
from ...configuration_utils import PretrainedConfig
from ...utils import logging


_snake_case      :							Optional[int]     	=    logging.get_logger(__name__)

_snake_case      :							int     	=    {
    "sayakpaul/vit-msn-base": "https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json",
    # See all ViT MSN models at https://huggingface.co/models?filter=vit_msn
}





class   UpperCamelCase_      (      __a		):







						'''simple docstring'''



						UpperCamelCase      :  Dict				   =					'''vit_msn'''





						def __init__(			self							:Union[str, Any]		,    lowerCAmelCase__							:Dict=768		,    lowerCAmelCase__							:Optional[int]=12		,    lowerCAmelCase__							:str=12		,    lowerCAmelCase__							:List[Any]=3072		,    lowerCAmelCase__							:Dict="gelu"		,    lowerCAmelCase__							:int=0.0		,    lowerCAmelCase__							:Optional[int]=0.0		,    lowerCAmelCase__							:List[Any]=0.02		,    lowerCAmelCase__							:Optional[Any]=1E-0_6		,    lowerCAmelCase__							:List[Any]=224		,    lowerCAmelCase__							:List[Any]=16		,    lowerCAmelCase__							:Tuple=3		,    lowerCAmelCase__							:Dict=True		,    **lowerCAmelCase__							:Optional[Any]		,    )  ->Dict:
										super().__init__(**lowerCAmelCase__     )

										lowercase         =      hidden_size
										lowercase         =      num_hidden_layers
										lowercase         =      num_attention_heads
										lowercase         =      intermediate_size
										lowercase         =      hidden_act
										lowercase         =      hidden_dropout_prob
										lowercase         =      attention_probs_dropout_prob
										lowercase         =      initializer_range
										lowercase         =      layer_norm_eps
										lowercase         =      image_size
										lowercase         =      patch_size
										lowercase         =      num_channels
										lowercase         =      qkv_bias


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  __snake_case							(	):







				'''simple docstring'''


				lowercase         =      torch.nn.Linear(2		,    4						)
				lowercase         =      torch.optim.AdamW(model.parameters()		,    lr=1.0						)
				lowercase         =      torch.optim.lr_scheduler.OneCycleLR(__magic_name__		,    max_lr=0.0_1		,    steps_per_epoch=2		,    epochs=1						)
				lowercase         =      DataLoader(TensorDataset(torch.tensor([1, 2, 3]						)						)						)
				lowercase         =      DataLoader(TensorDataset(torch.tensor([4, 5, 6]						)						)						)

				return model, optimizer, scheduler, train_dl, valid_dl

def  __snake_case							(	__magic_name__						):







				'''simple docstring'''


				return (model.weight.abs().sum() + model.bias.abs().sum()).item()

def  __snake_case							(	__magic_name__						):







				'''simple docstring'''


				lowercase         =      torch.nn.Linear(*tuple(model.weight.T.shape						)						).state_dict()
				model.load_state_dict(__magic_name__						)





class   UpperCamelCase_      (      __a		):







						'''simple docstring'''



						@require_cuda
						def        SCREAMING_SNAKE_CASE(			self							:Any     )  ->str:
										lowercase         =      Accelerator()
										assert PartialState._shared_state["_cpu"] is False
										assert PartialState._shared_state["device"].type == "cuda"
										with self.assertRaises(lowerCAmelCase__     ):
														lowercase         =      Accelerator(cpu=lowerCAmelCase__     )





						def        SCREAMING_SNAKE_CASE(			self							:Dict     )  ->Dict:
										lowercase         =      Accelerator()
										lowercase         =      GradientState()
										assert state.num_steps == 1
										lowercase         =      4
										assert state.num_steps == 4

										assert state.sync_gradients is True
										lowercase         =      False
										assert state.sync_gradients is False
										GradientState._reset_state()





						def        SCREAMING_SNAKE_CASE(			self							:int     )  ->Tuple:
										lowercase         =      Accelerator()
										lowercase     ,	lowercase     ,	lowercase     ,	lowercase     ,	lowercase         =      create_components()

