





"""simple docstring"""





import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional

import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset

from transformers import DPRContextEncoder, DPRContextEncoderTokenizerFast, HfArgumentParser


SCREAMING_SNAKE_CASE__					=   logging.getLogger(__name__)
torch.set_grad_enabled(False)
SCREAMING_SNAKE_CASE__					=   "cuda" if torch.cuda.is_available() else "cpu"


def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						str							,						SCREAMING_SNAKE_CASE     :						Union[str, Any]=1_00							,						SCREAMING_SNAKE_CASE     :						str=" "			):







      '''simple docstring'''




      lowerCAmelCase  						=       text.split(SCREAMING_SNAKE_CASE			)
      return [character.join(text[i : i + n]			).strip() for i in range(0							,						len(SCREAMING_SNAKE_CASE			)							,						SCREAMING_SNAKE_CASE			)]


def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						dict			):







      '''simple docstring'''




      lowerCAmelCase						,		lowerCAmelCase  						=       [], []
      for title, text in zip(documents["""title"""]							,						documents["""text"""]			):
            if text is not None:
                  for passage in split_text(SCREAMING_SNAKE_CASE			):
                        titles.append(title if title is not None else """"""			)
                        texts.append(SCREAMING_SNAKE_CASE			)
      return {"title": titles, "text": texts}


def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						dict							,						SCREAMING_SNAKE_CASE     :						DPRContextEncoder							,						SCREAMING_SNAKE_CASE     :						DPRContextEncoderTokenizerFast			):







      '''simple docstring'''




      lowerCAmelCase  						=       ctx_tokenizer(
          documents["""title"""]							,						documents["""text"""]							,						truncation=SCREAMING_SNAKE_CASE							,						padding="""longest"""							,						return_tensors="""pt"""			)["""input_ids"""]
      lowerCAmelCase  						=       ctx_encoder(input_ids.to(device=SCREAMING_SNAKE_CASE			)							,						return_dict=SCREAMING_SNAKE_CASE			).pooler_output
      return {"embeddings": embeddings.detach().cpu().numpy()}


def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						"RagExampleArguments"							,						SCREAMING_SNAKE_CASE     :						"ProcessingArguments"							,						SCREAMING_SNAKE_CASE     :						"IndexHnswArguments"							,						):







      '''simple docstring'''




      logger.info("""Step 1 - Create the dataset"""			)
      ######################################

      # The dataset needed for RAG must have three columns:
      # - title (string): title of the document
      # - text (string): text of a passage of the document
      # - embeddings (array of dimension d): DPR representation of the passage
      # Let's say you have documents in tab-separated csv files with columns "title" and "text"
      assert os.path.isfile(rag_example_args.csv_path			), "Please provide a valid path to a csv file"

      # You can load a Dataset object this way
      lowerCAmelCase  						=       load_dataset(
          """csv"""							,						data_files=[rag_example_args.csv_path]							,						split="""train"""							,						delimiter="""\t"""							,						column_names=["""title""", """text"""]			)

      # More info about loading csv files in the documentation: https://huggingface.co/docs/datasets/loading_datasets.html?highlight=csv#csv-files

      # Then split the documents into passages of 100 words
      lowerCAmelCase  						=       dataset.map(SCREAMING_SNAKE_CASE							,						batched=SCREAMING_SNAKE_CASE							,						num_proc=processing_args.num_proc			)

      # And compute the embeddings
      lowerCAmelCase  						=       DPRContextEncoder.from_pretrained(rag_example_args.dpr_ctx_encoder_model_name			).to(device=SCREAMING_SNAKE_CASE			)
      lowerCAmelCase  						=       DPRContextEncoderTokenizerFast.from_pretrained(rag_example_args.dpr_ctx_encoder_model_name			)
      lowerCAmelCase  						=       Features(
          {"""text""": Value("""string"""			), """title""": Value("""string"""			), """embeddings""": Sequence(Value("""float32"""			)			)}			)  # optional, save as float32 instead of float64 to save space
      lowerCAmelCase  						=       dataset.map(
          partial(SCREAMING_SNAKE_CASE							,						ctx_encoder=SCREAMING_SNAKE_CASE							,						ctx_tokenizer=SCREAMING_SNAKE_CASE			)							,						batched=SCREAMING_SNAKE_CASE							,						batch_size=processing_args.batch_size							,						features=SCREAMING_SNAKE_CASE							,						)

