





import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch

import numpy as np
from datasets import Dataset

from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAME, RealmRetriever
from transformers.models.realm.tokenization_realm import VOCAB_FILES_NAMES, RealmTokenizer






class 					lowercase__ (			__lowerCamelCase       ):

   '''simple docstring'''


   def    UpperCamelCase__						(					self							)				->   List[Any]:






       """simple docstring"""
       UpperCamelCase__							:       Dict      =   tempfile.mkdtemp()
       UpperCamelCase__							:       str      =   5

       # Realm tok
       UpperCamelCase__							:       Tuple      =   [
           '''[UNK]''',
           '''[CLS]''',
           '''[SEP]''',
           '''[PAD]''',
           '''[MASK]''',
           '''test''',
           '''question''',
           '''this''',
           '''is''',
           '''the''',
           '''first''',
           '''second''',
           '''third''',
           '''fourth''',
           '''fifth''',
           '''record''',
           '''want''',
           '''##want''',
           '''##ed''',
           '''wa''',
           '''un''',
           '''runn''',
           '''##ing''',
           ''',''',
           '''low''',
           '''lowest''',
       ]
       UpperCamelCase__							:       str      =   os.path.join(self.tmpdirname,	'''realm_tokenizer'''							)
       os.makedirs(__magic_name__,	exist_ok=__magic_name__							)
       UpperCamelCase__							:       List[str]      =   os.path.join(__magic_name__,	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]							)							)

       UpperCamelCase__							:       int      =   os.path.join(self.tmpdirname,	'''realm_block_records'''							)
       os.makedirs(__magic_name__,	exist_ok=__magic_name__							)




   def    UpperCamelCase__						(					self							)				->   RealmTokenizer:






       """simple docstring"""
       return RealmTokenizer.from_pretrained(os.path.join(self.tmpdirname,	'''realm_tokenizer'''							)							)




   def    UpperCamelCase__						(					self							)				->   List[str]:






       """simple docstring"""
       shutil.rmtree(self.tmpdirname							)




   def    UpperCamelCase__						(					self							)				->   Any:






       """simple docstring"""
       UpperCamelCase__							:       List[Any]      =   RealmConfig(num_block_records=self.num_block_records							)
       return config




   def    UpperCamelCase__						(					self							)				->   List[str]:






       """simple docstring"""
       UpperCamelCase__							:       int      =   Dataset.from_dict(
           {
               '''id''': ['''0''', '''1'''],
               '''question''': ['''foo''', '''bar'''],
               '''answers''': [['''Foo''', '''Bar'''], ['''Bar''']],
           }							)
       return dataset




   def    UpperCamelCase__						(					self							)				->   Union[str, Any]:






       """simple docstring"""
       UpperCamelCase__							:       Dict      =   np.array(
           [
               b'''This is the first record''',
               b'''This is the second record''',
               b'''This is the third record''',
               b'''This is the fourth record''',
               b'''This is the fifth record''',
               b'''This is a longer longer longer record''',
           ],	dtype=__magic_name__,	)
       return block_records




   def    UpperCamelCase__						(					self							)				->   List[Any]:






       """simple docstring"""
       UpperCamelCase__							:       str      =   RealmRetriever(
           block_records=self.get_dummy_block_records(),	tokenizer=self.get_tokenizer(),	)
       return retriever




   def    UpperCamelCase__						(					self							)				->   Union[str, Any]:






       """simple docstring"""
       UpperCamelCase__							:       str      =   self.get_config()
       UpperCamelCase__							:       int      =   self.get_dummy_retriever()
       UpperCamelCase__							:       int      =   retriever.tokenizer

       UpperCamelCase__							:       Optional[Any]      =   np.array([0, 3],	dtype='''long'''							)
       UpperCamelCase__							:       int      =   tokenizer(['''Test question''']							).input_ids
       UpperCamelCase__							:       List[str]      =   tokenizer(
           ['''the fourth'''],	add_special_tokens=__magic_name__,	return_token_type_ids=__magic_name__,	return_attention_mask=__magic_name__,	).input_ids
       UpperCamelCase__							:       str      =   config.reader_seq_len

