"""simple docstring"""







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						):



				def 					_lowercase     (self				:      Tuple)    ->	Optional[Any]:
					__snake_case			:							int      		= tempfile.mkdtemp()

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

					__snake_case			:							List[str]      		= {
					    '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],
					}
					__snake_case			:							Optional[int]      		= 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 					_lowercase     (self				:      Any	,  **_A				:      int)    ->	str:
					return BertTokenizer.from_pretrained(self.tmpdirname	,  **__snake_case)



				def 					_lowercase     (self				:      str	,  **_A				:      Dict)    ->	Optional[int]:
					return ViTImageProcessor.from_pretrained(self.tmpdirname	,  **__snake_case)



				def 					_lowercase     (self				:      Optional[Any])    ->	Optional[Any]:
					shutil.rmtree(self.tmpdirname)



				def 					_lowercase     (self				:      int)    ->	int:
					__snake_case			:							Union[str, Any]      		= [np.random.randint(2_55	,  size=(3, 30, 4_00)	,  dtype=np.uinta)]

					__snake_case			:							int      		= [Image.fromarray(np.moveaxis(__snake_case	,  0	,  -1)) for x in image_inputs]

					return image_inputs



				def 					_lowercase     (self				:      List[str])    ->	Dict:
					__snake_case			:							Any      		= self.get_tokenizer()
					__snake_case			:							Optional[Any]      		= self.get_image_processor()

					__snake_case			:							Union[str, Any]      		= VisionTextDualEncoderProcessor(tokenizer=__snake_case	,  image_processor=__snake_case)

					processor.save_pretrained(self.tmpdirname)
					__snake_case			:							Optional[int]      		= 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 					_lowercase     (self				:      Optional[int])    ->	Union[str, Any]:
					__snake_case			:							Any      		= VisionTextDualEncoderProcessor(
					    tokenizer=self.get_tokenizer()	,  image_processor=self.get_image_processor())
					processor.save_pretrained(self.tmpdirname)

					__snake_case			:							List[str]      		= self.get_tokenizer(bos_token='(BOS)'	,  eos_token='(EOS)')
					__snake_case			:							Any      		= self.get_image_processor(do_normalize=__snake_case	,  padding_value=1.0)

					__snake_case			:							Union[str, Any]      		= 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 					_lowercase     (self				:      Tuple)    ->	Union[str, Any]:
					__snake_case			:							Dict      		= self.get_image_processor()
					__snake_case			:							Optional[Any]      		= self.get_tokenizer()

					__snake_case			:							Tuple      		= VisionTextDualEncoderProcessor(tokenizer=__snake_case	,  image_processor=__snake_case)

					__snake_case			:							List[str]      		= self.prepare_image_inputs()

					__snake_case			:							Dict      		= image_processor(__snake_case	,  return_tensors='np')
					__snake_case			:							Optional[Any]      		= 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 					_lowercase     (self				:      Optional[int])    ->	List[Any]:
					__snake_case			:							List[str]      		= self.get_image_processor()
					__snake_case			:							List[Any]      		= self.get_tokenizer()

					__snake_case			:							str      		= VisionTextDualEncoderProcessor(tokenizer=__snake_case	,  image_processor=__snake_case)

					__snake_case			:							str      		= 'lower newer'

					__snake_case			:							str      		= processor(text=__snake_case)

					__snake_case			:							Dict      		= tokenizer(__snake_case)

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



				def 					_lowercase     (self				:      int)    ->	str:
					__snake_case			:							Union[str, Any]      		= self.get_image_processor()
					__snake_case			:							List[Any]      		= self.get_tokenizer()

					__snake_case			:							Dict      		= VisionTextDualEncoderProcessor(tokenizer=__snake_case	,  image_processor=__snake_case)

					__snake_case			:							Union[str, Any]      		= 'lower newer'
					__snake_case			:							Optional[Any]      		= self.prepare_image_inputs()

					__snake_case			:							Union[str, Any]      		= 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 					_lowercase     (self				:      Optional[Any])    ->	Any:
					__snake_case			:							List[Any]      		= self.get_image_processor()
					__snake_case			:							List[Any]      		= self.get_tokenizer()

					__snake_case			:							List[Any]      		= VisionTextDualEncoderProcessor(tokenizer=__snake_case	,  image_processor=__snake_case)

					__snake_case			:							List[str]      		= [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

					__snake_case			:							Dict      		= processor.batch_decode(__snake_case)
					__snake_case			:							List[str]      		= tokenizer.batch_decode(__snake_case)

					self.assertListEqual(__snake_case	,  __snake_case)






				def 					_lowercase     (self				:      Union[str, Any])    ->	Optional[Any]:
					__snake_case			:							Optional[int]      		= self.get_image_processor()
					__snake_case			:							List[str]      		= self.get_tokenizer()

					__snake_case			:							Any      		= VisionTextDualEncoderProcessor(tokenizer=__snake_case	,  image_processor=__snake_case)

					__snake_case			:							Union[str, Any]      		= 'lower newer'
					__snake_case			:							str      		= self.prepare_image_inputs()

					__snake_case			:							Any      		= processor(text=__snake_case	,  images=__snake_case)

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









import math






def 							__lowercase   ( __lowerCAmelCase							:				int   ):
							a__             =     [True] * n
							a__             =     False
							a__             =     False
							a__             =     True

							for i in range(3					,    int(n**0.5 + 1   )					,    2   ):
														a__             =     i * 2
														while index < n:
																					a__             =     False
																					a__             =     index + i

							a__             =     [2]

							for i in range(3					,    __lowerCAmelCase					,    2   ):
														if is_prime[i]:
																					primes.append(__lowerCAmelCase   )

							return primes






def 							__lowercase   ( __lowerCAmelCase							:				int = 9_9_9_9_6_6_6_6_3_3_3_3   ):
							a__             =     math.floor(math.sqrt(__lowerCAmelCase   )   ) + 1_0_0
							a__             =     prime_sieve(__lowerCAmelCase   )

							a__             =     0
							a__             =     0
							a__             =     primes[prime_index]

							while (last_prime**2) <= limit:
														a__             =     primes[prime_index + 1]

														a__             =     last_prime**2
														a__             =     next_prime**2

														# Get numbers divisible by lps(current)
														a__             =     lower_bound + last_prime
														while upper_bound > current <= limit:
																					matches_sum += current
																					current += last_prime

														# Reset the upper_bound
														while (upper_bound - next_prime) > limit:
																					upper_bound -= next_prime

														# Add the numbers divisible by ups(current)
														a__             =     upper_bound - next_prime
														while current > lower_bound:
																					matches_sum += current
																					current -= next_prime

														# Remove the numbers divisible by both ups and lps
														a__             =     0
														while upper_bound > current <= limit:
																					if current <= lower_bound:
																												# Increment the current number
																												current += last_prime * next_prime
																												continue

																					if current > limit:
																												break

																					# Remove twice since it was added by both ups and lps
																					matches_sum -= current * 2

																					# Increment the current number
																					current += last_prime * next_prime

														# Setup for next pair
														a__             =     next_prime
														prime_index += 1

							return matches_sum


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




