



'''simple docstring'''
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      UpperCamelCase_  (			self :    Union[str, Any]			):







							'''simple docstring'''
							_UpperCamelCase :		str			    =       tempfile.mkdtemp()

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

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

							_UpperCamelCase :		int			    =       {
							    '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],
							}
							_UpperCamelCase :		Optional[int]			    =       os.path.join(self.tmpdirname			,lowerCamelCase__			)
							with open(self.image_processor_file			,'w'			,encoding='utf-8'			) as fp:
													json.dump(lowerCamelCase__			,lowerCamelCase__			)





	def      UpperCamelCase_  (			self :    str			,**lowerCamelCase__ :    str			):







							'''simple docstring'''
							return CLIPTokenizer.from_pretrained(self.tmpdirname			,pad_token='!'			,**lowerCamelCase__			)





	def      UpperCamelCase_  (			self :    int			,**lowerCamelCase__ :    Any			):







							'''simple docstring'''
							return CLIPTokenizerFast.from_pretrained(self.tmpdirname			,pad_token='!'			,**lowerCamelCase__			)





	def      UpperCamelCase_  (			self :    Union[str, Any]			,**lowerCamelCase__ :    Tuple			):







							'''simple docstring'''
							return OwlViTImageProcessor.from_pretrained(self.tmpdirname			,**lowerCamelCase__			)





	def      UpperCamelCase_  (			self :    List[Any]			):







							'''simple docstring'''
							shutil.rmtree(self.tmpdirname			)





	def      UpperCamelCase_  (			self :    Dict			):







							'''simple docstring'''
							_UpperCamelCase :		Union[str, Any]			    =       [np.random.randint(255			,size=(3, 30, 400)			,dtype=np.uinta			)]

							_UpperCamelCase :		List[Any]			    =       [Image.fromarray(np.moveaxis(lowerCamelCase__			,0			,-1			)			) for x in image_inputs]

							return image_inputs





	def      UpperCamelCase_  (			self :    List[Any]			):







							'''simple docstring'''
							_UpperCamelCase :		Optional[Any]			    =       self.get_tokenizer()
							_UpperCamelCase :		Tuple			    =       self.get_rust_tokenizer()
							_UpperCamelCase :		str			    =       self.get_image_processor()

							_UpperCamelCase :		Union[str, Any]			    =       OwlViTProcessor(tokenizer=lowerCamelCase__			,image_processor=lowerCamelCase__			)
							processor_slow.save_pretrained(self.tmpdirname			)
							_UpperCamelCase :		Union[str, Any]			    =       OwlViTProcessor.from_pretrained(self.tmpdirname			,use_fast=lowerCamelCase__			)

							_UpperCamelCase :		List[Any]			    =       OwlViTProcessor(tokenizer=lowerCamelCase__			,image_processor=lowerCamelCase__			)
							processor_fast.save_pretrained(self.tmpdirname			)
							_UpperCamelCase :		Tuple			    =       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			,lowerCamelCase__			)
							self.assertIsInstance(processor_fast.tokenizer			,lowerCamelCase__			)

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





	def      UpperCamelCase_  (			self :    int			):







							'''simple docstring'''
							_UpperCamelCase :		Optional[int]			    =       OwlViTProcessor(tokenizer=self.get_tokenizer()			,image_processor=self.get_image_processor()			)
							processor.save_pretrained(self.tmpdirname			)

							_UpperCamelCase :		Optional[int]			    =       self.get_tokenizer(bos_token='(BOS)'			,eos_token='(EOS)'			)
							_UpperCamelCase :		Tuple			    =       self.get_image_processor(do_normalize=lowerCamelCase__			)

							_UpperCamelCase :		Tuple			    =       OwlViTProcessor.from_pretrained(
							    self.tmpdirname			,bos_token='(BOS)'			,eos_token='(EOS)'			,do_normalize=lowerCamelCase__			)

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

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





	def      UpperCamelCase_  (			self :    Union[str, Any]			):







							'''simple docstring'''
							_UpperCamelCase :		Any			    =       self.get_image_processor()
							_UpperCamelCase :		List[str]			    =       self.get_tokenizer()

							_UpperCamelCase :		Dict			    =       OwlViTProcessor(tokenizer=lowerCamelCase__			,image_processor=lowerCamelCase__			)

							_UpperCamelCase :		Dict			    =       self.prepare_image_inputs()

							_UpperCamelCase :		Tuple			    =       image_processor(lowerCamelCase__			,return_tensors='np'			)
							_UpperCamelCase :		Union[str, Any]			    =       processor(images=lowerCamelCase__			,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 :    Tuple			):







							'''simple docstring'''
							_UpperCamelCase :		List[str]			    =       self.get_image_processor()
							_UpperCamelCase :		List[Any]			    =       self.get_tokenizer()

							_UpperCamelCase :		Optional[Any]			    =       OwlViTProcessor(tokenizer=lowerCamelCase__			,image_processor=lowerCamelCase__			)

							_UpperCamelCase :		Optional[int]			    =       'lower newer'

							_UpperCamelCase :		Optional[int]			    =       processor(text=lowerCamelCase__			,return_tensors='np'			)

							_UpperCamelCase :		int			    =       tokenizer(lowerCamelCase__			,return_tensors='np'			)

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





	def      UpperCamelCase_  (			self :    Optional[int]			):







							'''simple docstring'''
							_UpperCamelCase :		Dict			    =       self.get_image_processor()
							_UpperCamelCase :		int			    =       self.get_tokenizer()