      # And finally save your dataset
      lowerCAmelCase  						=       os.path.join(rag_example_args.output_dir							,						"""my_knowledge_dataset"""			)
      dataset.save_to_disk(SCREAMING_SNAKE_CASE			)
      # from datasets import load_from_disk
      # dataset = load_from_disk(passages_path)  # to reload the dataset

      ######################################
      logger.info("""Step 2 - Index the dataset"""			)
      ######################################

      # Let's use the Faiss implementation of HNSW for fast approximate nearest neighbor search
      lowerCAmelCase  						=       faiss.IndexHNSWFlat(index_hnsw_args.d							,						index_hnsw_args.m							,						faiss.METRIC_INNER_PRODUCT			)
      dataset.add_faiss_index("""embeddings"""							,						custom_index=SCREAMING_SNAKE_CASE			)

      # And save the index
      lowerCAmelCase  						=       os.path.join(rag_example_args.output_dir							,						"""my_knowledge_dataset_hnsw_index.faiss"""			)
      dataset.get_index("""embeddings"""			).save(SCREAMING_SNAKE_CASE			)
      # dataset.load_faiss_index("embeddings", index_path)  # to reload the index

@dataclass
class 		lowercase					:
      _SCREAMING_SNAKE_CASE					=      field(
          default=str(Path(_UpperCAmelCase					).parent / 'test_run' / 'dummy-kb' / 'my_knowledge_dataset.csv'					)     ,  metadata={'help': 'Path to a tab-separated csv file with columns \'title\' and \'text\''}     ,  )
      _SCREAMING_SNAKE_CASE					=      field(
          default=_UpperCAmelCase     ,  metadata={'help': 'Question that is passed as input to RAG. Default is \'What does Moses\' rod turn into ?\'.'}     ,  )
      _SCREAMING_SNAKE_CASE					=      field(
          default='facebook/rag-sequence-nq'     ,  metadata={'help': 'The RAG model to use. Either \'facebook/rag-sequence-nq\' or \'facebook/rag-token-nq\''}     ,  )
      _SCREAMING_SNAKE_CASE					=      field(
          default='facebook/dpr-ctx_encoder-multiset-base'     ,  metadata={
              'help': (
                  'The DPR context encoder model to use. Either \'facebook/dpr-ctx_encoder-single-nq-base\' or'
                  ' \'facebook/dpr-ctx_encoder-multiset-base\''
              )
          }     ,  )
      _SCREAMING_SNAKE_CASE					=      field(
          default=str(Path(_UpperCAmelCase					).parent / 'test_run' / 'dummy-kb'					)     ,  metadata={'help': 'Path to a directory where the dataset passages and the index will be saved'}     ,  )







@dataclass
class 		lowercase					:
      _SCREAMING_SNAKE_CASE					=      field(
          default=_UpperCAmelCase     ,  metadata={
              'help': 'The number of processes to use to split the documents into passages. Default is single process.'
          }     ,  )
      _SCREAMING_SNAKE_CASE					=      field(
          default=16     ,  metadata={
              'help': 'The batch size to use when computing the passages embeddings using the DPR context encoder.'
          }     ,  )







@dataclass
class 		lowercase					:
      _SCREAMING_SNAKE_CASE					=      field(
          default=768     ,  metadata={'help': 'The dimension of the embeddings to pass to the HNSW Faiss index.'}     ,  )
      _SCREAMING_SNAKE_CASE					=      field(
          default=128     ,  metadata={
              'help': (
                  'The number of bi-directional links created for every new element during the HNSW index construction.'
              )
          }     ,  )


if __name__ == "__main__":
       logging.basicConfig(level=logging.WARNING)
       logger.setLevel(logging.INFO)

