



"""simple docstring"""





import inspect
import os
import unittest
from dataclasses import dataclass

import torch

from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cuda, require_multi_gpu
from accelerate.utils import KwargsHandler
@dataclass
class    lowercase__     (					SCREAMING_SNAKE_CASE   ):







       '''simple docstring'''


       UpperCamelCase		=  0
       UpperCamelCase		=  False
       UpperCamelCase		=  3.0



class    lowercase__     (					unittest.TestCase   ):







       '''simple docstring'''


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


             '''simple docstring'''




             self.assertDictEqual(MockClass().to_kwargs()	,       {}					)
             self.assertDictEqual(MockClass(a=2					).to_kwargs()	,       {"a": 2}					)
             self.assertDictEqual(MockClass(a=2	,       b=_UpperCAmelCase					).to_kwargs()	,       {"a": 2, "b": True}					)
             self.assertDictEqual(MockClass(a=2	,       c=2.25					).to_kwargs()	,       {"a": 2, "c": 2.25}					)



       @require_cuda
       def   lowercase__       (							self    :						str					)				->		str:


             '''simple docstring'''




             UpperCAmelCase_    				=							GradScalerKwargs(init_scale=1024	,       growth_factor=2					)
             AcceleratorState._reset_state()
             UpperCAmelCase_    				=							Accelerator(mixed_precision="fp16"	,       kwargs_handlers=[scaler_handler]					)
             print(accelerator.use_fpaa					)
             UpperCAmelCase_    				=							accelerator.scaler

             # Check the kwargs have been applied
             self.assertEqual(scaler._init_scale	,       1024.0					)
             self.assertEqual(scaler._growth_factor	,       2.0					)

             # Check the other values are at the default
             self.assertEqual(scaler._backoff_factor	,       0.5					)
             self.assertEqual(scaler._growth_interval	,       2000					)
             self.assertEqual(scaler._enabled	,       _UpperCAmelCase					)







       @require_multi_gpu
       def   lowercase__       (							self    :						Union[str, Any]					)				->		List[str]:


             '''simple docstring'''




             UpperCAmelCase_    				=							["torchrun", F"""--nproc_per_node={torch.cuda.device_count()}""", inspect.getfile(self.__class__					)]
             execute_subprocess_async(_UpperCAmelCase	,       env=os.environ.copy()					)


if __name__ == "__main__":
  lowerCamelCase      =		DistributedDataParallelKwargs(bucket_cap_mb=15, find_unused_parameters=True)
  lowerCamelCase      =		Accelerator(kwargs_handlers=[ddp_scaler])
  lowerCamelCase      =		torch.nn.Linear(100, 200)
  lowerCamelCase      =		accelerator.prepare(model)

  # Check the values changed in kwargs
  lowerCamelCase      =		""""""
  lowerCamelCase      =		model.bucket_bytes_cap // (1_024 * 1_024)
  if observed_bucket_cap_map != 15:
    error_msg += F"Kwargs badly passed, should have `15` but found {observed_bucket_cap_map}.\n"
  if model.find_unused_parameters is not True:
    error_msg += F"Kwargs badly passed, should have `True` but found {model.find_unused_parameters}.\n"

  # Check the values of the defaults
  if model.dim != 0:
    error_msg += F"Default value not respected, should have `0` but found {model.dim}.\n"
  if model.broadcast_buffers is not True:
    error_msg += F"Default value not respected, should have `True` but found {model.broadcast_buffers}.\n"
  if model.gradient_as_bucket_view is not False:
    error_msg += F"Default value not respected, should have `False` but found {model.gradient_as_bucket_view}.\n"

  # Raise error at the end to make sure we don't stop at the first failure.
  if len(error_msg) > 0:
    raise ValueError(error_msg)









"""simple docstring"""





lowerCamelCase      =		{
    "joule": 1.0,
    "kilojoule": 1_000,
    "megajoule": 1_000_000,
    "gigajoule": 1_000_000_000,
    "wattsecond": 1.0,
    "watthour": 3_600,
    "kilowatthour": 3_600_000,
    "newtonmeter": 1.0,
    "calorie_nutr": 4_186.8,
    "kilocalorie_nutr": 4_186_800.00,
    "electronvolt": 1.6_0_2_1_7_6_6_3_4e-1_9,
    "britishthermalunit_it": 1_055.05_585,
    "footpound": 1.355_818,
}
def      a__			(   lowerCAmelCase__			,    lowerCAmelCase__			,    lowerCAmelCase__   ):
      if to_type not in ENERGY_CONVERSION or from_type not in ENERGY_CONVERSION:
            UpperCAmelCase_    				=							(
                f"""Incorrect 'from_type' or 'to_type' value: {from_type!r}, {to_type!r}\n"""
                f"""Valid values are: {', '.join(lowerCAmelCase__   )}"""
            )
            raise ValueError(lowerCAmelCase__   )
      return value * ENERGY_CONVERSION[from_type] / ENERGY_CONVERSION[to_type]


if __name__ == "__main__":
  import doctest

  doctest.testmod()




