





'''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 							UpperCAmelCase_  (						):
      lowercase_      :int         =			torch.nn.Linear(2     ,4			)
      lowercase_      :Optional[Any]         =			torch.optim.AdamW(model.parameters()     ,lr=1.0			)
      lowercase_      :Optional[Any]         =			torch.optim.lr_scheduler.OneCycleLR(_snake_case     ,max_lr=0.01     ,steps_per_epoch=2     ,epochs=1			)
      lowercase_      :List[str]         =			DataLoader(TensorDataset(torch.tensor([1, 2, 3]			)			)			)
      lowercase_      :Dict         =			DataLoader(TensorDataset(torch.tensor([4, 5, 6]			)			)			)

      return model, optimizer, scheduler, train_dl, valid_dl
def 							UpperCAmelCase_  (						__lowerCamelCase : str			):
      return (model.weight.abs().sum() + model.bias.abs().sum()).item()
def 							UpperCAmelCase_  (						__lowerCamelCase : Union[str, Any]			):
      lowercase_      :Dict         =			torch.nn.Linear(*tuple(model.weight.T.shape			)			).state_dict()
      model.load_state_dict(_snake_case			)


class 				a_       (    __snake_case							):





     @require_cuda
     def 							lowercase__				(			self		: int						):





           """simple docstring"""




           lowercase_      :Optional[int]         =			Accelerator()
           assert PartialState._shared_state["_cpu"] is False
           assert PartialState._shared_state["device"].type == "cuda"
           with self.assertRaises(a_						):
                 lowercase_      :Any         =			Accelerator(cpu=a_						)





     def 							lowercase__				(			self		: Any						):





           """simple docstring"""




           lowercase_      :Optional[int]         =			Accelerator()
           lowercase_      :Optional[int]         =			GradientState()
           assert state.num_steps == 1
           lowercase_      :str         =			4
           assert state.num_steps == 4

           assert state.sync_gradients is True
           lowercase_      :List[Any]         =			False
           assert state.sync_gradients is False
           GradientState._reset_state()





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





           """simple docstring"""




           lowercase_      :Optional[Any]         =			Accelerator()
           lowercase_      :Optional[Any]         =			create_components()

           (
               lowercase_							
           )      :Union[str, Any]         =			accelerator.prepare(a_     ,				a_     ,				a_     ,				a_     ,				a_						)

           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"""




           lowercase_      :Tuple         =			Accelerator()
           lowercase_      :Union[str, Any]         =			create_components()
           accelerator.prepare(a_     ,				a_     ,				a_     ,				a_     ,				a_						)
           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		: List[str]						):





           """simple docstring"""




           PartialState._reset_state()

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

           with patch("torch.cuda.set_device"     ,				a_						), patch_environment(ACCELERATE_TORCH_DEVICE="cuda:64"						):
                 lowercase_      :List[Any]         =			Accelerator()
                 self.assertEqual(str(accelerator.state.device						)     ,				"cuda:64"						)





     def 							lowercase__				(			self		: Any						):





           """simple docstring"""




           lowercase_      :Optional[int]         =			Accelerator()
           lowercase_      :str         =			create_components()
           accelerator.prepare(a_     ,				a_     ,				a_     ,				a_     ,				a_						)

           lowercase_      :Any         =			get_signature(a_						)

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

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

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





     def 							lowercase__				(			self		: Optional[Any]						):





           """simple docstring"""




           lowercase_      :int         =			Accelerator()
           lowercase_      :str         =			create_components()
           accelerator.prepare(a_     ,				a_     ,				a_     ,				a_     ,				a_						)

           lowercase_      :List[Any]         =			get_signature(a_						)

           # saving hook
           def save_config(lowercase		: Union[str, Any]     ,				lowercase		: Optional[int]     ,				lowercase		: Optional[int]						):
                 lowercase_      :Optional[Any]         =			{'''class_name''': models[0].__class__.__name__}

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

        # loading hook
           def load_config(lowercase		: Optional[int]     ,				lowercase		: str						):
                 with open(os.path.join(a_     ,				"data.json"						)     ,				"r"						) as f:
                       lowercase_      :Any         =			json.load(a_						)

                 lowercase_      :List[str]         =			config['''class_name''']

           lowercase_      :str         =			accelerator.register_save_state_pre_hook(a_						)
           lowercase_      :Union[str, Any]         =			accelerator.register_load_state_pre_hook(a_						)

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

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

                 # random class name to verify correct one is loaded
                 lowercase_      :Any         =			'''random'''

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

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

                 # random class name to verify correct one is loaded
                 lowercase_      :Union[str, Any]         =			'''random'''

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

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





     def 							lowercase__				(			self		: Any						):





