





'''simple docstring'''

import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert 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 AlignProcessor, EfficientNetImageProcessor
@require_vision
class     __lowerCAmelCase					(   unittest.TestCase			):






       """simple docstring"""





       def snake_case__						(							self       :		Union[str, Any]					)   ->					Any:

            '''simple docstring'''




            _UpperCamelCase       =	tempfile.mkdtemp()

            _UpperCamelCase       =	[
                '''[UNK]''',
                '''[CLS]''',
                '''[SEP]''',
                '''[PAD]''',
                '''[MASK]''',
                '''want''',
                '''##want''',
                '''##ed''',
                '''wa''',
                '''un''',
                '''runn''',
                '''##ing''',
                ''',''',
                '''low''',
                '''lowest''',
            ]
            _UpperCamelCase       =	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]					)					)

            _UpperCamelCase       =	{
                '''do_resize''': True,
                '''size''': 20,
                '''do_center_crop''': True,
                '''crop_size''': 18,
                '''do_normalize''': True,
                '''image_mean''': [0.48145466, 0.4578275, 0.40821073],
                '''image_std''': [0.26862954, 0.26130258, 0.27577711],
            }
            _UpperCamelCase       =	os.path.join(self.tmpdirname	,			lowerCAmelCase__					)
            with open(self.image_processor_file	,			'''w'''	,			encoding='''utf-8'''					) as fp:
                 json.dump(lowerCAmelCase__	,			lowerCAmelCase__					)





       def snake_case__						(							self       :		Dict	,			**lowerCAmelCase__       :		Optional[int]					)   ->					Union[str, Any]:

            '''simple docstring'''




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





       def snake_case__						(							self       :		List[Any]	,			**lowerCAmelCase__       :		int					)   ->					List[str]:

            '''simple docstring'''




            return BertTokenizerFast.from_pretrained(self.tmpdirname	,			**lowerCAmelCase__					)





       def snake_case__						(							self       :		int	,			**lowerCAmelCase__       :		List[str]					)   ->					Union[str, Any]:

            '''simple docstring'''




            return EfficientNetImageProcessor.from_pretrained(self.tmpdirname	,			**lowerCAmelCase__					)





       def snake_case__						(							self       :		Any					)   ->					Tuple:

            '''simple docstring'''




            shutil.rmtree(self.tmpdirname					)





       def snake_case__						(							self       :		Union[str, Any]					)   ->					int:

            '''simple docstring'''




            _UpperCamelCase       =	[np.random.randint(255	,			size=(3, 30, 400)	,			dtype=np.uinta					)]
            _UpperCamelCase       =	[Image.fromarray(np.moveaxis(lowerCAmelCase__	,			0	,			-1					)					) for x in image_inputs]
            return image_inputs





       def snake_case__						(							self       :		Optional[Any]					)   ->					Any:

            '''simple docstring'''




            _UpperCamelCase       =	self.get_tokenizer()
            _UpperCamelCase       =	self.get_rust_tokenizer()
            _UpperCamelCase       =	self.get_image_processor()

            _UpperCamelCase       =	AlignProcessor(tokenizer=lowerCAmelCase__	,			image_processor=lowerCAmelCase__					)
            processor_slow.save_pretrained(self.tmpdirname					)
            _UpperCamelCase       =	AlignProcessor.from_pretrained(self.tmpdirname	,			use_fast=lowerCAmelCase__					)

            _UpperCamelCase       =	AlignProcessor(tokenizer=lowerCAmelCase__	,			image_processor=lowerCAmelCase__					)
            processor_fast.save_pretrained(self.tmpdirname					)
            _UpperCamelCase       =	AlignProcessor.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 snake_case__						(							self       :		Dict					)   ->					Any:

            '''simple docstring'''




            _UpperCamelCase       =	AlignProcessor(tokenizer=self.get_tokenizer()	,			image_processor=self.get_image_processor()					)
            processor.save_pretrained(self.tmpdirname					)

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

            _UpperCamelCase       =	AlignProcessor.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	,			lowerCAmelCase__					)

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





       def snake_case__						(							self       :		Tuple					)   ->					Dict:

            '''simple docstring'''




            _UpperCamelCase       =	self.get_image_processor()
            _UpperCamelCase       =	self.get_tokenizer()

            _UpperCamelCase       =	AlignProcessor(tokenizer=lowerCAmelCase__	,			image_processor=lowerCAmelCase__					)

            _UpperCamelCase       =	self.prepare_image_inputs()

            _UpperCamelCase       =	image_processor(lowerCAmelCase__	,			return_tensors='''np'''					)
            _UpperCamelCase       =	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 snake_case__						(							self       :		Optional[Any]					)   ->					str:

            '''simple docstring'''




            _UpperCamelCase       =	self.get_image_processor()
            _UpperCamelCase       =	self.get_tokenizer()

            _UpperCamelCase       =	AlignProcessor(tokenizer=lowerCAmelCase__	,			image_processor=lowerCAmelCase__					)

            _UpperCamelCase       =	'''lower newer'''

            _UpperCamelCase       =	processor(text=lowerCAmelCase__					)

            _UpperCamelCase       =	tokenizer(lowerCAmelCase__	,			padding='''max_length'''	,			max_length=64					)

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





       def snake_case__						(							self       :		str					)   ->					str:

            '''simple docstring'''




            _UpperCamelCase       =	self.get_image_processor()
            _UpperCamelCase       =	self.get_tokenizer()

            _UpperCamelCase       =	AlignProcessor(tokenizer=lowerCAmelCase__	,			image_processor=lowerCAmelCase__					)

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

            _UpperCamelCase       =	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 pytest.raises(lowerCAmelCase__					):
                 processor()





       def snake_case__						(							self       :		List[Any]					)   ->					Tuple:

            '''simple docstring'''




            _UpperCamelCase       =	self.get_image_processor()
            _UpperCamelCase       =	self.get_tokenizer()

            _UpperCamelCase       =	AlignProcessor(tokenizer=lowerCAmelCase__	,			image_processor=lowerCAmelCase__					)

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

            _UpperCamelCase       =	processor.batch_decode(lowerCAmelCase__					)
            _UpperCamelCase       =	tokenizer.batch_decode(lowerCAmelCase__					)

            self.assertListEqual(lowerCAmelCase__	,			lowerCAmelCase__					)







       def snake_case__						(							self       :		Optional[Any]					)   ->					List[Any]:

            '''simple docstring'''




            _UpperCamelCase       =	self.get_image_processor()
            _UpperCamelCase       =	self.get_tokenizer()

            _UpperCamelCase       =	AlignProcessor(tokenizer=lowerCAmelCase__	,			image_processor=lowerCAmelCase__					)

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

            _UpperCamelCase       =	processor(text=lowerCAmelCase__	,			images=lowerCAmelCase__					)

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










'''simple docstring'''

import warnings

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


lowercase__						:      Optional[Any]	=    logging.get_logger(__name__)
class     __lowerCAmelCase					(   __magic_name__			):






       """simple docstring"""





       def __init__(							self       :		List[Any]	,			*lowerCAmelCase__       :		List[str]	,			**lowerCAmelCase__       :		List[str]					)   ->					None:

            '''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__					)