       SCREAMING_SNAKE_CASE__					=   HfArgumentParser((RagExampleArguments, ProcessingArguments, IndexHnswArguments))
       SCREAMING_SNAKE_CASE__,      SCREAMING_SNAKE_CASE__,      SCREAMING_SNAKE_CASE__					=   parser.parse_args_into_dataclasses()
       with TemporaryDirectory() as tmp_dir:
              SCREAMING_SNAKE_CASE__					=   rag_example_args.output_dir or tmp_dir
              main(rag_example_args, processing_args, index_hnsw_args)











'''simple docstring'''





from math import sqrt




def lowerCAmelCase  (__A):



     """simple docstring"""



     assert isinstance(__A  ,	__A) and (
         number >= 0
     ), "'number' must been an int and positive"

     _a      =  True

     # 0 and 1 are none primes.
     if number <= 1:
          _a      =  False

     for divisor in range(2  ,	int(round(sqrt(__A))) + 1):
          # if 'number' divisible by 'divisor' then sets 'status'
          # of false and break up the loop.
          if number % divisor == 0:
               _a      =  False
               break

    # precondition
     assert isinstance(__A  ,	__A), "'status' must been from type bool"

     return status




def lowerCAmelCase  (__A):



     """simple docstring"""



     assert isinstance(__A  ,	__A) and (n > 2), "'N' must been an int and > 2"

     # beginList: contains all natural numbers from 2 up to N
     _a      =  list(range(2  ,	n + 1))

     _a      =  []  # this list will be returns.

     # actual sieve of erathostenes
     for i in range(len(__A)):
          for j in range(i + 1  ,	len(__A)):
               if (begin_list[i] != 0) and (begin_list[j] % begin_list[i] == 0):
                    _a      =  0

    # filters actual prime numbers.
     _a      =  [x for x in begin_list if x != 0]

     # precondition
     assert isinstance(__A  ,	__A), "'ans' must been from type list"

     return ans




def lowerCAmelCase  (__A):



     """simple docstring"""



     assert isinstance(__A  ,	__A) and (n > 2), "'N' must been an int and > 2"

     _a      =  []

     # iterates over all numbers between 2 up to N+1
     # if a number is prime then appends to list 'ans'
     for number in range(2  ,	n + 1):
          if is_prime(__A):
               ans.append(__A)

    # precondition
     assert isinstance(__A  ,	__A), "'ans' must been from type list"

     return ans




def lowerCAmelCase  (__A):



     """simple docstring"""



     assert isinstance(__A  ,	__A) and number >= 0, "'number' must been an int and >= 0"

     _a      =  []  # this list will be returns of the function.

     # potential prime number factors.

     _a      =  2

     _a      =  number

     if number == 0 or number == 1:
          ans.append(__A)

     # if 'number' not prime then builds the prime factorization of 'number'
     elif not is_prime(__A):
          while quotient != 1:
               if is_prime(__A) and (quotient % factor == 0):
                    ans.append(__A)
                    quotient /= factor
               else:
                    factor += 1

     else:
          ans.append(__A)

     # precondition
     assert isinstance(__A  ,	__A), "'ans' must been from type list"

     return ans




def lowerCAmelCase  (__A):



     """simple docstring"""



     assert isinstance(__A  ,	__A) and (
         number >= 0
     ), "'number' bust been an int and >= 0"

     _a      =  0

     # prime factorization of 'number'
     _a      =  prime_factorization(__A)

     _a      =  max(__A)

     # precondition
     assert isinstance(__A  ,	__A), "'ans' must been from type int"

     return ans




def lowerCAmelCase  (__A):