           """simple docstring"""




           lowercase_      :List[Any]         =			Accelerator()
           lowercase_      :Tuple         =			create_components()
           lowercase_      :Union[str, Any]         =			None

           # This should work
           lowercase_      :Tuple         =			accelerator.prepare(
               a_     ,				a_     ,				a_     ,				a_     ,				a_     ,				a_						)
           self.assertTrue(dummy_obj is None						)





     def 							lowercase__				(			self		: Optional[int]						):





           """simple docstring"""




           lowercase_      :str         =			Accelerator()
           lowercase_      :Optional[Any]         =			create_components()
           lowercase_      :Optional[int]         =			[1, 2, 3]

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





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





           """simple docstring"""




           from transformers import AutoModelForCausalLM

           lowercase_      :Dict         =			AutoModelForCausalLM.from_pretrained(
               "EleutherAI/gpt-neo-125m"     ,				load_in_abit=a_     ,				device_map={"": 0}     ,				)
           lowercase_      :Optional[Any]         =			Accelerator()

           # This should work
           lowercase_      :Any         =			accelerator.prepare(a_						)





     @slow
     @require_bnb
     def 							lowercase__				(			self		: List[Any]						):





           """simple docstring"""




           from transformers import AutoModelForCausalLM

           lowercase_      :Any         =			Accelerator()

           with init_empty_weights():
                 lowercase_      :List[str]         =			AutoModelForCausalLM.from_pretrained(
                     "EleutherAI/gpt-neo-125m"     ,				)
                 model.tie_weights()
                 lowercase_      :Union[str, Any]         =			infer_auto_device_map(a_						)
                 lowercase_      :str         =			'''cpu'''

           lowercase_      :Optional[int]         =			AutoModelForCausalLM.from_pretrained(
               "EleutherAI/gpt-neo-125m"     ,				device_map=a_     ,				load_in_abit=a_     ,				llm_inta_enable_fpaa_cpu_offload=a_						)

           # This should not work and get value error
           with self.assertRaises(a_						):
                 lowercase_      :Dict         =			accelerator.prepare(a_						)





     @slow
     @require_bnb
     @require_multi_gpu
     def 							lowercase__				(			self		: str						):





           """simple docstring"""




           from transformers import AutoModelForCausalLM

           lowercase_      :str         =			{'''distributed_type''': DistributedType.MULTI_GPU}

           with init_empty_weights():
                 lowercase_      :Any         =			AutoModelForCausalLM.from_pretrained(
                     "EleutherAI/gpt-neo-125m"     ,				)
                 model.tie_weights()
                 lowercase_      :List[Any]         =			infer_auto_device_map(a_						)
                 lowercase_      :Dict         =			1

           lowercase_      :str         =			AutoModelForCausalLM.from_pretrained(
               "EleutherAI/gpt-neo-125m"     ,				load_in_abit=a_     ,				device_map=a_     ,				)
           lowercase_      :Any         =			Accelerator()

           # This should not work and get value error
           with self.assertRaises(a_						):
                 lowercase_      :Tuple         =			accelerator.prepare(a_						)

           PartialState._reset_state()





     @slow
     @require_bnb
     @require_multi_gpu
     def 							lowercase__				(			self		: str						):





           """simple docstring"""




           from transformers import AutoModelForCausalLM

           with init_empty_weights():
                 lowercase_      :Dict         =			AutoModelForCausalLM.from_pretrained(
                     "EleutherAI/gpt-neo-125m"     ,				)
                 lowercase_      :Tuple         =			infer_auto_device_map(a_						)
                 lowercase_      :Tuple         =			1

           lowercase_      :List[Any]         =			AutoModelForCausalLM.from_pretrained(
               "EleutherAI/gpt-neo-125m"     ,				load_in_abit=a_     ,				device_map=a_     ,				)
           lowercase_      :Tuple         =			Accelerator()

           # This should work
           lowercase_      :Dict         =			accelerator.prepare(a_						)







     @require_cuda
     def 							lowercase__				(			self		: List[Any]						):





           """simple docstring"""




           lowercase_      :List[Any]         =			torch.nn.Linear(10     ,				10						)
           lowercase_      :List[str]         =			torch.optim.SGD(model.parameters()     ,				lr=0.01						)
           lowercase_      :Optional[Any]         =			Accelerator(cpu=a_						)
           lowercase_      :str         =			accelerator.prepare(a_						)









'''simple docstring'''


from abc import ABC, abstractmethod
from argparse import ArgumentParser
class 				a_       (    _lowerCAmelCase							):





     @staticmethod
     @abstractmethod
     def 							lowercase__				(			lowercase		: ArgumentParser						):





        """simple docstring"""




        raise NotImplementedError()







     @abstractmethod
     def 							lowercase__				(			self		: str						):





        """simple docstring"""




        raise NotImplementedError()


