


'''simple docstring'''
import json
import os
import tempfile
from unittest.mock import patch

import torch
from torch.utils.data import DataLoader, TensorDataset

from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState, PartialState
from accelerate.test_utils import require_bnb, require_multi_gpu, slow
from accelerate.test_utils.testing import AccelerateTestCase, require_cuda
from accelerate.utils import patch_environment





def    a__			(   )       ->      Any:
    UpperCAmelCase__     :						Optional[Any]						=							torch.nn.Linear(2    ,   4		)
    UpperCAmelCase__     :						Union[str, Any]						=							torch.optim.AdamW(model.parameters()    ,   lr=1.0		)
    UpperCAmelCase__     :						Union[str, Any]						=							torch.optim.lr_scheduler.OneCycleLR(_UpperCAmelCase    ,   max_lr=0.0_1    ,   steps_per_epoch=2    ,   epochs=1		)
    UpperCAmelCase__     :						List[str]						=							DataLoader(TensorDataset(torch.tensor([1, 2, 3]		)		)		)
    UpperCAmelCase__     :						List[str]						=							DataLoader(TensorDataset(torch.tensor([4, 5, 6]		)		)		)

    return model, optimizer, scheduler, train_dl, valid_dl





def    a__			(   lowerCAmelCase__		)       ->      Union[str, Any]:
    return (model.weight.abs().sum() + model.bias.abs().sum()).item()





def    a__			(   lowerCAmelCase__		)       ->      str:
    UpperCAmelCase__     :						Dict						=							torch.nn.Linear(*tuple(model.weight.T.shape		)		).state_dict()
    model.load_state_dict(_UpperCAmelCase		)







class      lowerCamelCase_  (      _SCREAMING_SNAKE_CASE ):






      @require_cuda
      def lowercase_				(   self							:       Any					):


          '''simple docstring'''


          UpperCAmelCase__     :						Tuple						=							Accelerator()
          assert PartialState._shared_state["_cpu"] is False
          assert PartialState._shared_state["device"].type == "cuda"
          with self.assertRaises(__snake_case					):
              UpperCAmelCase__     :						List[str]						=							Accelerator(cpu=__snake_case					)






      def lowercase_				(   self							:       Union[str, Any]					):


          '''simple docstring'''


          UpperCAmelCase__     :						Dict						=							Accelerator()
          UpperCAmelCase__     :						Tuple						=							GradientState()
          assert state.num_steps == 1
          UpperCAmelCase__     :						Any						=							4
          assert state.num_steps == 4

          assert state.sync_gradients is True
          UpperCAmelCase__     :						str						=							False
          assert state.sync_gradients is False
          GradientState._reset_state()






      def lowercase_				(   self							:       str					):


          '''simple docstring'''


          UpperCAmelCase__     :						Optional[int]						=							Accelerator()
          UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__     :						str						=							create_components()

          (
              (
              UpperCAmelCase__    
          )		,		(
              UpperCAmelCase__    
          )		,		(
              UpperCAmelCase__    
          )		,		(
              UpperCAmelCase__    
          )		,		(
              UpperCAmelCase__    
          )		,		    
          )     :						str						=							accelerator.prepare(__snake_case		,		__snake_case		,		__snake_case		,		__snake_case		,		__snake_case					)

          self.assertTrue(prepared_model in accelerator._models					)
          self.assertTrue(prepared_optimizer in accelerator._optimizers					)
          self.assertTrue(prepared_scheduler in accelerator._schedulers					)
          self.assertTrue(prepared_train_dl in accelerator._dataloaders					)
          self.assertTrue(prepared_valid_dl in accelerator._dataloaders					)






      def lowercase_				(   self							:       Optional[int]					):


          '''simple docstring'''


          UpperCAmelCase__     :						List[Any]						=							Accelerator()
          UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__     :						List[Any]						=							create_components()
          accelerator.prepare(__snake_case		,		__snake_case		,		__snake_case		,		__snake_case		,		__snake_case					)
          accelerator.free_memory()

          self.assertTrue(len(accelerator._models					) == 0					)
          self.assertTrue(len(accelerator._optimizers					) == 0					)
          self.assertTrue(len(accelerator._schedulers					) == 0					)
          self.assertTrue(len(accelerator._dataloaders					) == 0					)






      def lowercase_				(   self							:       str					):