     """simple docstring"""



     assert isinstance(__A  ,	__A) and (
         number >= 0
     ), "'number' bust been an int and >= 0"

     _a      =  0

     # prime factorization of 'number'
     _a      =  prime_factorization(__A)

     _a      =  min(__A)

     # precondition
     assert isinstance(__A  ,	__A), "'ans' must been from type int"

     return ans




def lowerCAmelCase  (__A):



     """simple docstring"""



     assert isinstance(__A  ,	__A), "'number' must been an int"
     assert isinstance(number % 2 == 0  ,	__A), "compare bust been from type bool"

     return number % 2 == 0




def lowerCAmelCase  (__A):



     """simple docstring"""



     assert isinstance(__A  ,	__A), "'number' must been an int"
     assert isinstance(number % 2 != 0  ,	__A), "compare bust been from type bool"

     return number % 2 != 0




def lowerCAmelCase  (__A):



     """simple docstring"""



     assert (
         isinstance(__A  ,	__A) and (number > 2) and is_even(__A)
     ), "'number' must been an int, even and > 2"

     _a      =  []  # this list will returned

     # creates a list of prime numbers between 2 up to 'number'
     _a      =  get_prime_numbers(__A)
     _a      =  len(__A)

     # run variable for while-loops.
     _a      =  0
     _a      =  None

     # exit variable. for break up the loops
     _a      =  True

     while i < len_pn and loop:
          _a      =  i + 1

          while j < len_pn and loop:
               if prime_numbers[i] + prime_numbers[j] == number:
                    _a      =  False
                    ans.append(prime_numbers[i])
                    ans.append(prime_numbers[j])

               j += 1

          i += 1

     # precondition
     assert (
         isinstance(__A  ,	__A)
         and (len(__A) == 2)
         and (ans[0] + ans[1] == number)
         and is_prime(ans[0])
         and is_prime(ans[1])
     ), "'ans' must contains two primes. And sum of elements must been eq 'number'"

     return ans




def lowerCAmelCase  (__A  ,	__A):



     """simple docstring"""



     assert (
         isinstance(__A  ,	__A)
         and isinstance(__A  ,	__A)
         and (numbera >= 0)
         and (numbera >= 0)
     ), "'number1' and 'number2' must been positive integer."

     _a      =  0

     while numbera != 0:
          _a      =  numbera % numbera
          _a      =  numbera
          _a      =  rest

     # precondition
     assert isinstance(__A  ,	__A) and (
         numbera >= 0
     ), "'number' must been from type int and positive"

     return numbera




def lowerCAmelCase  (__A  ,	__A):



     """simple docstring"""



     assert (
         isinstance(__A  ,	__A)
         and isinstance(__A  ,	__A)
         and (numbera >= 1)
         and (numbera >= 1)
     ), "'number1' and 'number2' must been positive integer."

     _a      =  1  # actual answer that will be return.

     # for kgV (x,1)
     if numbera > 1 and numbera > 1:
          # builds the prime factorization of 'number1' and 'number2'
          _a      =  prime_factorization(__A)
          _a      =  prime_factorization(__A)

     elif numbera == 1 or numbera == 1:
          _a      =  []
          _a      =  []
          _a      =  max(__A  ,	__A)

     _a      =  0
     _a      =  0

     _a      =  []  # captured numbers int both 'primeFac1' and 'primeFac2'

     # iterates through primeFac1
     for n in prime_fac_a:
          if n not in done:
               if n in prime_fac_a:
                    _a      =  prime_fac_a.count(__A)
                    _a      =  prime_fac_a.count(__A)

                    for _ in range(max(__A  ,	__A)):
                         ans *= n

               else:
                    _a      =  prime_fac_a.count(__A)

                    for _ in range(__A):
                         ans *= n

               done.append(__A)

    # iterates through primeFac2
     for n in prime_fac_a:
          if n not in done:
               _a      =  prime_fac_a.count(__A)

               for _ in range(__A):
                    ans *= n

               done.append(__A)

