code: 
  
  
  '''simple docstring'''
  
  import os
  from functools import partial
  from glob import glob
  
  import faiss
  from datasets import Features, Sequence, Value, concatenate_datasets, load_dataset, load_from_disk
  
  from transformers import DPRContextEncoder, DPRContextEncoderTokenizerFast
  
  def _SCREAMING_SNAKE_CASE   (A						,				A=100						,				A=" " ) -> int:
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         lowercase__       =				text.split(A )
         return [character.join(text[i : i + n] ).strip() for i in range(0						,				len(A )						,				A )]
  
  def _SCREAMING_SNAKE_CASE   (A ) -> str:
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         lowercase__    ,lowercase__       =				[], []
         for title, text in zip(documents['''title''']						,				documents['''text'''] ):
                if text is not None:
                       for passage in split_text(A ):
                              titles.append(title if title is not None else '''''' )
                              texts.append(A )
         return {"title": titles, "text": texts}
  
  def _SCREAMING_SNAKE_CASE   (A						,				A						,				A						,				A						,				A						,				A ) -> Optional[int]:
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         lowercase__       =				load_dataset(
             '''csv'''						,				data_files=[csv_path]						,				split='''train'''						,				delimiter='''\t'''						,				column_names=['''title''', '''text'''] )
         lowercase__       =				kb_dataset.map(
             A						,				batched=A						,				num_proc=1 )  # if you want you can load already splitted csv.
         lowercase__       =				[kb_dataset.shard(A						,				A						,				contiguous=A ) for i in range(A )]
         lowercase__       =				kb_list[process_num]
  
         lowercase__       =				'''data_''' + str(A )
         lowercase__       =				os.path.join(A						,				A )
  
         lowercase__       =				DPRContextEncoderTokenizerFast.from_pretrained('''facebook/dpr-ctx_encoder-multiset-base''' )
         lowercase__       =				ctx_encoder.to(device=A )
  
         def embed(
             A						,				A						,				A						,				A ) -> dict:
                lowercase__       =				ctx_tokenizer(
                    documents['''title''']						,				documents['''text''']						,				truncation=A						,				padding='''longest'''						,				return_tensors='''pt''' )['''input_ids''']
                lowercase__       =				ctx_encoder(input_ids.to(device=A )						,				return_dict=A ).pooler_output
                return {"embeddings": embeddings.detach().cpu().numpy()}
  
         lowercase__       =				Features(
             {'''text''': Value('''string''' ), '''title''': Value('''string''' ), '''embeddings''': Sequence(Value('''float32''' ) )} )  # optional, save as float32 instead of float64 to save space
  
         lowercase__       =				data_shrad.map(
             partial(A						,				ctx_encoder=A						,				ctx_tokenizer=A						,				device=A )						,				batched=A						,				batch_size=16						,				features=A						,				)
         dataset.save_to_disk(A )
  
  def _SCREAMING_SNAKE_CASE   (A						,				A ) -> Optional[int]:
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         lowercase__       =				[]
  
         for shard_address in glob(str(A ) + '''/*/''' ):
                data_shard_list.append(load_from_disk(A ) )
  
         lowercase__       =				concatenate_datasets(A )
         faiss.omp_set_num_threads(96 )
  
         lowercase__       =				faiss.IndexHNSWFlat(768						,				128						,				faiss.METRIC_INNER_PRODUCT )
         concat.add_faiss_index('''embeddings'''						,				custom_index=A )
         concat.get_index('''embeddings''' ).save(
             A )  # since we load the index in to memory,we can directly update the index in the disk
  
  
  
  
  
style_context: 
  
  
  '''simple docstring'''
  
  from __future__ import annotations
  
  from collections import Counter
  
  def _SCREAMING_SNAKE_CASE   (A ) -> list[int]:
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         lowercase__       =				[True] * n
         lowercase__       =				False
         lowercase__       =				False
         lowercase__       =				True
  
         for i in range(3						,				int(n**0.5 + 1 )						,				2 ):
                lowercase__       =				i * 2
                while index < n:
                       lowercase__       =				False
                       lowercase__       =				index + i
  
         lowercase__       =				[2]
  
         for i in range(3						,				A						,				2 ):
                if is_prime[i]:
                       primes.append(A )
  
         return primes
  
  def _SCREAMING_SNAKE_CASE   (A ) -> list[list[int]]:
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         lowercase__       =				str(A )
         lowercase__       =				[]
         lowercase__       =				['''0''', '''1''', '''2''', '''3''', '''4''', '''5''', '''6''', '''7''', '''8''', '''9''']
  
         for duplicate in Counter(A ) - Counter(set(A ) ):
                lowercase__       =				[int(number_str.replace(A						,				A ) ) for digit in digits]
                replacements.append(A )
  
         return replacements
  
  def _SCREAMING_SNAKE_CASE   (A = 8 ) -> int:
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         lowercase__       =				set()
  
         # Filter primes with less than 3 replaceable digits
         lowercase__       =				{
             x for x in set(prime_sieve(1_000_000 ) ) if len(str(A ) ) - len(set(str(A ) ) ) >= 3
         }
  
         for prime in primes:
                if prime in numbers_checked:
                       continue
  
                lowercase__       =				digit_replacements(A )
  
                for family in replacements:
                       numbers_checked.update(A )
                       lowercase__       =				primes.intersection(A )
  
                       if len(A ) != family_length:
                              continue
  
                       return min(A )
  
         return -1
  
  
  if __name__ == "__main__":
   print(solution())
  
  
  
  
  