





import os
import tempfile
import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch


if is_torch_available():
      import torch
      from torch import nn

      from transformers import (
          Adafactor,
          AdamW,
          get_constant_schedule,
          get_constant_schedule_with_warmup,
          get_cosine_schedule_with_warmup,
          get_cosine_with_hard_restarts_schedule_with_warmup,
          get_inverse_sqrt_schedule,
          get_linear_schedule_with_warmup,
          get_polynomial_decay_schedule_with_warmup,
      )






def 							_lowerCAmelCase (  _a   :					Tuple					,   _a   :					Dict=10			)	->			Any:
     lowerCAmelCase_					:       List[Any]    =		[]
     for _ in range(_a			):
          lrs.append(scheduler.get_lr()[0]			)
          scheduler.step()
     return lrs






def 							_lowerCAmelCase (  _a   :					Optional[Any]					,   _a   :					List[str]=10			)	->			List[str]:
     lowerCAmelCase_					:       Optional[Any]    =		[]
     for step in range(_a			):
          lrs.append(scheduler.get_lr()[0]			)
          scheduler.step()
          if step == num_steps // 2:
               with tempfile.TemporaryDirectory() as tmpdirname:
                    lowerCAmelCase_					:       List[Any]    =		os.path.join(_a					,   """schedule.bin"""			)
                    torch.save(scheduler.state_dict()					,   _a			)

                    lowerCAmelCase_					:       List[str]    =		torch.load(_a			)
                    scheduler.load_state_dict(_a			)
     return lrs





@require_torch
class      lowercase__    (							unittest.TestCase  ):







  def 	UpperCAmelCase__		(	self    ,						_lowercase    ,						_lowercase    ,						_lowercase						):
       self.assertEqual(len(_lowercase						)    ,						len(_lowercase						)						)
       for a, b in zip(_lowercase    ,						_lowercase						):
            self.assertAlmostEqual(_lowercase    ,						_lowercase    ,						delta=_lowercase						)







  def 	UpperCAmelCase__		(	self						):
       lowerCAmelCase_					:       Dict    =		torch.tensor([0.1, -0.2, -0.1]    ,						requires_grad=_lowercase						)
       lowerCAmelCase_					:       Optional[int]    =		torch.tensor([0.4, 0.2, -0.5]						)
       lowerCAmelCase_					:       List[Any]    =		nn.MSELoss()
       # No warmup, constant schedule, no gradient clipping
       lowerCAmelCase_					:       int    =		AdamW(params=[w]    ,						lr=2e-1    ,						weight_decay=0.0						)
       for _ in range(100						):
            lowerCAmelCase_					:       Dict    =		criterion(_lowercase    ,						_lowercase						)
            loss.backward()
            optimizer.step()
            w.grad.detach_()  # No zero_grad() function on simple tensors. we do it ourselves.
            w.grad.zero_()
       self.assertListAlmostEqual(w.tolist()    ,						[0.4, 0.2, -0.5]    ,						tol=1e-2						)







  def 	UpperCAmelCase__		(	self						):
       lowerCAmelCase_					:       List[Any]    =		torch.tensor([0.1, -0.2, -0.1]    ,						requires_grad=_lowercase						)
       lowerCAmelCase_					:       Optional[int]    =		torch.tensor([0.4, 0.2, -0.5]						)
       lowerCAmelCase_					:       Optional[int]    =		nn.MSELoss()
       # No warmup, constant schedule, no gradient clipping
       lowerCAmelCase_					:       List[str]    =		Adafactor(
           params=[w]    ,						lr=1e-2    ,						eps=(1e-30, 1e-3)    ,						clip_threshold=1.0    ,						decay_rate=-0.8    ,						betaa=_lowercase    ,						weight_decay=0.0    ,						relative_step=_lowercase    ,						scale_parameter=_lowercase    ,						warmup_init=_lowercase    ,						)
       for _ in range(1_000						):
            lowerCAmelCase_					:       int    =		criterion(_lowercase    ,						_lowercase						)
            loss.backward()
            optimizer.step()
            w.grad.detach_()  # No zero_grad() function on simple tensors. we do it ourselves.
            w.grad.zero_()
       self.assertListAlmostEqual(w.tolist()    ,						[0.4, 0.2, -0.5]    ,						tol=1e-2						)





