






import unittest

from transformers import load_tool

from .test_tools_common import ToolTesterMixin


UpperCAmelCase__				   =		"\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted at teenagers.[2] After open-sourcing the model behind the chatbot, the company pivoted to focus on being a platform for machine learning.\n\nIn March 2021, Hugging Face raised $40 million in a Series B funding round.[3]\n\nOn April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model.[4] In 2022, the workshop concluded with the announcement of BLOOM, a multilingual large language model with 176 billion parameters.[5]\n"






class 		lowercase_					(	unittest.TestCase ,  lowercase   ):






      '''simple docstring'''




      def       __lowerCAmelCase					(      self      :						int  )    ->Tuple:




       """simple docstring"""


       a		  =      load_tool('''text-question-answering'''  )
       self.tool.setup()
       a		  =      load_tool('''text-question-answering''' ,					remote=__UpperCAmelCase  )







      def       __lowerCAmelCase					(      self      :						Optional[int]  )    ->Optional[int]:




       """simple docstring"""


       a		  =      self.tool(__UpperCAmelCase ,					'''What did Hugging Face do in April 2021?'''  )
       self.assertEqual(__UpperCAmelCase ,					'''launched the BigScience Research Workshop'''  )







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




       """simple docstring"""


       a		  =      self.remote_tool(__UpperCAmelCase ,					'''What did Hugging Face do in April 2021?'''  )
       self.assertEqual(__UpperCAmelCase ,					'''launched the BigScience Research Workshop'''  )







      def       __lowerCAmelCase					(      self      :						Dict  )    ->Optional[int]:




       """simple docstring"""


       a		  =      self.tool(text=__UpperCAmelCase ,					question='''What did Hugging Face do in April 2021?'''  )
       self.assertEqual(__UpperCAmelCase ,					'''launched the BigScience Research Workshop'''  )







      def       __lowerCAmelCase					(      self      :						int  )    ->Optional[Any]:




       """simple docstring"""


       a		  =      self.remote_tool(text=__UpperCAmelCase ,					question='''What did Hugging Face do in April 2021?'''  )
       self.assertEqual(__UpperCAmelCase ,					'''launched the BigScience Research Workshop'''  )








from __future__ import annotations

from math import gcd

def 					UpperCAmelCase_							(      __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.
            SCREAMING_SNAKE_CASE_							=			seed
            SCREAMING_SNAKE_CASE_							=			seed

            while True:
                  # At each iteration, the tortoise moves one step and the hare moves two.
                  SCREAMING_SNAKE_CASE_							=			rand_fn(__UpperCAmelCase			,			__UpperCAmelCase			,			__UpperCAmelCase							)
                  SCREAMING_SNAKE_CASE_							=			rand_fn(__UpperCAmelCase			,			__UpperCAmelCase			,			__UpperCAmelCase							)
                  SCREAMING_SNAKE_CASE_							=			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``.
                  SCREAMING_SNAKE_CASE_							=			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.
            SCREAMING_SNAKE_CASE_							=			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

   lowerCamelCase__ :   List[str]					=							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',
   )
   lowerCamelCase__ :   Tuple					=							parser.parse_args()

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