							_UpperCamelCase :		List[str]			    =       OwlViTProcessor(tokenizer=lowerCamelCase__			,image_processor=lowerCamelCase__			)

							_UpperCamelCase :		List[str]			    =       'lower newer'
							_UpperCamelCase :		List[str]			    =       self.prepare_image_inputs()

							_UpperCamelCase :		Tuple			    =       processor(text=lowerCamelCase__			,images=lowerCamelCase__			)

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

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





	def      UpperCamelCase_  (			self :    str			):







							'''simple docstring'''
							_UpperCamelCase :		Union[str, Any]			    =       'google/owlvit-base-patch32'
							_UpperCamelCase :		Optional[int]			    =       OwlViTProcessor.from_pretrained(lowerCamelCase__			)

							_UpperCamelCase :		List[Any]			    =       ['cat', 'nasa badge']
							_UpperCamelCase :		List[str]			    =       processor(text=lowerCamelCase__			)

							_UpperCamelCase :		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(lowerCamelCase__			):
													processor()





	def      UpperCamelCase_  (			self :    Tuple			):







							'''simple docstring'''
							_UpperCamelCase :		Dict			    =       'google/owlvit-base-patch32'
							_UpperCamelCase :		List[str]			    =       OwlViTProcessor.from_pretrained(lowerCamelCase__			)

							_UpperCamelCase :		int			    =       [['cat', 'nasa badge'], ['person']]
							_UpperCamelCase :		str			    =       processor(text=lowerCamelCase__			)

							_UpperCamelCase :		Dict			    =       16
							_UpperCamelCase :		Optional[int]			    =       len(lowerCamelCase__			)
							_UpperCamelCase :		Optional[Any]			    =       max([len(lowerCamelCase__			) 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(lowerCamelCase__			):
													processor()





	def      UpperCamelCase_  (			self :    Optional[int]			):







							'''simple docstring'''
							_UpperCamelCase :		Optional[Any]			    =       'google/owlvit-base-patch32'
							_UpperCamelCase :		Dict			    =       OwlViTProcessor.from_pretrained(lowerCamelCase__			)

							_UpperCamelCase :		Dict			    =       ['cat', 'nasa badge']
							_UpperCamelCase :		Optional[int]			    =       processor(text=lowerCamelCase__			)

							_UpperCamelCase :		Optional[Any]			    =       16
							_UpperCamelCase :		Dict			    =       inputs['input_ids']
							_UpperCamelCase :		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 :    Optional[Any]			):







							'''simple docstring'''
							_UpperCamelCase :		List[Any]			    =       self.get_image_processor()
							_UpperCamelCase :		Any			    =       self.get_tokenizer()

							_UpperCamelCase :		str			    =       OwlViTProcessor(tokenizer=lowerCamelCase__			,image_processor=lowerCamelCase__			)

							_UpperCamelCase :		Any			    =       self.prepare_image_inputs()
							_UpperCamelCase :		str			    =       self.prepare_image_inputs()

							_UpperCamelCase :		str			    =       processor(images=lowerCamelCase__			,query_images=lowerCamelCase__			)

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

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





	def      UpperCamelCase_  (			self :    Union[str, Any]			):







							'''simple docstring'''
							_UpperCamelCase :		Any			    =       self.get_image_processor()
							_UpperCamelCase :		List[str]			    =       self.get_tokenizer()

							_UpperCamelCase :		Optional[Any]			    =       OwlViTProcessor(tokenizer=lowerCamelCase__			,image_processor=lowerCamelCase__			)

							_UpperCamelCase :		Optional[int]			    =       [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

							_UpperCamelCase :		Union[str, Any]			    =       processor.batch_decode(lowerCamelCase__			)
							_UpperCamelCase :		Union[str, Any]			    =       tokenizer.batch_decode(lowerCamelCase__			)

							self.assertListEqual(lowerCamelCase__			,lowerCamelCase__			)







'''simple docstring'''
from __future__ import annotations

import numpy as np






def A__   (					UpperCAmelCase_							):
						_UpperCamelCase    ,      _UpperCamelCase :		Optional[int]			    =       np.shape(UpperCAmelCase_							)
						if rows != columns:
												_UpperCamelCase :		Union[str, Any]			    =       (
												    '\'table\' has to be of square shaped array but got a '
												    f'{rows}x{columns} array:\n{table}'
												)
												raise ValueError(UpperCAmelCase_							)

						_UpperCamelCase :		Optional[Any]			    =       np.zeros((rows, columns)							)
						_UpperCamelCase :		Tuple			    =       np.zeros((rows, columns)							)
						for i in range(UpperCAmelCase_							):
												for j in range(UpperCAmelCase_							):
																		_UpperCamelCase :		Optional[Any]			    =       sum(lower[i][k] * upper[k][j] for k in range(UpperCAmelCase_							)							)
																		if upper[j][j] == 0:
																								raise ArithmeticError('No LU decomposition exists'							)
																		_UpperCamelCase :		Optional[Any]			    =       (table[i][j] - total) / upper[j][j]
												_UpperCamelCase :		int			    =       1
												for j in range(UpperCAmelCase_  ,  UpperCAmelCase_							):
																		_UpperCamelCase :		Optional[int]			    =       sum(lower[i][k] * upper[k][j] for k in range(UpperCAmelCase_							)							)
																		_UpperCamelCase :		Tuple			    =       table[i][j] - total
						return lower, upper


if __name__ == "__main__":
					import doctest

					doctest.testmod()


