


"""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_	(			a_    ):
      __magic_name__  :				int 							=					0
      __magic_name__  :				bool 							=					False
      __magic_name__  :				float 							=					3.0

class 			lowercase_	(			unittest.TestCase    ):







      def 					_lowerCAmelCase							(   self			:				Tuple     ):
        # If no defaults are changed, `to_kwargs` returns an empty dict.
        self.assertDictEqual(MockClass().to_kwargs()		,	{}     )
        self.assertDictEqual(MockClass(a=2     ).to_kwargs()		,	{"a": 2}     )
        self.assertDictEqual(MockClass(a=2		,	b=_lowercase     ).to_kwargs()		,	{"a": 2, "b": True}     )
        self.assertDictEqual(MockClass(a=2		,	c=2.25     ).to_kwargs()		,	{"a": 2, "c": 2.25}     )







      @require_cuda
      def 					_lowerCAmelCase							(   self			:				Union[str, Any]     ):
        # If no defaults are changed, `to_kwargs` returns an empty dict.
        lowerCAmelCase__     :     Union[str, Any]										=       GradScalerKwargs(init_scale=1_0_2_4		,	growth_factor=2     )
        AcceleratorState._reset_state()
        lowerCAmelCase__     :     List[Any]										=       Accelerator(mixed_precision="fp16"		,	kwargs_handlers=[scaler_handler]     )
        print(accelerator.use_fpaa     )
        lowerCAmelCase__     :     Any										=       accelerator.scaler

        # Check the kwargs have been applied
        self.assertEqual(scaler._init_scale		,	1_0_2_4.0     )
        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		,	2_0_0_0     )
        self.assertEqual(scaler._enabled		,	_lowercase     )







      @require_multi_gpu
      def 					_lowerCAmelCase							(   self			:				Any     ):
        lowerCAmelCase__     :     Optional[Any]										=       ["torchrun", f"--nproc_per_node={torch.cuda.device_count()}", inspect.getfile(self.__class__     )]
        execute_subprocess_async(_lowercase		,	env=os.environ.copy()     )


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

   # Check the values changed in kwargs
   __UpperCAmelCase     					=   ""
   __UpperCAmelCase     					=   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"""


def  lowercase						(	lowerCAmelCase__						):
			return " ".join(input_str.split()[::-1]						)


if __name__ == "__main__":
						import doctest

						doctest.testmod()



