





'''simple docstring'''

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    _a    (							lowerCAmelCase_			,      lowerCAmelCase_=10	):





      """simple docstring"""



      _snake_case		:	Tuple					     =     []
      for _ in range(lowerCAmelCase_	):
            lrs.append(scheduler.get_lr()[0]	)
            scheduler.step()
      return lrs




def    _a    (							lowerCAmelCase_			,      lowerCAmelCase_=10	):





      """simple docstring"""



      _snake_case		:	Optional[int]					     =     []
      for step in range(lowerCAmelCase_	):
            lrs.append(scheduler.get_lr()[0]	)
            scheduler.step()
            if step == num_steps // 2:
                  with tempfile.TemporaryDirectory() as tmpdirname:
                        _snake_case		:	Any					     =     os.path.join(lowerCAmelCase_			,      '''schedule.bin'''	)
                        torch.save(scheduler.state_dict()			,      lowerCAmelCase_	)

                        _snake_case		:	Optional[int]					     =     torch.load(lowerCAmelCase_	)
                        scheduler.load_state_dict(lowerCAmelCase_	)
      return lrs





@require_torch
class lowerCamelCase						(unittest.TestCase					):







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






        """simple docstring"""





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







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






        """simple docstring"""





        _snake_case		:	Union[str, Any]					     =     torch.tensor([0.1, -0.2, -0.1]     ,     requires_grad=lowercase__		)
        _snake_case		:	List[str]					     =     torch.tensor([0.4, 0.2, -0.5]		)
        _snake_case		:	Optional[Any]					     =     nn.MSELoss()
        # No warmup, constant schedule, no gradient clipping
        _snake_case		:	List[Any]					     =     AdamW(params=[w]     ,     lr=2E-1     ,     weight_decay=0.0		)
        for _ in range(100		):
              _snake_case		:	str					     =     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		)		->						str:






        """simple docstring"""





        _snake_case		:	Tuple					     =     torch.tensor([0.1, -0.2, -0.1]     ,     requires_grad=lowercase__		)
        _snake_case		:	Optional[Any]					     =     torch.tensor([0.4, 0.2, -0.5]		)
        _snake_case		:	Optional[int]					     =     nn.MSELoss()
        # No warmup, constant schedule, no gradient clipping
        _snake_case		:	int					     =     Adafactor(
            params=[w]     ,     lr=1E-2     ,     eps=(1E-3_0, 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		):
              _snake_case		:	Optional[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 lowerCamelCase						(unittest.TestCase					):
  _lowercase  :	Dict       					=				nn.Linear(50						,      50					) if is_torch_available() else None
  _lowercase  :	Optional[Any]       					=				AdamW(m.parameters()						,      lr=1_0.0					) if is_torch_available() else None
  _lowercase  :	Union[str, Any]       					=				10







  def 				UpperCAmelCase_				(		self     ,     lowercase__     ,     lowercase__     ,     lowercase__     ,     lowercase__=None		)		->						Optional[int]:






        """simple docstring"""





        self.assertEqual(len(lowercase__		)     ,     len(lowercase__		)		)
        for a, b in zip(lowercase__     ,     lowercase__		):
              self.assertAlmostEqual(lowercase__     ,     lowercase__     ,     delta=lowercase__     ,     msg=lowercase__		)







  def 				UpperCAmelCase_				(		self		)		->						Dict:






        """simple docstring"""





        _snake_case		:	str					     =     {'''num_warmup_steps''': 2, '''num_training_steps''': 10}
        # schedulers doct format
        # function: (sched_args_dict, expected_learning_rates)
        _snake_case		:	Optional[int]					     =     {
            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():
              _snake_case     ,							_snake_case		:	Any					     =     data

              _snake_case		:	str					     =     scheduler_func(self.optimizer     ,     **lowercase__		)
              self.assertEqual(len([scheduler.get_lr()[0]]		)     ,     1		)
              _snake_case		:	Union[str, Any]					     =     unwrap_schedule(lowercase__     ,     self.num_steps		)
              self.assertListAlmostEqual(
                  lowercase__     ,     lowercase__     ,     tol=1E-2     ,     msg=F'''failed for {scheduler_func} in normal scheduler'''     ,     )

              _snake_case		:	Union[str, Any]					     =     scheduler_func(self.optimizer     ,     **lowercase__		)
              if scheduler_func.__name__ != "get_constant_schedule":
                    LambdaScheduleWrapper.wrap_scheduler(lowercase__		)  # wrap to test picklability of the schedule
              _snake_case		:	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 lowerCamelCase						:







  def __init__(		self     ,     lowercase__		)		->						str:






        """simple docstring"""





        _snake_case		:	str					     =     fn







  def __call__(		self     ,     *lowercase__     ,     **lowercase__		)		->						str:






        """simple docstring"""





        return self.fn(*lowercase__     ,     **lowercase__		)







  @classmethod
  def 				UpperCAmelCase_				(		self     ,     lowercase__		)		->						Dict:






        """simple docstring"""





        _snake_case		:	Union[str, Any]					     =     list(map(self     ,     scheduler.lr_lambdas		)		)









'''simple docstring'''

from __future__ import annotations




def    _a    (							lowerCAmelCase_			,      lowerCAmelCase_ = None			,      lowerCAmelCase_ = None	):





      """simple docstring"""



      if start is None:
            _snake_case		:	Optional[Any]					     =     0

      if end is None:
            _snake_case		:	Any					     =     len(lowerCAmelCase_	) - 1

      if start >= end:
            return

      _snake_case		:	Optional[Any]					     =     (start + end) // 2

      slowsort(lowerCAmelCase_			,      lowerCAmelCase_			,      lowerCAmelCase_	)
      slowsort(lowerCAmelCase_			,      mid + 1			,      lowerCAmelCase_	)

      if sequence[end] < sequence[mid]:
            _snake_case     ,							_snake_case		:	int					     =     sequence[mid], sequence[end]

      slowsort(lowerCAmelCase_			,      lowerCAmelCase_			,      end - 1	)


if __name__ == "__main__":
   from doctest import testmod

   testmod()


