





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        __SCREAMING_SNAKE_CASE					(     unittest.TestCase       ):






							def 				_lowerCamelCase		(						self  ):
														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  , __lowerCAmelCase  )
														with open(self.image_processor_file  , """w"""  , encoding="""utf-8"""  ) as fp:
																					json.dump(__lowerCAmelCase  , __lowerCAmelCase  )






							def 				_lowerCamelCase		(						self  , **__lowerCAmelCase  ):
														return BertTokenizer.from_pretrained(self.tmpdirname  , **__lowerCAmelCase  )






							def 				_lowerCamelCase		(						self  , **__lowerCAmelCase  ):
														return ViTImageProcessor.from_pretrained(self.tmpdirname  , **__lowerCAmelCase  )






							def 				_lowerCamelCase		(						self  ):
														shutil.rmtree(self.tmpdirname  )






							def 				_lowerCamelCase		(						self  ):
														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 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			self.get_tokenizer()
														UpperCamelCase__				     =			self.get_image_processor()

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

														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  , __lowerCAmelCase  )






							def 				_lowerCamelCase		(						self  ):
														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=__lowerCAmelCase  , padding_value=1.0  )

														UpperCamelCase__				     =			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  ):
														UpperCamelCase__				     =			self.get_image_processor()
														UpperCamelCase__				     =			self.get_tokenizer()

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






							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			self.get_image_processor()
														UpperCamelCase__				     =			self.get_tokenizer()

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

														UpperCamelCase__				     =			"""lower newer"""

														UpperCamelCase__				     =			processor(text=__lowerCAmelCase  )

														UpperCamelCase__				     =			tokenizer(__lowerCAmelCase  )

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






							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			self.get_image_processor()
														UpperCamelCase__				     =			self.get_tokenizer()

														UpperCamelCase__				     =			VisionTextDualEncoderProcessor(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 self.assertRaises(__lowerCAmelCase  ):
																					processor()






							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			self.get_image_processor()
														UpperCamelCase__				     =			self.get_tokenizer()

														UpperCamelCase__				     =			VisionTextDualEncoderProcessor(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 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			self.get_image_processor()
														UpperCamelCase__				     =			self.get_tokenizer()

														UpperCamelCase__				     =			VisionTextDualEncoderProcessor(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  )











def     _UpperCamelCase     (a__   :int       ):






							"""simple docstring"""





							if divisor % 5 == 0 or divisor % 2 == 0:
														return 0
							UpperCamelCase__				     =			1
							UpperCamelCase__				     =			1
							while repunit:
														UpperCamelCase__				     =			(10 * repunit + 1) % divisor
														repunit_index += 1
							return repunit_index





def     _UpperCamelCase     (a__   :int = 100_0000       ):






							"""simple docstring"""





							UpperCamelCase__				     =			limit - 1
							if divisor % 2 == 0:
														divisor += 1
							while least_divisible_repunit(a__       ) <= limit:
														divisor += 2
							return divisor


if __name__ == "__main__":
					print(f"""{solution() = }""")




