



from __future__ import annotations

import math

def 	SCREAMING_SNAKE_CASE_							(	_snake_case	:int				)  ->     bool:

   if 1 < number < 4:
      # 2 and 3 are primes
      return True
   elif number < 2 or number % 2 == 0 or number % 3 == 0:
      # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
      return False

   # All primes number are in format of 6k +/- 1
   for i in range(5	,   int(math.sqrt(_snake_case				) + 1				)	,   6				):
      if number % i == 0 or number % (i + 2) == 0:
         return False
   return True


UpperCAmelCase_		 =					[num for num in range(3, 1_0_0_0_0_1, 2) if not is_prime(num)]

def 	SCREAMING_SNAKE_CASE_							(	_snake_case	:int				)  ->     list[int]:
   if not isinstance(_snake_case	,   _snake_case				):
      raise ValueError('''n must be an integer'''				)
   if n <= 0:
      raise ValueError('''n must be >= 0'''				)

   _A      =       []
   for num in range(len(_snake_case				)				):
      _A      =       0
      while 2 * i * i <= odd_composites[num]:
         _A      =       odd_composites[num] - 2 * i * i
         if is_prime(_snake_case				):
            break
         i += 1
      else:
         list_nums.append(odd_composites[num]				)
         if len(_snake_case				) == n:
            return list_nums

   return []

def 	SCREAMING_SNAKE_CASE_							(	)  ->     int:
   return compute_nums(1				)[0]


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










"""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,
      BertTokenizerFast,
      BlipImageProcessor,
      GPTaTokenizer,
      InstructBlipProcessor,
      PreTrainedTokenizerFast,
  )






@require_vision
class    _lowerCAmelCase  (	unittest.TestCase			):
       """simple docstring"""




       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :Any											=				tempfile.mkdtemp()

         lowerCAmelCase__     :List[Any]											=				BlipImageProcessor()
         lowerCAmelCase__     :Union[str, Any]											=				GPTaTokenizer.from_pretrained('hf-internal-testing/tiny-random-GPT2Model' )
         lowerCAmelCase__     :Union[str, Any]											=				BertTokenizerFast.from_pretrained('hf-internal-testing/tiny-random-bert' )

         lowerCAmelCase__     :List[str]											=				InstructBlipProcessor(__UpperCAmelCase       ,					__UpperCAmelCase       ,					__UpperCAmelCase )

         processor.save_pretrained(self.tmpdirname )






       def 	snake_case		(       self       ,					**__UpperCAmelCase ):



         '''simple docstring'''

         return AutoProcessor.from_pretrained(self.tmpdirname       ,					**__UpperCAmelCase ).tokenizer






       def 	snake_case		(       self       ,					**__UpperCAmelCase ):



         '''simple docstring'''

         return AutoProcessor.from_pretrained(self.tmpdirname       ,					**__UpperCAmelCase ).image_processor






       def 	snake_case		(       self       ,					**__UpperCAmelCase ):



         '''simple docstring'''

         return AutoProcessor.from_pretrained(self.tmpdirname       ,					**__UpperCAmelCase ).qformer_tokenizer






       def 	snake_case		(       self ):



         '''simple docstring'''

         shutil.rmtree(self.tmpdirname )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :Optional[Any]											=				[np.random.randint(2_5_5       ,					size=(3, 3_0, 4_0_0)       ,					dtype=np.uinta )]

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

         return image_inputs






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :List[str]											=				InstructBlipProcessor(
             tokenizer=self.get_tokenizer()       ,					image_processor=self.get_image_processor()       ,					qformer_tokenizer=self.get_qformer_tokenizer()       ,					)
         processor.save_pretrained(self.tmpdirname )

         lowerCAmelCase__     :Tuple											=				self.get_tokenizer(bos_token='(BOS)'       ,					eos_token='(EOS)' )
         lowerCAmelCase__     :str											=				self.get_image_processor(do_normalize=__UpperCAmelCase       ,					padding_value=1.0 )

