





import json
import os
import shutil
import tempfile
import unittest

import numpy as np

from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
			from PIL import Image

			from transformers import VisionTextDualEncoderProcessor, ViTImageProcessor






@require_tokenizers
@require_vision
class       __A					(					unittest.TestCase				):

			'''simple docstring'''







			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				lowerCamelCase__              =	tempfile.mkdtemp()

				# fmt: off
				lowerCamelCase__              =	['''[UNK]''', '''[CLS]''', '''[SEP]''', '''[PAD]''', '''[MASK]''', '''want''', '''##want''', '''##ed''', '''wa''', '''un''', '''runn''', '''##ing''', ''',''', '''low''', '''lowest''']
				# fmt: on
				lowerCamelCase__              =	os.path.join(self.tmpdirname ,						VOCAB_FILES_NAMES['''vocab_file''']							)
				with open(self.vocab_file ,						'''w''' ,						encoding='''utf-8'''							) as vocab_writer:
					vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]							)							)

				lowerCamelCase__              =	{
				    '''do_resize''': True,
				    '''size''': {'''height''': 1_8, '''width''': 1_8},
				    '''do_normalize''': True,
				    '''image_mean''': [0.5, 0.5, 0.5],
				    '''image_std''': [0.5, 0.5, 0.5],
				}
				lowerCamelCase__              =	os.path.join(self.tmpdirname ,						__lowerCAmelCase							)
				with open(self.image_processor_file ,						'''w''' ,						encoding='''utf-8'''							) as fp:
					json.dump(__lowerCAmelCase ,						__lowerCAmelCase							)





			def 	__lowerCamelCase       (					self ,						**__lowerCAmelCase							):



				'''simple docstring'''







				return BertTokenizer.from_pretrained(self.tmpdirname ,						**__lowerCAmelCase							)





			def 	__lowerCamelCase       (					self ,						**__lowerCAmelCase							):



				'''simple docstring'''







				return ViTImageProcessor.from_pretrained(self.tmpdirname ,						**__lowerCAmelCase							)





			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				shutil.rmtree(self.tmpdirname							)





			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				lowerCamelCase__              =	[np.random.randint(2_5_5 ,						size=(3, 3_0, 4_0_0) ,						dtype=np.uinta							)]

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

				return image_inputs





			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				lowerCamelCase__              =	self.get_tokenizer()
				lowerCamelCase__              =	self.get_image_processor()

				lowerCamelCase__              =	VisionTextDualEncoderProcessor(tokenizer=__lowerCAmelCase ,						image_processor=__lowerCAmelCase							)

				processor.save_pretrained(self.tmpdirname							)
				lowerCamelCase__              =	VisionTextDualEncoderProcessor.from_pretrained(self.tmpdirname							)

				self.assertEqual(processor.tokenizer.get_vocab() ,						tokenizer.get_vocab()							)
				self.assertIsInstance(processor.tokenizer ,						(BertTokenizer, BertTokenizerFast)							)

				self.assertEqual(processor.image_processor.to_json_string() ,						image_processor.to_json_string()							)
				self.assertIsInstance(processor.image_processor ,						__lowerCAmelCase							)





			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				lowerCamelCase__              =	VisionTextDualEncoderProcessor(
				    tokenizer=self.get_tokenizer() ,						image_processor=self.get_image_processor()							)
				processor.save_pretrained(self.tmpdirname							)

				lowerCamelCase__              =	self.get_tokenizer(bos_token='''(BOS)''' ,						eos_token='''(EOS)'''							)
				lowerCamelCase__              =	self.get_image_processor(do_normalize=__lowerCAmelCase ,						padding_value=1.0							)

				lowerCamelCase__              =	VisionTextDualEncoderProcessor.from_pretrained(
				    self.tmpdirname ,						bos_token='''(BOS)''' ,						eos_token='''(EOS)''' ,						do_normalize=__lowerCAmelCase ,						padding_value=1.0							)

				self.assertEqual(processor.tokenizer.get_vocab() ,						tokenizer_add_kwargs.get_vocab()							)
				self.assertIsInstance(processor.tokenizer ,						(BertTokenizer, BertTokenizerFast)							)

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





			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				lowerCamelCase__              =	self.get_image_processor()
				lowerCamelCase__              =	self.get_tokenizer()

				lowerCamelCase__              =	VisionTextDualEncoderProcessor(tokenizer=__lowerCAmelCase ,						image_processor=__lowerCAmelCase							)

				lowerCamelCase__              =	self.prepare_image_inputs()

				lowerCamelCase__              =	image_processor(__lowerCAmelCase ,						return_tensors='''np'''							)
				lowerCamelCase__              =	processor(images=__lowerCAmelCase ,						return_tensors='''np'''							)

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





			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				lowerCamelCase__              =	self.get_image_processor()
				lowerCamelCase__              =	self.get_tokenizer()

				lowerCamelCase__              =	VisionTextDualEncoderProcessor(tokenizer=__lowerCAmelCase ,						image_processor=__lowerCAmelCase							)

				lowerCamelCase__              =	'''lower newer'''

				lowerCamelCase__              =	processor(text=__lowerCAmelCase							)

				lowerCamelCase__              =	tokenizer(__lowerCAmelCase							)

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





			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				lowerCamelCase__              =	self.get_image_processor()
				lowerCamelCase__              =	self.get_tokenizer()

				lowerCamelCase__              =	VisionTextDualEncoderProcessor(tokenizer=__lowerCAmelCase ,						image_processor=__lowerCAmelCase							)

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

				lowerCamelCase__              =	processor(text=__lowerCAmelCase ,						images=__lowerCAmelCase							)

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

				# test if it raises when no input is passed
				with self.assertRaises(__lowerCAmelCase							):
					processor()





			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				lowerCamelCase__              =	self.get_image_processor()
				lowerCamelCase__              =	self.get_tokenizer()

				lowerCamelCase__              =	VisionTextDualEncoderProcessor(tokenizer=__lowerCAmelCase ,						image_processor=__lowerCAmelCase							)

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

				lowerCamelCase__              =	processor.batch_decode(__lowerCAmelCase							)
				lowerCamelCase__              =	tokenizer.batch_decode(__lowerCAmelCase							)

				self.assertListEqual(__lowerCAmelCase ,						__lowerCAmelCase							)





			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				lowerCamelCase__              =	self.get_image_processor()
				lowerCamelCase__              =	self.get_tokenizer()

				lowerCamelCase__              =	VisionTextDualEncoderProcessor(tokenizer=__lowerCAmelCase ,						image_processor=__lowerCAmelCase							)

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

				lowerCamelCase__              =	processor(text=__lowerCAmelCase ,						images=__lowerCAmelCase							)

				self.assertListEqual(list(inputs.keys()							) ,						processor.model_input_names							)










import warnings

from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor


_a						=   logging.get_logger(__name__)






class       __A					(					lowerCAmelCase				):

			'''simple docstring'''







			def __init__(					self ,						*__lowerCAmelCase ,						**__lowerCAmelCase							):



				'''simple docstring'''







				warnings.warn(
				    '''The class OwlViTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
				    ''' use OwlViTImageProcessor instead.''' ,						__lowerCAmelCase ,						)
				super().__init__(*__lowerCAmelCase ,						**__lowerCAmelCase							)