@require_torch
class      lowercase__    (							unittest.TestCase  ):
  __UpperCamelCase	     =  nn.Linear(50     ,					50  ) if is_torch_available() else None
  __UpperCamelCase	     =  AdamW(m.parameters()     ,					lr=1_0.0  ) if is_torch_available() else None
  __UpperCamelCase	     =  10







  def 	UpperCAmelCase__		(	self    ,						_lowercase    ,						_lowercase    ,						_lowercase    ,						_lowercase=None						):
       self.assertEqual(len(_lowercase						)    ,						len(_lowercase						)						)
       for a, b in zip(_lowercase    ,						_lowercase						):
            self.assertAlmostEqual(_lowercase    ,						_lowercase    ,						delta=_lowercase    ,						msg=_lowercase						)







  def 	UpperCAmelCase__		(	self						):
       lowerCAmelCase_					:       Union[str, Any]    =		{"""num_warmup_steps""": 2, """num_training_steps""": 10}
       # schedulers doct format
       # function: (sched_args_dict, expected_learning_rates)
       lowerCAmelCase_					:       str    =		{
           get_constant_schedule: ({}, [10.0] * self.num_steps),
           get_constant_schedule_with_warmup: (
               {"""num_warmup_steps""": 4},
               [0.0, 2.5, 5.0, 7.5, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0],
           ),
           get_linear_schedule_with_warmup: (
               {**common_kwargs},
               [0.0, 5.0, 10.0, 8.75, 7.5, 6.25, 5.0, 3.75, 2.5, 1.25],
           ),
           get_cosine_schedule_with_warmup: (
               {**common_kwargs},
               [0.0, 5.0, 10.0, 9.61, 8.53, 6.91, 5.0, 3.08, 1.46, 0.38],
           ),
           get_cosine_with_hard_restarts_schedule_with_warmup: (
               {**common_kwargs, """num_cycles""": 2},
               [0.0, 5.0, 10.0, 8.53, 5.0, 1.46, 10.0, 8.53, 5.0, 1.46],
           ),
           get_polynomial_decay_schedule_with_warmup: (
               {**common_kwargs, """power""": 2.0, """lr_end""": 1e-7},
               [0.0, 5.0, 10.0, 7.656, 5.625, 3.906, 2.5, 1.406, 0.625, 0.156],
           ),
           get_inverse_sqrt_schedule: (
               {"""num_warmup_steps""": 2},
               [0.0, 5.0, 10.0, 8.165, 7.071, 6.325, 5.774, 5.345, 5.0, 4.714],
           ),
       }

       for scheduler_func, data in scheds.items():
            lowerCAmelCase_   ,  lowerCAmelCase_					:       List[str]    =		data

            lowerCAmelCase_					:       Dict    =		scheduler_func(self.optimizer    ,						**_lowercase						)
            self.assertEqual(len([scheduler.get_lr()[0]]						)    ,						1						)
            lowerCAmelCase_					:       Dict    =		unwrap_schedule(_lowercase    ,						self.num_steps						)
            self.assertListAlmostEqual(
                _lowercase    ,						_lowercase    ,						tol=1e-2    ,						msg=F'failed for {scheduler_func} in normal scheduler'    ,						)

            lowerCAmelCase_					:       List[Any]    =		scheduler_func(self.optimizer    ,						**_lowercase						)
            if scheduler_func.__name__ != "get_constant_schedule":
                 LambdaScheduleWrapper.wrap_scheduler(_lowercase						)  # wrap to test picklability of the schedule
            lowerCAmelCase_					:       List[str]    =		unwrap_and_save_reload_schedule(_lowercase    ,						self.num_steps						)
            self.assertListEqual(_lowercase    ,						_lowercase    ,						msg=F'failed for {scheduler_func} in save and reload'						)





class      lowercase__    :







  def __init__(	self    ,						_lowercase						):
       lowerCAmelCase_					:       Optional[int]    =		fn







  def __call__(	self    ,						*_lowercase    ,						**_lowercase						):
       return self.fn(*_lowercase    ,						**_lowercase						)