         lowerCAmelCase__     :Dict											=				InstructBlipProcessor.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 )
         self.assertIsInstance(processor.qformer_tokenizer       ,					__UpperCAmelCase )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :Optional[Any]											=				self.get_image_processor()
         lowerCAmelCase__     :List[Any]											=				self.get_tokenizer()
         lowerCAmelCase__     :Optional[int]											=				self.get_qformer_tokenizer()

         lowerCAmelCase__     :str											=				InstructBlipProcessor(
             tokenizer=__UpperCAmelCase       ,					image_processor=__UpperCAmelCase       ,					qformer_tokenizer=__UpperCAmelCase )

         lowerCAmelCase__     :Dict											=				self.prepare_image_inputs()

         lowerCAmelCase__     :List[str]											=				image_processor(__UpperCAmelCase       ,					return_tensors='np' )
         lowerCAmelCase__     :Optional[Any]											=				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 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :Union[str, Any]											=				self.get_image_processor()
         lowerCAmelCase__     :Optional[int]											=				self.get_tokenizer()
         lowerCAmelCase__     :Optional[int]											=				self.get_qformer_tokenizer()

         lowerCAmelCase__     :Any											=				InstructBlipProcessor(
             tokenizer=__UpperCAmelCase       ,					image_processor=__UpperCAmelCase       ,					qformer_tokenizer=__UpperCAmelCase )

         lowerCAmelCase__     :Optional[int]											=				'lower newer'

         lowerCAmelCase__     :Dict											=				processor(text=__UpperCAmelCase )

         lowerCAmelCase__     :Union[str, Any]											=				tokenizer(__UpperCAmelCase       ,					return_token_type_ids=__UpperCAmelCase )
         lowerCAmelCase__     :Tuple											=				qformer_tokenizer(__UpperCAmelCase       ,					return_token_type_ids=__UpperCAmelCase )

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

         for key in encoded_tokens_qformer.keys():
           self.assertListEqual(encoded_tokens_qformer[key]       ,					encoded_processor['qformer_' + key] )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :Optional[Any]											=				self.get_image_processor()
         lowerCAmelCase__     :Optional[int]											=				self.get_tokenizer()
         lowerCAmelCase__     :str											=				self.get_qformer_tokenizer()

         lowerCAmelCase__     :Dict											=				InstructBlipProcessor(
             tokenizer=__UpperCAmelCase       ,					image_processor=__UpperCAmelCase       ,					qformer_tokenizer=__UpperCAmelCase )

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

         lowerCAmelCase__     :Tuple											=				processor(text=__UpperCAmelCase       ,					images=__UpperCAmelCase )

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

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






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :Tuple											=				self.get_image_processor()
         lowerCAmelCase__     :Dict											=				self.get_tokenizer()
         lowerCAmelCase__     :Optional[int]											=				self.get_qformer_tokenizer()

         lowerCAmelCase__     :int											=				InstructBlipProcessor(
             tokenizer=__UpperCAmelCase       ,					image_processor=__UpperCAmelCase       ,					qformer_tokenizer=__UpperCAmelCase )

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

         lowerCAmelCase__     :Tuple											=				processor.batch_decode(__UpperCAmelCase )
         lowerCAmelCase__     :Optional[int]											=				tokenizer.batch_decode(__UpperCAmelCase )

         self.assertListEqual(__UpperCAmelCase       ,					__UpperCAmelCase )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :Tuple											=				self.get_image_processor()
         lowerCAmelCase__     :Optional[int]											=				self.get_tokenizer()
         lowerCAmelCase__     :Dict											=				self.get_qformer_tokenizer()

         lowerCAmelCase__     :Optional[Any]											=				InstructBlipProcessor(
             tokenizer=__UpperCAmelCase       ,					image_processor=__UpperCAmelCase       ,					qformer_tokenizer=__UpperCAmelCase )

         lowerCAmelCase__     :Optional[int]											=				'lower newer'
         lowerCAmelCase__     :Optional[int]											=				self.prepare_image_inputs()

         lowerCAmelCase__     :int											=				processor(text=__UpperCAmelCase       ,					images=__UpperCAmelCase )

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