






"""simple docstring"""



import unittest
from dataclasses import dataclass
from typing import Optional

from transformers.utils import ModelOutput

@dataclass
class 			a	(  a_      ):
    UpperCAmelCase_					:	float
    UpperCAmelCase_					:	Optional[float]      	=None
    UpperCAmelCase_					:	Optional[float]      	=None


class 			a	(  unittest.TestCase      ):







    def      UpperCamelCase_ (     self			):
      lowercase				       =			ModelOutputTest(a=3_0			)
      self.assertEqual(x.a				,						3_0			)
      self.assertIsNone(x.b			)
      self.assertIsNone(x.c			)
      with self.assertRaises(_lowerCamelCase			):
        lowercase				       =			x.d







    def      UpperCamelCase_ (     self			):
      lowercase				       =			ModelOutputTest(a=3_0				,						b=1_0			)
      self.assertEqual(x[0]				,						3_0			)
      self.assertEqual(x[1]				,						1_0			)
      self.assertEqual(x[:2]				,						(3_0, 1_0)			)
      self.assertEqual(x[:]				,						(3_0, 1_0)			)

      lowercase				       =			ModelOutputTest(a=3_0				,						c=1_0			)
      self.assertEqual(x[0]				,						3_0			)
      self.assertEqual(x[1]				,						1_0			)
      self.assertEqual(x[:2]				,						(3_0, 1_0)			)
      self.assertEqual(x[:]				,						(3_0, 1_0)			)







    def      UpperCamelCase_ (     self			):
      lowercase				       =			ModelOutputTest(a=3_0				,						b=1_0			)
      self.assertEqual(x['a']				,						3_0			)
      self.assertEqual(x['b']				,						1_0			)
      with self.assertRaises(_lowerCamelCase			):
        lowercase				       =			x['c']

      lowercase				       =			ModelOutputTest(a=3_0				,						c=1_0			)
      self.assertEqual(x['a']				,						3_0			)
      self.assertEqual(x['c']				,						1_0			)
      with self.assertRaises(_lowerCamelCase			):
        lowercase				       =			x['b']







    def      UpperCamelCase_ (     self			):
      lowercase				       =			ModelOutputTest(a=3_0			)
      self.assertEqual(list(x.keys()			)				,						['a']			)
      self.assertEqual(list(x.values()			)				,						[3_0]			)
      self.assertEqual(list(x.items()			)				,						[('a', 3_0)]			)
      self.assertEqual(list(_lowerCamelCase			)				,						['a']			)

      lowercase				       =			ModelOutputTest(a=3_0				,						b=1_0			)
      self.assertEqual(list(x.keys()			)				,						['a', 'b']			)
      self.assertEqual(list(x.values()			)				,						[3_0, 1_0]			)
      self.assertEqual(list(x.items()			)				,						[('a', 3_0), ('b', 1_0)]			)
      self.assertEqual(list(_lowerCamelCase			)				,						['a', 'b']			)

      lowercase				       =			ModelOutputTest(a=3_0				,						c=1_0			)
      self.assertEqual(list(x.keys()			)				,						['a', 'c']			)
      self.assertEqual(list(x.values()			)				,						[3_0, 1_0]			)
      self.assertEqual(list(x.items()			)				,						[('a', 3_0), ('c', 1_0)]			)
      self.assertEqual(list(_lowerCamelCase			)				,						['a', 'c']			)

      with self.assertRaises(_lowerCamelCase			):
        lowercase				       =			x.update({'d': 2_0}			)
      with self.assertRaises(_lowerCamelCase			):
        del x["a"]
      with self.assertRaises(_lowerCamelCase			):
        lowercase				       =			x.pop('a'			)
      with self.assertRaises(_lowerCamelCase			):
        lowercase				       =			x.setdefault('d'				,						3_2			)







    def      UpperCamelCase_ (     self			):
      lowercase				       =			ModelOutputTest(a=3_0			)
      lowercase				       =			1_0
      self.assertEqual(x.a				,						1_0			)
      self.assertEqual(x['a']				,						1_0			)







    def      UpperCamelCase_ (     self			):
      lowercase				       =			ModelOutputTest(a=3_0			)
      lowercase				       =			1_0
      self.assertEqual(x.a				,						1_0			)
      self.assertEqual(x['a']				,						1_0			)







    def      UpperCamelCase_ (     self			):
      lowercase				       =			ModelOutputTest({'a': 3_0, 'b': 1_0}			)
      self.assertEqual(list(x.keys()			)				,						['a', 'b']			)
      self.assertEqual(x.a				,						3_0			)
      self.assertEqual(x.b				,						1_0			)







    def      UpperCamelCase_ (     self			):
      lowercase				       =			ModelOutputTest([('a', 3_0), ('b', 1_0)]			)
      self.assertEqual(list(x.keys()			)				,						['a', 'b']			)
      self.assertEqual(x.a				,						3_0			)
      self.assertEqual(x.b				,						1_0			)

      with self.assertRaises(_lowerCamelCase			):
        lowercase				       =			ModelOutputTest([('a', 3_0), (1_0, 1_0)]			)

      lowercase				       =			ModelOutputTest(a=(3_0, 3_0)			)
      self.assertEqual(list(x.keys()			)				,						['a']			)
      self.assertEqual(x.a				,						(3_0, 3_0)			)



import torch

from accelerate import Accelerator, DistributedType




class 						__snake_case						:





      '''simple docstring'''






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


          """simple docstring"""


          if self.enabled:
              _lowerCamelCase  :		str			    =    self.model.no_sync()
              self.model_sync_obj.__enter__()

          return self



      def __exit__(       self  :					List[str]     ,	_UpperCamelCase  :					Any     ,	_UpperCamelCase  :					Union[str, Any]     ,	_UpperCamelCase  :					int)					->Optional[Any]:


          """simple docstring"""


          if self.enabled:
              # Average all models on exit
              self._sync_and_avg_model_params()
              self.model_sync_obj.__exit__(_UpperCamelCase     ,	_UpperCamelCase     ,	_UpperCamelCase)



      def __init__(       self  :					Union[str, Any]     ,	_UpperCamelCase  :					Accelerator     ,	_UpperCamelCase  :					torch.nn.Module     ,	_UpperCamelCase  :					int     ,	_UpperCamelCase  :					bool = True)					->int:


          """simple docstring"""


          if accelerator.distributed_type not in [
              DistributedType.NO,
              DistributedType.MULTI_CPU,
              DistributedType.MULTI_GPU,
          ]:
              raise NotImplementedError("""LocalSGD is supported only for CPUs and GPUs (no DeepSpeed or MegatronLM)""")
          _lowerCamelCase  :		str			    =    enabled and accelerator.distributed_type != DistributedType.NO
          _lowerCamelCase  :		Optional[int]			    =    0
          if self.enabled:
              _lowerCamelCase  :		Union[str, Any]			    =    accelerator
              _lowerCamelCase  :		int			    =    model
              _lowerCamelCase  :		int			    =    local_sgd_steps



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


          """simple docstring"""


          self.num_steps += 1
          if not self.enabled:
              return

          if self.num_steps % self.local_sgd_steps == 0:
              self._sync_and_avg_model_params()




      def 						_SCREAMING_SNAKE_CASE     (       self  :					Optional[Any])					->List[str]:


          """simple docstring"""


          self.accelerator.wait_for_everyone()
          with self.accelerator.autocast():
              for param in self.model.parameters():
                  _lowerCamelCase  :		Union[str, Any]			    =    self.accelerator.reduce(param.data     ,	reduction="""mean""")




