
"""simple docstring"""


import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available


if is_vision_available():
						from PIL import Image

						from transformers import AutoProcessor, BlipaProcessor, BlipImageProcessor, GPTaTokenizer, PreTrainedTokenizerFast




@require_vision
class  __lowerCamelCase  ( unittest.TestCase			):




				def        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  tempfile.mkdtemp()

							lowerCamelCase_					=  BlipImageProcessor()
							lowerCamelCase_					=  GPTaTokenizer.from_pretrained('''hf-internal-testing/tiny-random-GPT2Model'''   )

							lowerCamelCase_					=  BlipaProcessor(UpperCAmelCase							,						UpperCAmelCase   )

							processor.save_pretrained(self.tmpdirname   )




				def        UpperCAmelCase__						(				self							,						**UpperCAmelCase   ):
							return AutoProcessor.from_pretrained(self.tmpdirname							,						**UpperCAmelCase   ).tokenizer




				def        UpperCAmelCase__						(				self							,						**UpperCAmelCase   ):
							return AutoProcessor.from_pretrained(self.tmpdirname							,						**UpperCAmelCase   ).image_processor




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




				def        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  [np.random.randint(255							,						size=(3, 30, 400)							,						dtype=np.uinta   )]

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

							return image_inputs




				def        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  BlipaProcessor(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=UpperCAmelCase							,						padding_value=1.0   )

							lowerCamelCase_					=  BlipaProcessor.from_pretrained(
							    self.tmpdirname							,						bos_token='''(BOS)'''							,						eos_token='''(EOS)'''							,						do_normalize=UpperCAmelCase							,						padding_value=1.0   )

							self.assertEqual(processor.tokenizer.get_vocab()							,						tokenizer_add_kwargs.get_vocab()   )
							self.assertIsInstance(processor.tokenizer							,						UpperCAmelCase   )

							self.assertEqual(processor.image_processor.to_json_string()							,						image_processor_add_kwargs.to_json_string()   )
							self.assertIsInstance(processor.image_processor							,						UpperCAmelCase   )




				def        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  self.get_image_processor()
							lowerCamelCase_					=  self.get_tokenizer()

							lowerCamelCase_					=  BlipaProcessor(tokenizer=UpperCAmelCase							,						image_processor=UpperCAmelCase   )

							lowerCamelCase_					=  self.prepare_image_inputs()

							lowerCamelCase_					=  image_processor(UpperCAmelCase							,						return_tensors='''np'''   )
							lowerCamelCase_					=  processor(images=UpperCAmelCase							,						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        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  self.get_image_processor()
							lowerCamelCase_					=  self.get_tokenizer()

							lowerCamelCase_					=  BlipaProcessor(tokenizer=UpperCAmelCase							,						image_processor=UpperCAmelCase   )

							lowerCamelCase_					=  '''lower newer'''

							lowerCamelCase_					=  processor(text=UpperCAmelCase   )

							lowerCamelCase_					=  tokenizer(UpperCAmelCase							,						return_token_type_ids=UpperCAmelCase   )

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




				def        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  self.get_image_processor()
							lowerCamelCase_					=  self.get_tokenizer()

							lowerCamelCase_					=  BlipaProcessor(tokenizer=UpperCAmelCase							,						image_processor=UpperCAmelCase   )

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

							lowerCamelCase_					=  processor(text=UpperCAmelCase							,						images=UpperCAmelCase   )

							self.assertListEqual(list(inputs.keys()   )							,						['''pixel_values''', '''input_ids''', '''attention_mask''']   )

							# test if it raises when no input is passed
							with pytest.raises(UpperCAmelCase   ):
										processor()




				def        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  self.get_image_processor()
							lowerCamelCase_					=  self.get_tokenizer()

							lowerCamelCase_					=  BlipaProcessor(tokenizer=UpperCAmelCase							,						image_processor=UpperCAmelCase   )

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

							lowerCamelCase_					=  processor.batch_decode(UpperCAmelCase   )
							lowerCamelCase_					=  tokenizer.batch_decode(UpperCAmelCase   )

							self.assertListEqual(UpperCAmelCase							,						UpperCAmelCase   )





				def        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  self.get_image_processor()
							lowerCamelCase_					=  self.get_tokenizer()

							lowerCamelCase_					=  BlipaProcessor(tokenizer=UpperCAmelCase							,						image_processor=UpperCAmelCase   )

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

							lowerCamelCase_					=  processor(text=UpperCAmelCase							,						images=UpperCAmelCase   )

							# For now the processor supports only ['pixel_values', 'input_ids', 'attention_mask']
							self.assertListEqual(list(inputs.keys()   )							,						['''pixel_values''', '''input_ids''', '''attention_mask''']   )





"""simple docstring"""


import math






def  lowercase						(	lowerCAmelCase__						):
			lowerCamelCase_					=  [True] * n
			lowerCamelCase_					=  False
			lowerCamelCase_					=  False
			lowerCamelCase_					=  True

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

			lowerCamelCase_					=  [2]

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

			return primes






def  lowercase						(	lowerCAmelCase__ = 999_966_663_333						):
			lowerCamelCase_					=  math.floor(math.sqrt(lowerCAmelCase__						)						) + 100
			lowerCamelCase_					=  prime_sieve(lowerCAmelCase__						)

			lowerCamelCase_					=  0
			lowerCamelCase_					=  0
			lowerCamelCase_					=  primes[prime_index]

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

						lowerCamelCase_					=  last_prime**2
						lowerCamelCase_					=  next_prime**2

						# Get numbers divisible by lps(current)
						lowerCamelCase_					=  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)
						lowerCamelCase_					=  upper_bound - next_prime
						while current > lower_bound:
									matches_sum += current
									current -= next_prime

						# Remove the numbers divisible by both ups and lps
						lowerCamelCase_					=  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
						lowerCamelCase_					=  next_prime
						prime_index += 1

			return matches_sum


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



