
'''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 snake_case_     (					lowercase__   ,       lowercase__=1_0		):
  UpperCAmelCase__      :					List[str]				       =							[]
  for _ in range(lowercase__		):
    lrs.append(scheduler.get_lr()[0]		)
    scheduler.step()
  return lrs







def snake_case_     (					lowercase__   ,       lowercase__=1_0		):
  UpperCAmelCase__      :					Optional[Any]				       =							[]
  for step in range(lowercase__		):
    lrs.append(scheduler.get_lr()[0]		)
    scheduler.step()
    if step == num_steps // 2:
      with tempfile.TemporaryDirectory() as tmpdirname:
        UpperCAmelCase__      :					Union[str, Any]				       =							os.path.join(lowercase__   ,       "schedule.bin"		)
        torch.save(scheduler.state_dict()   ,       lowercase__		)

        UpperCAmelCase__      :					List[str]				       =							torch.load(lowercase__		)
        scheduler.load_state_dict(lowercase__		)
  return lrs






@require_torch
class 							UpperCAmelCase_							(    unittest.TestCase				):

 '''simple docstring'''







 def 							UpperCamelCase  (					self		:  Optional[Any]			,				snake_case__		:  Optional[int]			,				snake_case__		:  Optional[Any]			,				snake_case__		:  Optional[Any] ):



   '''simple docstring'''




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







 def 							UpperCamelCase  (					self		:  Optional[Any] ):



   '''simple docstring'''




   UpperCAmelCase__      :					Tuple				       =							torch.tensor([0.1, -0.2, -0.1]			,				requires_grad=snake_case__ )
   UpperCAmelCase__      :					List[str]				       =							torch.tensor([0.4, 0.2, -0.5] )
   UpperCAmelCase__      :					int				       =							nn.MSELoss()
   # No warmup, constant schedule, no gradient clipping
   UpperCAmelCase__      :					str				       =							AdamW(params=[w]			,				lr=2e-1			,				weight_decay=0.0 )
   for _ in range(1_00 ):
     UpperCAmelCase__      :					int				       =							criterion(snake_case__			,				snake_case__ )
     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'''




   UpperCAmelCase__      :					Union[str, Any]				       =							torch.tensor([0.1, -0.2, -0.1]			,				requires_grad=snake_case__ )
   UpperCAmelCase__      :					List[str]				       =							torch.tensor([0.4, 0.2, -0.5] )
   UpperCAmelCase__      :					List[str]				       =							nn.MSELoss()
   # No warmup, constant schedule, no gradient clipping
   UpperCAmelCase__      :					List[str]				       =							Adafactor(
       params=[w]			,				lr=1e-2			,				eps=(1e-30, 1e-3)			,				clip_threshold=1.0			,				decay_rate=-0.8			,				betaa=snake_case__			,				weight_decay=0.0			,				relative_step=snake_case__			,				scale_parameter=snake_case__			,				warmup_init=snake_case__			,				)
   for _ in range(10_00 ):
     UpperCAmelCase__      :					List[Any]				       =							criterion(snake_case__			,				snake_case__ )
     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 							UpperCAmelCase_							(    unittest.TestCase				):

 '''simple docstring'''
 lowercase_					:    Optional[int]				=							nn.Linear(50					,				50				) if is_torch_available() else None
 lowercase_					:    int				=							AdamW(m.parameters()					,				lr=10.0				) if is_torch_available() else None
 lowercase_					:    Dict				=							10







 def 							UpperCamelCase  (					self		:  Dict			,				snake_case__		:  Optional[Any]			,				snake_case__		:  str			,				snake_case__		:  int			,				snake_case__		:  str=None ):



   '''simple docstring'''




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







 def 							UpperCamelCase  (					self		:  int ):



   '''simple docstring'''




   UpperCAmelCase__      :					List[Any]				       =							{"num_warmup_steps": 2, "num_training_steps": 10}
   # schedulers doct format
   # function: (sched_args_dict, expected_learning_rates)
   UpperCAmelCase__      :					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():
     UpperCAmelCase__       ,			UpperCAmelCase__      :					List[Any]				       =							data