  @classmethod
  def 	UpperCAmelCase__		(	self    ,						_lowercase						):
       lowerCAmelCase_					:       List[Any]    =		list(map(self    ,						scheduler.lr_lambdas						)						)







def 							_lowerCAmelCase (  _a   :					int					,   _a   :					bool = False			)	->			bool:
     if n == 2:
          return True
     if not n % 2 or n < 2:
          return False
     if n > 5 and n % 10 not in (1, 3, 7, 9):  # can quickly check last digit
          return False
     if n > 3_31_70_44_06_46_79_88_73_85_96_19_81 and not allow_probable:
          raise ValueError(
              """Warning: upper bound of deterministic test is exceeded. """
              """Pass allow_probable=True to allow probabilistic test. """
              """A return value of True indicates a probable prime."""			)
     # array bounds provided by analysis
     lowerCAmelCase_					:       Optional[int]    =		[
         20_47,
         1_37_36_53,
         25_32_60_01,
         32_15_03_17_51,
         2_15_23_02_89_87_47,
         3_47_47_49_66_03_83,
         3_41_55_00_71_72_83_21,
         1,
         3_82_51_23_05_65_46_41_30_51,
         1,
         1,
         31_86_65_85_78_34_03_11_51_16_74_61,
         3_31_70_44_06_46_79_88_73_85_96_19_81,
     ]

     lowerCAmelCase_					:       Dict    =		[2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41]
     for idx, _p in enumerate(_a					,   1			):
          if n < _p:
               # then we have our last prime to check
               lowerCAmelCase_					:       str    =		primes[:idx]
               break
     lowerCAmelCase_   ,  lowerCAmelCase_					:       Optional[Any]    =		n - 1, 0
     # break up n -1 into a power of 2 (s) and
     # remaining odd component
     # essentially, solve for d * 2 ** s == n - 1
     while d % 2 == 0:
          d //= 2
          s += 1
     for prime in plist:
          lowerCAmelCase_					:       Tuple    =		False
          for r in range(_a			):
               lowerCAmelCase_					:       Tuple    =		pow(_a					,   d * 2**r					,   _a			)
               # see article for analysis explanation for m
               if (r == 0 and m == 1) or ((m + 1) % n == 0):
                    lowerCAmelCase_					:       List[Any]    =		True
                    # this loop will not determine compositeness
                    break
          if pr:
               continue
          # if pr is False, then the above loop never evaluated to true,
          # and the n MUST be composite
          return False
     return True






def 							_lowerCAmelCase (  )	->			None:
     assert not miller_rabin(5_61			)
     assert miller_rabin(5_63			)
     # 2047

     assert not miller_rabin(83_82_01			)
     assert miller_rabin(83_82_07			)
     # 1_373_653

     assert not miller_rabin(17_31_60_01			)
     assert miller_rabin(17_31_60_17			)
     # 25_326_001

     assert not miller_rabin(30_78_38_66_41			)
     assert miller_rabin(30_78_38_66_53			)
     # 3_215_031_751

     assert not miller_rabin(1_71_30_45_57_48_01			)
     assert miller_rabin(1_71_30_45_57_48_19			)
     # 2_152_302_898_747

     assert not miller_rabin(2_77_97_99_72_83_07			)
     assert miller_rabin(2_77_97_99_72_83_27			)
     # 3_474_749_660_383

     assert not miller_rabin(1_13_85_00_23_90_94_41			)
     assert miller_rabin(1_13_85_00_23_90_95_27			)
     # 341_550_071_728_321

     assert not miller_rabin(1_27_50_41_01_88_48_80_43_51			)
     assert miller_rabin(1_27_50_41_01_88_48_80_43_91			)
     # 3_825_123_056_546_413_051

     assert not miller_rabin(7_96_66_46_44_58_50_77_87_79_18_67			)
     assert miller_rabin(7_96_66_46_44_58_50_77_87_79_19_51			)
     # 318_665_857_834_031_151_167_461

     assert not miller_rabin(55_28_40_67_74_46_64_78_97_66_03_33			)
     assert miller_rabin(55_28_40_67_74_46_64_78_97_66_03_59			)
     # 3_317_044_064_679_887_385_961_981
     # upper limit for probabilistic test


if __name__ == "__main__":
      test_miller_rabin()