       UpperCamelCase__     ,UpperCamelCase__     ,UpperCamelCase__     ,UpperCamelCase__							:       str      =   retriever(
           __magic_name__,	__magic_name__,	answer_ids=__magic_name__,	max_length=__magic_name__,	return_tensors='''np'''							)

       self.assertEqual(len(__magic_name__							),	2							)
       self.assertEqual(len(__magic_name__							),	2							)
       self.assertEqual(len(__magic_name__							),	2							)
       self.assertEqual(concat_inputs.input_ids.shape,	(2, 10)							)
       self.assertEqual(concat_inputs.attention_mask.shape,	(2, 10)							)
       self.assertEqual(concat_inputs.token_type_ids.shape,	(2, 10)							)
       self.assertEqual(concat_inputs.special_tokens_mask.shape,	(2, 10)							)
       self.assertEqual(
           tokenizer.convert_ids_to_tokens(concat_inputs.input_ids[0]							),	['''[CLS]''', '''test''', '''question''', '''[SEP]''', '''this''', '''is''', '''the''', '''first''', '''record''', '''[SEP]'''],	)
       self.assertEqual(
           tokenizer.convert_ids_to_tokens(concat_inputs.input_ids[1]							),	['''[CLS]''', '''test''', '''question''', '''[SEP]''', '''this''', '''is''', '''the''', '''fourth''', '''record''', '''[SEP]'''],	)




   def    UpperCamelCase__						(					self							)				->   List[str]:






       """simple docstring"""
       UpperCamelCase__							:       str      =   self.get_config()
       UpperCamelCase__							:       Dict      =   self.get_dummy_retriever()
       UpperCamelCase__							:       Optional[Any]      =   retriever.tokenizer

       UpperCamelCase__							:       List[str]      =   np.array([0, 3, 5],	dtype='''long'''							)
       UpperCamelCase__							:       Dict      =   tokenizer(['''Test question''']							).input_ids
       UpperCamelCase__							:       Dict      =   tokenizer(
           ['''the fourth''', '''longer longer'''],	add_special_tokens=__magic_name__,	return_token_type_ids=__magic_name__,	return_attention_mask=__magic_name__,	).input_ids
       UpperCamelCase__							:       Tuple      =   config.reader_seq_len

       UpperCamelCase__     ,UpperCamelCase__     ,UpperCamelCase__     ,UpperCamelCase__							:       Tuple      =   retriever(
           __magic_name__,	__magic_name__,	answer_ids=__magic_name__,	max_length=__magic_name__,	return_tensors='''np'''							)

       self.assertEqual([False, True, True],	__magic_name__							)
       self.assertEqual([[-1, -1, -1], [6, -1, -1], [6, 7, 8]],	__magic_name__							)
       self.assertEqual([[-1, -1, -1], [7, -1, -1], [7, 8, 9]],	__magic_name__							)




   def    UpperCamelCase__						(					self							)				->   str:






       """simple docstring"""
       UpperCamelCase__							:       Dict      =   self.get_dummy_retriever()
       retriever.save_pretrained(os.path.join(self.tmpdirname,	'''realm_block_records'''							)							)

       # Test local path
       UpperCamelCase__							:       Union[str, Any]      =   retriever.from_pretrained(os.path.join(self.tmpdirname,	'''realm_block_records'''							)							)
       self.assertEqual(retriever.block_records[0],	b'''This is the first record'''							)

       # Test mocked remote path
       with patch('''transformers.models.realm.retrieval_realm.hf_hub_download'''							) as mock_hf_hub_download:
           UpperCamelCase__							:       str      =   os.path.join(
               os.path.join(self.tmpdirname,	'''realm_block_records'''							),	_REALM_BLOCK_RECORDS_FILENAME							)
           UpperCamelCase__							:       Any      =   RealmRetriever.from_pretrained('''google/realm-cc-news-pretrained-openqa'''							)

       self.assertEqual(retriever.block_records[0],	b'''This is the first record'''							)








from __future__ import annotations

from math import gcd




def 	lowerCAmelCase_					(						__UpperCAmelCase:    int	,     __UpperCAmelCase:    int = 2	,     __UpperCAmelCase:    int = 1	,     __UpperCAmelCase:    int = 3	,     )   ->			int | None:
    # A value less than 2 can cause an infinite loop in the algorithm.
    if num < 2:
        raise ValueError('''The input value cannot be less than 2'''   )