          '''simple docstring'''


          PartialState._reset_state()

          # Mock torch.cuda.set_device to avoid an exception as the device doesn't exist
          def noop(*_A							:       List[str]		,		**_A							:       int					):
              pass

          with patch('''torch.cuda.set_device'''		,		__snake_case					), patch_environment(ACCELERATE_TORCH_DEVICE='''cuda:64'''					):
              UpperCAmelCase__     :						Optional[Any]						=							Accelerator()
              self.assertEqual(str(accelerator.state.device					)		,		'''cuda:64'''					)






      def lowercase_				(   self							:       Optional[int]					):


          '''simple docstring'''


          UpperCAmelCase__     :						Dict						=							Accelerator()
          UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__     :						int						=							create_components()
          accelerator.prepare(__snake_case		,		__snake_case		,		__snake_case		,		__snake_case		,		__snake_case					)

          UpperCAmelCase__     :						Optional[int]						=							get_signature(__snake_case					)

          with tempfile.TemporaryDirectory() as tmpdirname:
              accelerator.save_state(__snake_case					)

              # make sure random weights don't match
              load_random_weights(__snake_case					)
              self.assertTrue(abs(model_signature - get_signature(__snake_case					)					) > 1e-3					)

              # make sure loaded weights match
              accelerator.load_state(__snake_case					)
              self.assertTrue(abs(model_signature - get_signature(__snake_case					)					) < 1e-3					)






      def lowercase_				(   self							:       List[str]					):


          '''simple docstring'''


          UpperCAmelCase__     :						Optional[int]						=							Accelerator()
          UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__     :						Optional[Any]						=							create_components()
          accelerator.prepare(__snake_case		,		__snake_case		,		__snake_case		,		__snake_case		,		__snake_case					)

          UpperCAmelCase__     :						Any						=							get_signature(__snake_case					)

          # saving hook
          def save_config(_A							:       str		,		_A							:       Any		,		_A							:       Optional[Any]					):
              UpperCAmelCase__     :						Dict						=							{'''class_name''': models[0].__class__.__name__}

              with open(os.path.join(__snake_case		,		'''data.json'''					)		,		'''w'''					) as f:
                  json.dump(__snake_case		,		__snake_case					)

        # loading hook
          def load_config(_A							:       str		,		_A							:       Dict					):
              with open(os.path.join(__snake_case		,		'''data.json'''					)		,		'''r'''					) as f:
                  UpperCAmelCase__     :						List[Any]						=							json.load(__snake_case					)

              UpperCAmelCase__     :						Union[str, Any]						=							config['''class_name''']

          UpperCAmelCase__     :						Dict						=							accelerator.register_save_state_pre_hook(__snake_case					)
          UpperCAmelCase__     :						Union[str, Any]						=							accelerator.register_load_state_pre_hook(__snake_case					)

          with tempfile.TemporaryDirectory() as tmpdirname:
              accelerator.save_state(__snake_case					)

              # make sure random weights don't match with hooks
              load_random_weights(__snake_case					)
              self.assertTrue(abs(model_signature - get_signature(__snake_case					)					) > 1e-3					)

              # random class name to verify correct one is loaded
              UpperCAmelCase__     :						Tuple						=							'''random'''

              # make sure loaded weights match with hooks
              accelerator.load_state(__snake_case					)
              self.assertTrue(abs(model_signature - get_signature(__snake_case					)					) < 1e-3					)

              # mode.class_name is loaded from config
              self.assertTrue(model.class_name == model.__class__.__name__					)

          # remove hooks
          save_hook.remove()
          load_hook.remove()

          with tempfile.TemporaryDirectory() as tmpdirname:
              accelerator.save_state(__snake_case					)