    # precondition
     assert isinstance(__A  ,	__A) and (
         ans >= 0
     ), "'ans' must been from type int and positive"

     return ans




def lowerCAmelCase  (__A):



     """simple docstring"""



     assert isinstance(__A  ,	__A) and (n >= 0), "'number' must been a positive int"

     _a      =  0
     _a      =  2  # this variable holds the answer

     while index < n:
          index += 1

          ans += 1  # counts to the next number

          # if ans not prime then
          # runs to the next prime number.
          while not is_prime(__A):
               ans += 1

    # precondition
     assert isinstance(__A  ,	__A) and is_prime(
         __A), "'ans' must been a prime number and from type int"

     return ans




def lowerCAmelCase  (__A  ,	__A):



     """simple docstring"""



     assert (
         is_prime(__A) and is_prime(__A) and (p_number_a < p_number_a)
     ), "The arguments must been prime numbers and 'pNumber1' < 'pNumber2'"

     _a      =  p_number_a + 1  # jump to the next number

     _a      =  []  # this list will be returns.

     # if number is not prime then
     # fetch the next prime number.
     while not is_prime(__A):
          number += 1

     while number < p_number_a:
          ans.append(__A)

          number += 1

          # fetch the next prime number.
          while not is_prime(__A):
               number += 1

    # precondition
     assert (
         isinstance(__A  ,	__A)
         and ans[0] != p_number_a
         and ans[len(__A) - 1] != p_number_a
     ), "'ans' must been a list without the arguments"

     # 'ans' contains not 'pNumber1' and 'pNumber2' !
     return ans




def lowerCAmelCase  (__A):



     """simple docstring"""



     assert isinstance(__A  ,	__A) and (n >= 1), "'n' must been int and >= 1"

     _a      =  []  # will be returned.

     for divisor in range(1  ,	n + 1):
          if n % divisor == 0:
               ans.append(__A)

    # precondition
     assert ans[0] == 1 and ans[len(__A) - 1] == n, "Error in function getDivisiors(...)"

     return ans




def lowerCAmelCase  (__A):



     """simple docstring"""



     assert isinstance(__A  ,	__A) and (
         number > 1
     ), "'number' must been an int and >= 1"

     _a      =  get_divisors(__A)

     # precondition
     assert (
         isinstance(__A  ,	__A)
         and (divisors[0] == 1)
         and (divisors[len(__A) - 1] == number)
     ), "Error in help-function getDivisiors(...)"

     # summed all divisors up to 'number' (exclusive), hence [:-1]
     return sum(divisors[:-1]) == number




def lowerCAmelCase  (__A  ,	__A):



     """simple docstring"""



     assert (
         isinstance(__A  ,	__A)
         and isinstance(__A  ,	__A)
         and (denominator != 0)
     ), "The arguments must been from type int and 'denominator' != 0"

     # build the greatest common divisor of numerator and denominator.
     _a      =  gcd(abs(__A)  ,	abs(__A))

     # precondition
     assert (
         isinstance(__A  ,	__A)
         and (numerator % gcd_of_fraction == 0)
         and (denominator % gcd_of_fraction == 0)
     ), "Error in function gcd(...,...)"

     return (numerator // gcd_of_fraction, denominator // gcd_of_fraction)




def lowerCAmelCase  (__A):



     """simple docstring"""



     assert isinstance(__A  ,	__A) and (n >= 0), "'n' must been a int and >= 0"

     _a      =  1  # this will be return.

     for factor in range(1  ,	n + 1):
          ans *= factor

     return ans




def lowerCAmelCase  (__A):



     """simple docstring"""



     assert isinstance(__A  ,	__A) and (n >= 0), "'n' must been an int and >= 0"

     _a      =  0
     _a      =  1
     _a      =  1  # this will be return

     for _ in range(n - 1):
          _a      =  ans
          ans += fiba
          _a      =  tmp

     return ans



