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 		__snake_case						(      self :  List[Any]):







								'''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""": 18, """width""": 18},
								    """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 		__snake_case						(      self :  Dict      ,   **lowercase__ :  Dict):







								'''simple docstring'''



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




	def 		__snake_case						(      self :  Dict      ,   **lowercase__ :  List[Any]):







								'''simple docstring'''



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




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







								'''simple docstring'''



								shutil.rmtree(self.tmpdirname)




	def 		__snake_case						(      self :  Tuple):







								'''simple docstring'''



								lowerCAmelCase__					     = [np.random.randint(255      ,   size=(3, 30, 400)      ,   dtype=np.uinta)]

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

								return image_inputs




	def 		__snake_case						(      self :  Any):







								'''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 		__snake_case						(      self :  Tuple):







								'''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 		__snake_case						(      self :  Optional[int]):







								'''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 		__snake_case						(      self :  Union[str, Any]):







								'''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 		__snake_case						(      self :  Tuple):







								'''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 		__snake_case						(      self :  int):







								'''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 		__snake_case						(      self :  Any):







								'''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 copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class     a_			:






 '''simple docstring'''






 UpperCAmelCase_     			= None
 UpperCAmelCase_     			= False
 UpperCAmelCase_     			= False
 UpperCAmelCase_     			= False
 UpperCAmelCase_     			= None
 UpperCAmelCase_     			= None
 UpperCAmelCase_     			= False
 UpperCAmelCase_     			= False
 UpperCAmelCase_     			= False
 UpperCAmelCase_     			= True
 UpperCAmelCase_     			= None
 UpperCAmelCase_     			= 1
 UpperCAmelCase_     			= None
 UpperCAmelCase_     			= False
 UpperCAmelCase_     			= None
 UpperCAmelCase_     			= None




 def 		__snake_case						(      self :  Dict):







        '''simple docstring'''



        return self.__class__(**{k: copy.deepcopy(lowercase__) for k, v in self.__dict__.items()})