              # make sure random weights don't match with hooks removed
              load_random_weights(__snake_case					)
              self.assertTrue(abs(model_signature - get_signature(__snake_case					)					) > 1e-3					)

              # random class name to verify correct one is loaded
              UpperCAmelCase__     :						Optional[Any]						=							'''random'''

              # make sure loaded weights match with hooks removed
              accelerator.load_state(__snake_case					)
              self.assertTrue(abs(model_signature - get_signature(__snake_case					)					) < 1e-3					)

              # mode.class_name is NOT loaded from config
              self.assertTrue(model.class_name != model.__class__.__name__					)






      def lowercase_				(   self							:       List[str]					):


          '''simple docstring'''


          UpperCAmelCase__     :						Tuple						=							Accelerator()
          UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__     :						int						=							create_components()
          UpperCAmelCase__     :						int						=							None

          # This should work
          UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__     :						Optional[int]						=							accelerator.prepare(
              __snake_case		,		__snake_case		,		__snake_case		,		__snake_case		,		__snake_case		,		__snake_case					)
          self.assertTrue(dummy_obj is None					)






      def lowercase_				(   self							:       Union[str, Any]					):


          '''simple docstring'''


          UpperCAmelCase__     :						Tuple						=							Accelerator()
          UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__     :						List[str]						=							create_components()
          UpperCAmelCase__     :						int						=							[1, 2, 3]

          # This should work
          UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__		,		UpperCAmelCase__     :						Tuple						=							accelerator.prepare(
              __snake_case		,		__snake_case		,		__snake_case		,		__snake_case		,		__snake_case		,		__snake_case					)
          self.assertEqual(
              getattr(__snake_case		,		'''_is_accelerate_prepared'''		,		__snake_case					)		,		__snake_case		,		'''Dummy object should have `_is_accelerate_prepared` set to `True`'''		,		)
          self.assertEqual(
              getattr(__snake_case		,		'''_is_accelerate_prepared'''		,		__snake_case					)		,		__snake_case		,		'''Model is missing `_is_accelerator_prepared` or is set to `False`'''		,		)
          self.assertEqual(
              getattr(__snake_case		,		'''_is_accelerate_prepared'''		,		__snake_case					)		,		__snake_case		,		'''Optimizer is missing `_is_accelerator_prepared` or is set to `False`'''		,		)
          self.assertEqual(
              getattr(__snake_case		,		'''_is_accelerate_prepared'''		,		__snake_case					)		,		__snake_case		,		'''Scheduler is missing `_is_accelerator_prepared` or is set to `False`'''		,		)
          self.assertEqual(
              getattr(__snake_case		,		'''_is_accelerate_prepared'''		,		__snake_case					)		,		__snake_case		,		'''Train Dataloader is missing `_is_accelerator_prepared` or is set to `False`'''		,		)
          self.assertEqual(
              getattr(__snake_case		,		'''_is_accelerate_prepared'''		,		__snake_case					)		,		__snake_case		,		'''Valid Dataloader is missing `_is_accelerator_prepared` or is set to `False`'''		,		)






      @slow
      @require_bnb
      def lowercase_				(   self							:       Optional[int]					):


          '''simple docstring'''


          from transformers import AutoModelForCausalLM

          UpperCAmelCase__     :						Union[str, Any]						=							AutoModelForCausalLM.from_pretrained(
              '''EleutherAI/gpt-neo-125m'''		,		load_in_abit=__snake_case		,		device_map={'''''': 0}		,		)
          UpperCAmelCase__     :						str						=							Accelerator()

          # This should work
          UpperCAmelCase__     :						Union[str, Any]						=							accelerator.prepare(__snake_case					)






      @slow
      @require_bnb
      def lowercase_				(   self							:       str					):


          '''simple docstring'''


          from transformers import AutoModelForCausalLM

          UpperCAmelCase__     :						Any						=							Accelerator()

          with init_empty_weights():
              UpperCAmelCase__     :						Optional[Any]						=							AutoModelForCausalLM.from_pretrained(
                  '''EleutherAI/gpt-neo-125m'''		,		)
              model.tie_weights()
              UpperCAmelCase__     :						str						=							infer_auto_device_map(__snake_case					)
              UpperCAmelCase__     :						Optional[int]						=							'''cpu'''

