-base-patch32'''
												lowercase						     =						OwlViTProcessor.from_pretrained(A__)

												lowercase						     =						['''cat''', '''nasa badge''']
												lowercase						     =						processor(text=A__)

												lowercase						     =						1_6
												lowercase						     =						inputs['''input_ids''']
												lowercase						     =						[
												    [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):
												lowercase						     =						self.get_image_processor()
												lowercase						     =						self.get_tokenizer()

												lowercase						     =						OwlViTProcessor(tokenizer=A__       ,image_processor=A__)

												lowercase						     =						self.prepare_image_inputs()
												lowercase						     =						self.prepare_image_inputs()

												lowercase						     =						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 			A__				(    self):
												lowercase						     =						self.get_image_processor()
												lowercase						     =						self.get_tokenizer()

												lowercase						     =						OwlViTProcessor(tokenizer=A__       ,image_processor=A__)

												lowercase						     =						[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

												lowercase						     =						processor.batch_decode(A__)
												lowercase						     =						tokenizer.batch_decode(A__)

												self.assertListEqual(A__       ,A__)






from __future__ import annotations

from decimal import Decimal

from numpy import array



def 	UpperCamelCase   (							lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						Decimal

					# Check if the provided matrix has 2 rows and 2 columns
					# since this implementation only works for 2x2 matrices
					if len(lowerCAmelCase__		) == 2 and len(matrix[0]		) == 2 and len(matrix[1]		) == 2:
										# Calculate the determinant of the matrix
										lowercase						     =						float(
										    d(matrix[0][0]		) * d(matrix[1][1]		) - d(matrix[1][0]		) * d(matrix[0][1]		)		)
										if determinant == 0:
															raise ValueError('''This matrix has no inverse.'''		)

										# Creates a copy of the matrix with swapped positions of the elements
										lowercase						     =						[[0.0, 0.0], [0.0, 0.0]]
										lowercase     ,						lowercase						     =						matrix[1][1], matrix[0][0]
										lowercase     ,						lowercase						     =						-matrix[1][0], -matrix[0][1]

										# Calculate the inverse of the matrix
										return [
										    [(float(d(lowerCAmelCase__		)		) / determinant) or 0.0 for n in row] for row in swapped_matrix
										]
					elif (
					    len(lowerCAmelCase__		) == 3
					    and len(matrix[0]		) == 3
					    and len(matrix[1]		) == 3
					    and len(matrix[2]		) == 3
					):
										# Calculate the determinant of the matrix using Sarrus rule
										lowercase						     =						float(
										    (
										        (d(matrix[0][0]		) * d(matrix[1][1]		) * d(matrix[2][2]		))
										        + (d(matrix[0][1]		) * d(matrix[1][2]		) * d(matrix[2][0]		))
										        + (d(matrix[0][2]		) * d(matrix[1][0]		) * d(matrix[2][1]		))
										    )
										    - (
										        (d(matrix[0][2]		) * d(matrix[1][1]		) * d(matrix[2][0]		))
										        + (d(matrix[0][1]		) * d(matrix[1][0]		) * d(matrix[2][2]		))
										        + (d(matrix[0][0]		) * d(matrix[1][2]		) * d(matrix[2][1]		))
										    )		)
										if determinant == 0:
															raise ValueError('''This matrix has no inverse.'''		)

										# Creating cofactor matrix
										lowercase						     =						[
										    [d(0.0		), d(0.0		), d(0.0		)],
										    [d(0.0		), d(0.0		), d(0.0		)],
										    [d(0.0		), d(0.0		), d(0.0		)],
										]
										lowercase						     =						(d(matrix[1][1]		) * d(matrix[2][2]		)) - (
										    d(matrix[1][2]		) * d(matrix[2][1]		)
										)
										lowercase						     =						-(
										    (d(matrix[1][0]		) * d(matrix[2][2]		)) - (d(matrix[1][2]		) * d(matrix[2][0]		))
										)
										lowercase						     =						(d(matrix[1][0]		) * d(matrix[2][1]		)) - (
										    d(matrix[1][1]		) * d(matrix[2][0]		)
										)
										lowercase						     =						-(
										    (d(matrix[0][1]		) * d(matrix[2][2]		)) - (d(matrix[0][2]		) * d(matrix[2][1]		))
										)
										lowercase						     =						(d(matrix[0][0]		) * d(matrix[2][2]		)) - (
										    d(matrix[0][2]		) * d(matrix[2][0]		)
										)
										lowercase						     =						-(
										    (d(matrix[0][0]		) * d(matrix[2][1]		)) - (d(matrix[0][1]		) * d(matrix[2][0]		))
										)
										lowercase						     =						(d(matrix[0][1]		) * d(matrix[1][2]		)) - (
										    d(matrix[0][2]		) * d(matrix[1][1]		)
										)
										lowercase						     =						-(
										    (d(matrix[0][0]		) * d(matrix[1][2]		)) - (d(matrix[0][2]		) * d(matrix[1][0]		))
										)
										lowercase						     =						(d(matrix[0][0]		) * d(matrix[1][1]		)) - (
										    d(matrix[0][1]		) * d(matrix[1][0]		)
										)

										# Transpose the cofactor matrix (Adjoint matrix)
										lowercase						     =						array(lowerCAmelCase__		)
										for i in range(3		):
															for j in range(3		):
																				lowercase						     =						cofactor_matrix[j][i]

        # Inverse of the matrix using the formula (1/determinant) * adjoint matrix
										lowercase						     =						array(lowerCAmelCase__		)
										for i in range(3		):
															for j in range(3		):
																				inverse_matrix[i][j] /= d(lowerCAmelCase__		)

        # Calculate the inverse of the matrix
										return [[float(d(lowerCAmelCase__		)		) or 0.0 for n in row] for row in inverse_matrix]
					raise ValueError('''Please provide a matrix of size 2x2 or 3x3.'''		)




