



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 			lowercase__			(      unittest.TestCase    ):
							'''simple docstring'''







							def        lowerCamelCase_   (  self						)			->							Union[str, Any]:
									_UpperCAmelCase							 =		tempfile.mkdtemp()

									# fmt: off
									_UpperCAmelCase							 =		['[UNK]', '[CLS]', '[SEP]', '[PAD]', '[MASK]', 'want', '##want', '##ed', 'wa', 'un', 'runn', '##ing', ',', 'low', 'lowest']
									# fmt: on
									_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': {'height': 18, 'width': 18},
									    'do_normalize': True,
									    'image_mean': [0.5, 0.5, 0.5],
									    'image_std': [0.5, 0.5, 0.5],
									}
									_UpperCAmelCase							 =		os.path.join(self.tmpdirname	,       snake_case						)
									with open(self.image_processor_file	,       'w'	,       encoding='utf-8'						) as fp:
											json.dump(snake_case	,       snake_case						)






							def        lowerCamelCase_   (  self	,       **snake_case						)			->							Union[str, Any]:
									return BertTokenizer.from_pretrained(self.tmpdirname	,       **snake_case						)






							def        lowerCamelCase_   (  self	,       **snake_case						)			->							int:
									return ViTImageProcessor.from_pretrained(self.tmpdirname	,       **snake_case						)






							def        lowerCamelCase_   (  self						)			->							List[str]:
									shutil.rmtree(self.tmpdirname						)






							def        lowerCamelCase_   (  self						)			->							Optional[Any]:
									_UpperCAmelCase							 =		[np.random.randint(255	,       size=(3, 30, 400)	,       dtype=np.uinta						)]

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

									return image_inputs






							def        lowerCamelCase_   (  self						)			->							str:
									_UpperCAmelCase							 =		self.get_tokenizer()
									_UpperCAmelCase							 =		self.get_image_processor()

									_UpperCAmelCase							 =		VisionTextDualEncoderProcessor(tokenizer=snake_case	,       image_processor=snake_case						)

									processor.save_pretrained(self.tmpdirname						)
									_UpperCAmelCase							 =		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	,       snake_case						)






							def        lowerCamelCase_   (  self						)			->							Optional[int]:
									_UpperCAmelCase							 =		VisionTextDualEncoderProcessor(
									    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=snake_case	,       padding_value=1.0						)

									_UpperCAmelCase							 =		VisionTextDualEncoderProcessor.from_pretrained(
									    self.tmpdirname	,       bos_token='(BOS)'	,       eos_token='(EOS)'	,       do_normalize=snake_case	,       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	,       snake_case						)






							def        lowerCamelCase_   (  self						)			->							int:
									_UpperCAmelCase							 =		self.get_image_processor()
									_UpperCAmelCase							 =		self.get_tokenizer()

									_UpperCAmelCase							 =		VisionTextDualEncoderProcessor(tokenizer=snake_case	,       image_processor=snake_case						)

									_UpperCAmelCase							 =		self.prepare_image_inputs()

									_UpperCAmelCase							 =		image_processor(snake_case	,       return_tensors='np'						)
									_UpperCAmelCase							 =		processor(images=snake_case	,       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						)			->							str:
									_UpperCAmelCase							 =		self.get_image_processor()
									_UpperCAmelCase							 =		self.get_tokenizer()

									_UpperCAmelCase							 =		VisionTextDualEncoderProcessor(tokenizer=snake_case	,       image_processor=snake_case						)

									_UpperCAmelCase							 =		'lower newer'

									_UpperCAmelCase							 =		processor(text=snake_case						)

									_UpperCAmelCase							 =		tokenizer(snake_case						)

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






							def        lowerCamelCase_   (  self						)			->							Tuple:
									_UpperCAmelCase							 =		self.get_image_processor()
									_UpperCAmelCase							 =		self.get_tokenizer()

									_UpperCAmelCase							 =		VisionTextDualEncoderProcessor(tokenizer=snake_case	,       image_processor=snake_case						)

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

									_UpperCAmelCase							 =		processor(text=snake_case	,       images=snake_case						)

									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(snake_case						):
											processor()






							def        lowerCamelCase_   (  self						)			->							int:
									_UpperCAmelCase							 =		self.get_image_processor()
									_UpperCAmelCase							 =		self.get_tokenizer()

									_UpperCAmelCase							 =		VisionTextDualEncoderProcessor(tokenizer=snake_case	,       image_processor=snake_case						)

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

									_UpperCAmelCase							 =		processor.batch_decode(snake_case						)
									_UpperCAmelCase							 =		tokenizer.batch_decode(snake_case						)

									self.assertListEqual(snake_case	,       snake_case						)






							def        lowerCamelCase_   (  self						)			->							List[Any]:
									_UpperCAmelCase							 =		self.get_image_processor()
									_UpperCAmelCase							 =		self.get_tokenizer()

									_UpperCAmelCase							 =		VisionTextDualEncoderProcessor(tokenizer=snake_case	,       image_processor=snake_case						)

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

									_UpperCAmelCase							 =		processor(text=snake_case	,       images=snake_case						)

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







"""simple docstring"""





import os




def 	UpperCAmelCase     (		):

		'''simple docstring'''


		_UpperCAmelCase							 =		os.path.join(os.path.dirname(A       )     ,				'num.txt'       )
		with open(A       ) as file_hand:
				return str(sum(int(A       ) for line in file_hand       )       )[:10]


if __name__ == "__main__":
					print(solution())


