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    _UpperCamelCase      (						unittest.TestCase ):


			"""simple docstring"""






			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					Optional[int]:

							'''simple docstring'''


							__lowercase 			=							tempfile.mkdtemp()

							# fmt: off
							__lowercase 			=							['''[UNK]''', '''[CLS]''', '''[SEP]''', '''[PAD]''', '''[MASK]''', '''want''', '''##want''', '''##ed''', '''wa''', '''un''', '''runn''', '''##ing''', ''',''', '''low''', '''lowest''']
							# fmt: on
							__lowercase 			=							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]						)						)

							__lowercase 			=							{
							    '''do_resize''': True,
							    '''size''': {'''height''': 18, '''width''': 18},
							    '''do_normalize''': True,
							    '''image_mean''': [0.5, 0.5, 0.5],
							    '''image_std''': [0.5, 0.5, 0.5],
							}
							__lowercase 			=							os.path.join(self.tmpdirname      ,   lowerCAmelCase__						)
							with open(self.image_processor_file      ,   '''w'''      ,   encoding='''utf-8'''						) as fp:
											json.dump(lowerCAmelCase__      ,   lowerCAmelCase__						)





			def        _SCREAMING_SNAKE_CASE			(   self      ,   **lowerCAmelCase__						)     ->					List[Any]:

							'''simple docstring'''


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





			def        _SCREAMING_SNAKE_CASE			(   self      ,   **lowerCAmelCase__						)     ->					Union[str, Any]:

							'''simple docstring'''


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





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					List[Any]:

							'''simple docstring'''


							shutil.rmtree(self.tmpdirname						)





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					Any:

							'''simple docstring'''


							__lowercase 			=							[np.random.randint(2_55      ,   size=(3, 30, 4_00)      ,   dtype=np.uinta						)]

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

							return image_inputs





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					int:

							'''simple docstring'''


							__lowercase 			=							self.get_tokenizer()
							__lowercase 			=							self.get_image_processor()

							__lowercase 			=							VisionTextDualEncoderProcessor(tokenizer=lowerCAmelCase__      ,   image_processor=lowerCAmelCase__						)

							processor.save_pretrained(self.tmpdirname						)
							__lowercase 			=							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        _SCREAMING_SNAKE_CASE			(   self						)     ->					str:

							'''simple docstring'''


							__lowercase 			=							VisionTextDualEncoderProcessor(
							    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=lowerCAmelCase__      ,   padding_value=1.0						)

							__lowercase 			=							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        _SCREAMING_SNAKE_CASE			(   self						)     ->					Dict:

							'''simple docstring'''


							__lowercase 			=							self.get_image_processor()
							__lowercase 			=							self.get_tokenizer()

							__lowercase 			=							VisionTextDualEncoderProcessor(tokenizer=lowerCAmelCase__      ,   image_processor=lowerCAmelCase__						)

							__lowercase 			=							self.prepare_image_inputs()

							__lowercase 			=							image_processor(lowerCAmelCase__      ,   return_tensors='''np'''						)
							__lowercase 			=							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        _SCREAMING_SNAKE_CASE			(   self						)     ->					Dict:

							'''simple docstring'''


							__lowercase 			=							self.get_image_processor()
							__lowercase 			=							self.get_tokenizer()

							__lowercase 			=							VisionTextDualEncoderProcessor(tokenizer=lowerCAmelCase__      ,   image_processor=lowerCAmelCase__						)

							__lowercase 			=							'''lower newer'''

							__lowercase 			=							processor(text=lowerCAmelCase__						)

							__lowercase 			=							tokenizer(lowerCAmelCase__						)

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





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					Any:

							'''simple docstring'''


							__lowercase 			=							self.get_image_processor()
							__lowercase 			=							self.get_tokenizer()

							__lowercase 			=							VisionTextDualEncoderProcessor(tokenizer=lowerCAmelCase__      ,   image_processor=lowerCAmelCase__						)

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

							__lowercase 			=							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        _SCREAMING_SNAKE_CASE			(   self						)     ->					Dict:

							'''simple docstring'''


							__lowercase 			=							self.get_image_processor()
							__lowercase 			=							self.get_tokenizer()

							__lowercase 			=							VisionTextDualEncoderProcessor(tokenizer=lowerCAmelCase__      ,   image_processor=lowerCAmelCase__						)

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

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

							self.assertListEqual(lowerCAmelCase__      ,   lowerCAmelCase__						)





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					int:

							'''simple docstring'''


							__lowercase 			=							self.get_image_processor()
							__lowercase 			=							self.get_tokenizer()

							__lowercase 			=							VisionTextDualEncoderProcessor(tokenizer=lowerCAmelCase__      ,   image_processor=lowerCAmelCase__						)

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

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

							self.assertListEqual(list(inputs.keys()						)      ,   processor.model_input_names						)
from ..utils import DummyObject, requires_backends




class    _UpperCamelCase      (						metaclass=_UpperCAmelCase ):


			"""simple docstring"""






			__a  : Dict			 =						['''keras_nlp''']





			def __init__(   self      ,   *lowerCAmelCase__      ,   **lowerCAmelCase__						)     ->					Tuple:

							'''simple docstring'''


							requires_backends(self      ,   ['''keras_nlp''']						)