



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 	SCREAMING_SNAKE_CASE_							(	_snake_case	:Union[str, Any]	,   _snake_case	:str=10				)  ->     Optional[Any]:
   _A      =       []
   for _ in range(_snake_case				):
      lrs.append(scheduler.get_lr()[0]				)
      scheduler.step()
   return lrs

def 	SCREAMING_SNAKE_CASE_							(	_snake_case	:List[str]	,   _snake_case	:Dict=10				)  ->     Optional[int]:
   _A      =       []
   for step in range(_snake_case				):
      lrs.append(scheduler.get_lr()[0]				)
      scheduler.step()
      if step == num_steps // 2:
         with tempfile.TemporaryDirectory() as tmpdirname:
            _A      =       os.path.join(_snake_case	,   '''schedule.bin'''				)
            torch.save(scheduler.state_dict()	,   _snake_case				)

            _A      =       torch.load(_snake_case				)
            scheduler.load_state_dict(_snake_case				)
   return lrs


@require_torch
class 	lowerCamelCase__	(       unittest.TestCase):



 """simple docstring"""

 def     snake_case_      (    self					:					Optional[int]			,						__lowerCAmelCase					:					Tuple			,						__lowerCAmelCase					:					str			,						__lowerCAmelCase					:					Optional[int]      )   ->	Any:
    self.assertEqual(len(__lowerCAmelCase      )			,						len(__lowerCAmelCase      )      )
    for a, b in zip(__lowerCAmelCase			,						__lowerCAmelCase      ):
       self.assertAlmostEqual(__lowerCAmelCase			,						__lowerCAmelCase			,						delta=__lowerCAmelCase      )

 def     snake_case_      (    self					:					int      )   ->	Union[str, Any]:
    _A      =       torch.tensor([0.1, -0.2, -0.1]			,						requires_grad=__lowerCAmelCase      )
    _A      =       torch.tensor([0.4, 0.2, -0.5]      )
    _A      =       nn.MSELoss()
    # No warmup, constant schedule, no gradient clipping
    _A      =       AdamW(params=[w]			,						lr=2E-1			,						weight_decay=0.0      )
    for _ in range(1_00      ):
       _A      =       criterion(__lowerCAmelCase			,						__lowerCAmelCase      )
       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     snake_case_      (    self					:					int      )   ->	Union[str, Any]:
    _A      =       torch.tensor([0.1, -0.2, -0.1]			,						requires_grad=__lowerCAmelCase      )
    _A      =       torch.tensor([0.4, 0.2, -0.5]      )
    _A      =       nn.MSELoss()
    # No warmup, constant schedule, no gradient clipping
    _A      =       Adafactor(
        params=[w]			,						lr=1E-2			,						eps=(1E-30, 1E-3)			,						clip_threshold=1.0			,						decay_rate=-0.8			,						betaa=__lowerCAmelCase			,						weight_decay=0.0			,						relative_step=__lowerCAmelCase			,						scale_parameter=__lowerCAmelCase			,						warmup_init=__lowerCAmelCase			,						)
    for _ in range(10_00      ):
       _A      =       criterion(__lowerCAmelCase			,						__lowerCAmelCase      )
       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):



 """simple docstring"""

 a__					: Optional[Any] =  nn.Linear(50							,  50) if is_torch_available() else None
 a__					: Dict =  AdamW(m.parameters()							,  lr=10.0) if is_torch_available() else None
 a__					: List[Any] =  10

 def     snake_case_      (    self					:					Union[str, Any]			,						__lowerCAmelCase					:					List[str]			,						__lowerCAmelCase					:					Any			,						__lowerCAmelCase					:					Any			,						__lowerCAmelCase					:					List[Any]=None      )   ->	List[Any]:
    self.assertEqual(len(__lowerCAmelCase      )			,						len(__lowerCAmelCase      )      )
    for a, b in zip(__lowerCAmelCase			,						__lowerCAmelCase      ):
       self.assertAlmostEqual(__lowerCAmelCase			,						__lowerCAmelCase			,						delta=__lowerCAmelCase			,						msg=__lowerCAmelCase      )

 def     snake_case_      (    self					:					Any      )   ->	str:
    _A      =       {'''num_warmup_steps''': 2, '''num_training_steps''': 10}
    # schedulers doct format
    # function: (sched_args_dict, expected_learning_rates)
    _A      =       {
        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():
       _A  ,    _A      =       data

       _A      =       scheduler_func(self.optimizer			,						**__lowerCAmelCase      )
       self.assertEqual(len([scheduler.get_lr()[0]]      )			,						1      )
       _A      =       unwrap_schedule(__lowerCAmelCase			,						self.num_steps      )
       self.assertListAlmostEqual(
           __lowerCAmelCase			,						__lowerCAmelCase			,						tol=1E-2			,						msg=f'''failed for {scheduler_func} in normal scheduler'''			,						)

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


class 	lowerCamelCase__	:



 """simple docstring"""

 def __init__(    self					:					List[Any]			,						__lowerCAmelCase					:					Any      )   ->	List[Any]:
    _A      =       fn

 def __call__(    self					:					Union[str, Any]			,						*__lowerCAmelCase					:					Any			,						**__lowerCAmelCase					:					List[str]      )   ->	Dict:
    return self.fn(*__lowerCAmelCase			,						**__lowerCAmelCase      )

 @classmethod
 def     snake_case_      (    self					:					Any			,						__lowerCAmelCase					:					Optional[Any]      )   ->	List[str]:
    _A      =       list(map(self			,						scheduler.lr_lambdas      )      )








def 	SCREAMING_SNAKE_CASE_							(	_snake_case	:bytes				)  ->     str:
   return "".join([hex(_snake_case				)[2:].zfill(2				).upper() for byte in list(_snake_case				)]				)

def 	SCREAMING_SNAKE_CASE_							(	_snake_case	:str				)  ->     bytes:
   # Check data validity, following RFC3548
   # https://www.ietf.org/rfc/rfc3548.txt
   if (len(_snake_case				) % 2) != 0:
      raise ValueError(
          '''Base16 encoded data is invalid:
Data does not have an even number of hex digits.'''				)
   # Check the character set - the standard base16 alphabet
   # is uppercase according to RFC3548 section 6
   if not set(_snake_case				) <= set('''0123456789ABCDEF'''				):
      raise ValueError(
          '''Base16 encoded data is invalid:
Data is not uppercase hex or it contains invalid characters.'''				)
   # For every two hexadecimal digits (= a byte), turn it into an integer.
   # Then, string the result together into bytes, and return it.
   return bytes(int(data[i] + data[i + 1]	,   16				) for i in range(0	,   len(_snake_case				)	,   2				)				)


if __name__ == "__main__":
   import doctest

   doctest.testmod()