     UpperCAmelCase__      :					Optional[Any]				       =							scheduler_func(self.optimizer			,				**snake_case__ )
     self.assertEqual(len([scheduler.get_lr()[0]] )			,				1 )
     UpperCAmelCase__      :					Optional[int]				       =							unwrap_schedule(snake_case__			,				self.num_steps )
     self.assertListAlmostEqual(
         snake_case__			,				snake_case__			,				tol=1e-2			,				msg=F"""failed for {scheduler_func} in normal scheduler"""			,				)

     UpperCAmelCase__      :					Tuple				       =							scheduler_func(self.optimizer			,				**snake_case__ )
     if scheduler_func.__name__ != "get_constant_schedule":
       LambdaScheduleWrapper.wrap_scheduler(snake_case__ )  # wrap to test picklability of the schedule
     UpperCAmelCase__      :					Tuple				       =							unwrap_and_save_reload_schedule(snake_case__			,				self.num_steps )
     self.assertListEqual(snake_case__			,				snake_case__			,				msg=F"""failed for {scheduler_func} in save and reload""" )






class 							UpperCAmelCase_							:

 '''simple docstring'''







 def __init__(					self		:  str			,				snake_case__		:  List[str] ):



   '''simple docstring'''




   UpperCAmelCase__      :					Dict				       =							fn







 def __call__(					self		:  List[str]			,				*snake_case__		:  List[Any]			,				**snake_case__		:  Dict ):



   '''simple docstring'''




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







 @classmethod
 def 							UpperCamelCase  (					self		:  int			,				snake_case__		:  List[str] ):



   '''simple docstring'''




   UpperCAmelCase__      :					int				       =							list(map(self			,				scheduler.lr_lambdas ) )





'''simple docstring'''





SCREAMING_SNAKE_CASE     =       {
    """meter""": """m""",
    """kilometer""": """km""",
    """megametre""": """Mm""",
    """gigametre""": """Gm""",
    """terametre""": """Tm""",
    """petametre""": """Pm""",
    """exametre""": """Em""",
    """zettametre""": """Zm""",
    """yottametre""": """Ym""",
}
# Exponent of the factor(meter)
SCREAMING_SNAKE_CASE     =       {
    """m""": 0,
    """km""": 3,
    """Mm""": 6,
    """Gm""": 9,
    """Tm""": 1_2,
    """Pm""": 1_5,
    """Em""": 1_8,
    """Zm""": 2_1,
    """Ym""": 2_4,
}







def snake_case_     (					lowercase__   ,       lowercase__   ,       lowercase__		):
  UpperCAmelCase__      :					str				       =							from_type.lower().strip("s"		)
  UpperCAmelCase__      :					Any				       =							to_type.lower().strip("s"		)

  UpperCAmelCase__      :					Union[str, Any]				       =							UNIT_SYMBOL.get(lowercase__   ,       lowercase__		)
  UpperCAmelCase__      :					Any				       =							UNIT_SYMBOL.get(lowercase__   ,       lowercase__		)

  if from_sanitized not in METRIC_CONVERSION:
    UpperCAmelCase__      :					str				       =							(
        F"""Invalid 'from_type' value: {from_type!r}.\n"""
        F"""Conversion abbreviations are: {", ".join(lowercase__		)}"""
    )
    raise ValueError(lowercase__		)
  if to_sanitized not in METRIC_CONVERSION:
    UpperCAmelCase__      :					List[str]				       =							(
        F"""Invalid 'to_type' value: {to_type!r}.\n"""
        F"""Conversion abbreviations are: {", ".join(lowercase__		)}"""
    )
    raise ValueError(lowercase__		)
  UpperCAmelCase__      :					Optional[int]				       =							METRIC_CONVERSION[from_sanitized]
  UpperCAmelCase__      :					str				       =							METRIC_CONVERSION[to_sanitized]
  UpperCAmelCase__      :					Tuple				       =							1

  if from_exponent > to_exponent:
    UpperCAmelCase__      :					Tuple				       =							from_exponent - to_exponent
  else:
    UpperCAmelCase__      :					Optional[int]				       =							-(to_exponent - from_exponent)

  return value * pow(1_0   ,       lowercase__		)


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

      testmod()