    # Because of the relationship between ``f(f(x))`` and ``f(x)``, this
    # algorithm struggles to find factors that are divisible by two.
    # As a workaround, we specifically check for two and even inputs.
    #   See: https://math.stackexchange.com/a/2856214/165820
    if num > 2 and num % 2 == 0:
        return 2

    # Pollard's Rho algorithm requires a function that returns pseudorandom
    # values between 0 <= X < ``num``.  It doesn't need to be random in the
    # sense that the output value is cryptographically secure or difficult
    # to calculate, it only needs to be random in the sense that all output
    # values should be equally likely to appear.
    # For this reason, Pollard suggested using ``f(x) = (x**2 - 1) % num``
    # However, the success of Pollard's algorithm isn't guaranteed and is
    # determined in part by the initial seed and the chosen random function.
    # To make retries easier, we will instead use ``f(x) = (x**2 + C) % num``
    # where ``C`` is a value that we can modify between each attempt.
    def rand_fn(__UpperCAmelCase:    int	,     __UpperCAmelCase:    int	,     __UpperCAmelCase:    int   ) -> int:
        return (pow(__UpperCAmelCase	,     2   ) + step) % modulus

    for _ in range(__UpperCAmelCase   ):
        # These track the position within the cycle detection logic.
        UpperCamelCase__							:       List[Any]      =   seed
        UpperCamelCase__							:       List[str]      =   seed

        while True:
            # At each iteration, the tortoise moves one step and the hare moves two.
            UpperCamelCase__							:       Optional[int]      =   rand_fn(__UpperCAmelCase	,     __UpperCAmelCase	,     __UpperCAmelCase   )
            UpperCamelCase__							:       List[str]      =   rand_fn(__UpperCAmelCase	,     __UpperCAmelCase	,     __UpperCAmelCase   )
            UpperCamelCase__							:       Optional[int]      =   rand_fn(__UpperCAmelCase	,     __UpperCAmelCase	,     __UpperCAmelCase   )

            # At some point both the tortoise and the hare will enter a cycle whose
            # length ``p`` is a divisor of ``num``.  Once in that cycle, at some point
            # the tortoise and hare will end up on the same value modulo ``p``.
            # We can detect when this happens because the position difference between
            # the tortoise and the hare will share a common divisor with ``num``.
            UpperCamelCase__							:       Optional[int]      =   gcd(hare - tortoise	,     __UpperCAmelCase   )

            if divisor == 1:
                # No common divisor yet, just keep searching.
                continue
            else:
                # We found a common divisor!
                if divisor == num:
                    # Unfortunately, the divisor is ``num`` itself and is useless.
                    break
                else:
                    # The divisor is a nontrivial factor of ``num``!
                    return divisor

        # If we made it here, then this attempt failed.
        # We need to pick a new starting seed for the tortoise and hare
        # in addition to a new step value for the random function.
        # To keep this example implementation deterministic, the
        # new values will be generated based on currently available
        # values instead of using something like ``random.randint``.

        # We can use the hare's position as the new seed.
        # This is actually what Richard Brent's the "optimized" variant does.
        UpperCamelCase__							:       List[str]      =   hare

        # The new step value for the random function can just be incremented.
        # At first the results will be similar to what the old function would
        # have produced, but the value will quickly diverge after a bit.
        step += 1

    # We haven't found a divisor within the requested number of attempts.
    # We were unlucky or ``num`` itself is actually prime.
    return None


if __name__ == "__main__":
  import argparse

  UpperCAmelCase_  							=				argparse.ArgumentParser()
  parser.add_argument(
      'num',
      type=int,
      help='The value to find a divisor of',
  )
  parser.add_argument(
      '--attempts',
      type=int,
      default=3,
      help='The number of attempts before giving up',
  )
  UpperCAmelCase_  							=				parser.parse_args()

  UpperCAmelCase_  							=				pollard_rho(args.num, attempts=args.attempts)
  if divisor is None:
    print(F'''{args.num} is probably prime''')
  else:
    UpperCAmelCase_  							=				args.num // divisor
    print(F'''{args.num} = {divisor} * {quotient}''')