										(
										    (
										    lowercase
										)     ,	(
										    lowercase
										)     ,	(
										    lowercase
										)     ,	(
										    lowercase
										)     ,	(
										    lowercase
										)     ,	
										)         =      accelerator.prepare(lowerCAmelCase__		,    lowerCAmelCase__		,    lowerCAmelCase__		,    lowerCAmelCase__		,    lowerCAmelCase__     )

										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        SCREAMING_SNAKE_CASE(			self							:List[Any]     )  ->Tuple:
										lowercase         =      Accelerator()
										lowercase     ,	lowercase     ,	lowercase     ,	lowercase     ,	lowercase         =      create_components()
										accelerator.prepare(lowerCAmelCase__		,    lowerCAmelCase__		,    lowerCAmelCase__		,    lowerCAmelCase__		,    lowerCAmelCase__     )
										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        SCREAMING_SNAKE_CASE(			self							:List[str]     )  ->Optional[int]:
										PartialState._reset_state()

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

										with patch("torch.cuda.set_device"		,    lowerCAmelCase__     ), patch_environment(ACCELERATE_TORCH_DEVICE="cuda:64"     ):
														lowercase         =      Accelerator()
														self.assertEqual(str(accelerator.state.device     )		,    "cuda:64"     )





						def        SCREAMING_SNAKE_CASE(			self							:Union[str, Any]     )  ->Union[str, Any]:
										lowercase         =      Accelerator()
										lowercase     ,	lowercase     ,	lowercase     ,	lowercase     ,	lowercase         =      create_components()
										accelerator.prepare(lowerCAmelCase__		,    lowerCAmelCase__		,    lowerCAmelCase__		,    lowerCAmelCase__		,    lowerCAmelCase__     )

										lowercase         =      get_signature(lowerCAmelCase__     )

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

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

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





						def        SCREAMING_SNAKE_CASE(			self							:List[str]     )  ->int:
										lowercase         =      Accelerator()
										lowercase     ,	lowercase     ,	lowercase     ,	lowercase     ,	lowercase         =      create_components()
										accelerator.prepare(lowerCAmelCase__		,    lowerCAmelCase__		,    lowerCAmelCase__		,    lowerCAmelCase__		,    lowerCAmelCase__     )

										lowercase         =      get_signature(lowerCAmelCase__     )

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

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

        # loading hook
										def load_config(lowerCAmelCase__							:Dict		,    lowerCAmelCase__							:List[str]     ):
														with open(os.path.join(lowerCAmelCase__		,    "data.json"     )		,    "r"     ) as f:
																		lowercase         =      json.load(lowerCAmelCase__     )

														lowercase         =      config["class_name"]

										lowercase         =      accelerator.register_save_state_pre_hook(lowerCAmelCase__     )
										lowercase         =      accelerator.register_load_state_pre_hook(lowerCAmelCase__     )

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

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

														# random class name to verify correct one is loaded
														lowercase         =      "random"

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

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

														# random class name to verify correct one is loaded
														lowercase         =      "random"

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

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





						def        SCREAMING_SNAKE_CASE(			self							:Optional[int]     )  ->List[Any]:
										lowercase         =      Accelerator()
										lowercase     ,	lowercase     ,	lowercase     ,	lowercase     ,	lowercase         =      create_components()
										lowercase         =      None

										# This should work
										lowercase     ,	lowercase     ,	lowercase     ,	lowercase     ,	lowercase     ,	lowercase         =      accelerator.prepare(
										    lowerCAmelCase__		,    lowerCAmelCase__		,    lowerCAmelCase__		,    lowerCAmelCase__		,    lowerCAmelCase__		,    lowerCAmelCase__     )
										self.assertTrue(dummy_obj is None     )





						def        SCREAMING_SNAKE_CASE(			self							:Tuple     )  ->Optional[int]:
										lowercase         =      Accelerator()
										lowercase     ,	lowercase     ,	lowercase     ,	lowercase     ,	lowercase         =      create_components()
										lowercase         =      [1, 2, 3]