          UpperCAmelCase__     :						Dict						=							AutoModelForCausalLM.from_pretrained(
              '''EleutherAI/gpt-neo-125m'''		,		device_map=__snake_case		,		load_in_abit=__snake_case		,		llm_inta_enable_fpaa_cpu_offload=__snake_case					)

          # This should not work and get value error
          with self.assertRaises(__snake_case					):
              UpperCAmelCase__     :						str						=							accelerator.prepare(__snake_case					)






      @slow
      @require_bnb
      @require_multi_gpu
      def lowercase_				(   self							:       Union[str, Any]					):


          '''simple docstring'''


          from transformers import AutoModelForCausalLM

          UpperCAmelCase__     :						Optional[int]						=							{'''distributed_type''': DistributedType.MULTI_GPU}

          with init_empty_weights():
              UpperCAmelCase__     :						List[Any]						=							AutoModelForCausalLM.from_pretrained(
                  '''EleutherAI/gpt-neo-125m'''		,		)
              model.tie_weights()
              UpperCAmelCase__     :						List[Any]						=							infer_auto_device_map(__snake_case					)
              UpperCAmelCase__     :						int						=							1

          UpperCAmelCase__     :						Union[str, Any]						=							AutoModelForCausalLM.from_pretrained(
              '''EleutherAI/gpt-neo-125m'''		,		load_in_abit=__snake_case		,		device_map=__snake_case		,		)
          UpperCAmelCase__     :						Tuple						=							Accelerator()

          # This should not work and get value error
          with self.assertRaises(__snake_case					):
              UpperCAmelCase__     :						Optional[Any]						=							accelerator.prepare(__snake_case					)

          PartialState._reset_state()






      @slow
      @require_bnb
      @require_multi_gpu
      def lowercase_				(   self							:       Any					):


          '''simple docstring'''


          from transformers import AutoModelForCausalLM

          with init_empty_weights():
              UpperCAmelCase__     :						str						=							AutoModelForCausalLM.from_pretrained(
                  '''EleutherAI/gpt-neo-125m'''		,		)
              UpperCAmelCase__     :						Optional[Any]						=							infer_auto_device_map(__snake_case					)
              UpperCAmelCase__     :						int						=							1

          UpperCAmelCase__     :						List[Any]						=							AutoModelForCausalLM.from_pretrained(
              '''EleutherAI/gpt-neo-125m'''		,		load_in_abit=__snake_case		,		device_map=__snake_case		,		)
          UpperCAmelCase__     :						List[Any]						=							Accelerator()

          # This should work
          UpperCAmelCase__     :						List[str]						=							accelerator.prepare(__snake_case					)






      @require_cuda
      def lowercase_				(   self							:       Optional[int]					):


          '''simple docstring'''


          UpperCAmelCase__     :						List[str]						=							torch.nn.Linear(10		,		10					)
          UpperCAmelCase__     :						Any						=							torch.optim.SGD(model.parameters()		,		lr=0.0_1					)
          UpperCAmelCase__     :						int						=							Accelerator(cpu=__snake_case					)
          UpperCAmelCase__     :						Dict						=							accelerator.prepare(__snake_case					)







from __future__ import annotations

def      UpperCAmelCase_    (    _UpperCAmelCase							:list[float]  ,						_UpperCAmelCase							:list[float]				)	->				float:
     '''simple docstring'''


     A_          =       sorted(numsa + numsa				)
     A_   ,    A_          =       divmod(len(_UpperCAmelCase				)  ,						2				)
     if mod == 1:
          return all_numbers[div]
     else:
          return (all_numbers[div] + all_numbers[div - 1]) / 2


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      a__      :     Optional[Any]         =		[float(x) for x in input('Enter the elements of first array: ').split()]
      a__      :     int         =		[float(x) for x in input('Enter the elements of second array: ').split()]
      print(f'''The median of two arrays is: {median_of_two_arrays(array_a, array_a)}''')