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





						@slow
						@require_bnb
						def        SCREAMING_SNAKE_CASE(			self							:Union[str, Any]     )  ->Tuple:
										from transformers import AutoModelForCausalLM

										lowercase         =      AutoModelForCausalLM.from_pretrained(
										    "EleutherAI/gpt-neo-125m"		,    load_in_abit=lowerCAmelCase__		,    device_map={"": 0}		,    )
										lowercase         =      Accelerator()

										# This should work
										lowercase         =      accelerator.prepare(lowerCAmelCase__     )





						@slow
						@require_bnb
						def        SCREAMING_SNAKE_CASE(			self							:Tuple     )  ->List[str]:
										from transformers import AutoModelForCausalLM

										lowercase         =      Accelerator()

										with init_empty_weights():
														lowercase         =      AutoModelForCausalLM.from_pretrained(
														    "EleutherAI/gpt-neo-125m"		,    )
														model.tie_weights()
														lowercase         =      infer_auto_device_map(lowerCAmelCase__     )
														lowercase         =      "cpu"

										lowercase         =      AutoModelForCausalLM.from_pretrained(
										    "EleutherAI/gpt-neo-125m"		,    device_map=lowerCAmelCase__		,    load_in_abit=lowerCAmelCase__		,    llm_inta_enable_fpaa_cpu_offload=lowerCAmelCase__     )

										# This should not work and get value error
										with self.assertRaises(lowerCAmelCase__     ):
														lowercase         =      accelerator.prepare(lowerCAmelCase__     )





						@slow
						@require_bnb
						@require_multi_gpu
						def        SCREAMING_SNAKE_CASE(			self							:Tuple     )  ->int:
										from transformers import AutoModelForCausalLM

										lowercase         =      {"distributed_type": DistributedType.MULTI_GPU}

										with init_empty_weights():
														lowercase         =      AutoModelForCausalLM.from_pretrained(
														    "EleutherAI/gpt-neo-125m"		,    )
														model.tie_weights()
														lowercase         =      infer_auto_device_map(lowerCAmelCase__     )
														lowercase         =      1

										lowercase         =      AutoModelForCausalLM.from_pretrained(
										    "EleutherAI/gpt-neo-125m"		,    load_in_abit=lowerCAmelCase__		,    device_map=lowerCAmelCase__		,    )
										lowercase         =      Accelerator()

										# This should not work and get value error
										with self.assertRaises(lowerCAmelCase__     ):
														lowercase         =      accelerator.prepare(lowerCAmelCase__     )

										PartialState._reset_state()





						@slow
						@require_bnb
						@require_multi_gpu
						def        SCREAMING_SNAKE_CASE(			self							:List[str]     )  ->Tuple:
										from transformers import AutoModelForCausalLM

										with init_empty_weights():
														lowercase         =      AutoModelForCausalLM.from_pretrained(
														    "EleutherAI/gpt-neo-125m"		,    )
														lowercase         =      infer_auto_device_map(lowerCAmelCase__     )
														lowercase         =      1

										lowercase         =      AutoModelForCausalLM.from_pretrained(
										    "EleutherAI/gpt-neo-125m"		,    load_in_abit=lowerCAmelCase__		,    device_map=lowerCAmelCase__		,    )
										lowercase         =      Accelerator()

										# This should work
										lowercase         =      accelerator.prepare(lowerCAmelCase__     )





						@require_cuda
						def        SCREAMING_SNAKE_CASE(			self							:Optional[int]     )  ->Any:
										lowercase         =      torch.nn.Linear(10		,    10     )
										lowercase         =      torch.optim.SGD(model.parameters()		,    lr=0.01     )
										lowercase         =      Accelerator(cpu=lowerCAmelCase__     )
										lowercase         =      accelerator.prepare(lowerCAmelCase__     )
