

"""simple docstring"""




import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


SCREAMING_SNAKE_CASE_     :			Union[str, Any]	  =			logging.get_logger(__name__)


SCREAMING_SNAKE_CASE_     :			str	  =			{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt'''}

# See all BART models at https://huggingface.co/models?filter=bart
SCREAMING_SNAKE_CASE_     :			Union[str, Any]	  =			{
    '''vocab_file''': {
        '''facebook/bart-base''': '''https://huggingface.co/facebook/bart-base/resolve/main/vocab.json''',
        '''facebook/bart-large''': '''https://huggingface.co/facebook/bart-large/resolve/main/vocab.json''',
        '''facebook/bart-large-mnli''': '''https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json''',
        '''facebook/bart-large-cnn''': '''https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json''',
        '''facebook/bart-large-xsum''': '''https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json''',
        '''yjernite/bart_eli5''': '''https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json''',
    },
    '''merges_file''': {
        '''facebook/bart-base''': '''https://huggingface.co/facebook/bart-base/resolve/main/merges.txt''',
        '''facebook/bart-large''': '''https://huggingface.co/facebook/bart-large/resolve/main/merges.txt''',
        '''facebook/bart-large-mnli''': '''https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt''',
        '''facebook/bart-large-cnn''': '''https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt''',
        '''facebook/bart-large-xsum''': '''https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt''',
        '''yjernite/bart_eli5''': '''https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt''',
    },
}

SCREAMING_SNAKE_CASE_     :			Optional[Any]	  =			{
    '''facebook/bart-base''': 1024,
    '''facebook/bart-large''': 1024,
    '''facebook/bart-large-mnli''': 1024,
    '''facebook/bart-large-cnn''': 1024,
    '''facebook/bart-large-xsum''': 1024,
    '''yjernite/bart_eli5''': 1024,
}



@lru_cache()
def 	UpperCAmelCase__   (				)      ->      Tuple:




   """simple docstring"""
   lowerCamelCase__						=			(
       list(range(ord("!"   )	,    ord("~"   ) + 1   )   ) + list(range(ord("¡"   )	,    ord("¬"   ) + 1   )   ) + list(range(ord("®"   )	,    ord("ÿ"   ) + 1   )   )
   )
   lowerCamelCase__						=			bs[:]
   lowerCamelCase__						=			0
   for b in range(2**8   ):
      if b not in bs:
         bs.append(A__   )
         cs.append(2**8 + n   )
         n += 1
   lowerCamelCase__						=			[chr(A__   ) for n in cs]
   return dict(zip(A__	,    A__   )   )



def 	UpperCAmelCase__   (				A__   )      ->      List[Any]:




   """simple docstring"""
   lowerCamelCase__						=			set()
   lowerCamelCase__						=			word[0]
   for char in word[1:]:
      pairs.add((prev_char, char)   )
      lowerCamelCase__						=			char
   return pairs


class 		_A       (			__a					):
      __a								=	VOCAB_FILES_NAMES
      __a								=	PRETRAINED_VOCAB_FILES_MAP
      __a								=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      __a								=	['input_ids', 'attention_mask']





      def __init__(  self    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__="replace"    ,						SCREAMING_SNAKE_CASE__="<s>"    ,						SCREAMING_SNAKE_CASE__="</s>"    ,						SCREAMING_SNAKE_CASE__="</s>"    ,						SCREAMING_SNAKE_CASE__="<s>"    ,						SCREAMING_SNAKE_CASE__="<unk>"    ,						SCREAMING_SNAKE_CASE__="<pad>"    ,						SCREAMING_SNAKE_CASE__="<mask>"    ,						SCREAMING_SNAKE_CASE__=False    ,						**SCREAMING_SNAKE_CASE__    ,						)   ->					int:
         lowerCamelCase__						=			AddedToken(SCREAMING_SNAKE_CASE__    ,						lstrip=SCREAMING_SNAKE_CASE__    ,						rstrip=SCREAMING_SNAKE_CASE__		) if isinstance(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__		) else bos_token
         lowerCamelCase__						=			AddedToken(SCREAMING_SNAKE_CASE__    ,						lstrip=SCREAMING_SNAKE_CASE__    ,						rstrip=SCREAMING_SNAKE_CASE__		) if isinstance(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__		) else eos_token
         lowerCamelCase__						=			AddedToken(SCREAMING_SNAKE_CASE__    ,						lstrip=SCREAMING_SNAKE_CASE__    ,						rstrip=SCREAMING_SNAKE_CASE__		) if isinstance(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__		) else sep_token
         lowerCamelCase__						=			AddedToken(SCREAMING_SNAKE_CASE__    ,						lstrip=SCREAMING_SNAKE_CASE__    ,						rstrip=SCREAMING_SNAKE_CASE__		) if isinstance(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__		) else cls_token
         lowerCamelCase__						=			AddedToken(SCREAMING_SNAKE_CASE__    ,						lstrip=SCREAMING_SNAKE_CASE__    ,						rstrip=SCREAMING_SNAKE_CASE__		) if isinstance(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__		) else unk_token
         lowerCamelCase__						=			AddedToken(SCREAMING_SNAKE_CASE__    ,						lstrip=SCREAMING_SNAKE_CASE__    ,						rstrip=SCREAMING_SNAKE_CASE__		) if isinstance(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__		) else pad_token

         # Mask token behave like a normal word, i.e. include the space before it
         lowerCamelCase__						=			AddedToken(SCREAMING_SNAKE_CASE__    ,						lstrip=SCREAMING_SNAKE_CASE__    ,						rstrip=SCREAMING_SNAKE_CASE__		) if isinstance(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__		) else mask_token

         super().__init__(
             errors=SCREAMING_SNAKE_CASE__    ,						bos_token=SCREAMING_SNAKE_CASE__    ,						eos_token=SCREAMING_SNAKE_CASE__    ,						unk_token=SCREAMING_SNAKE_CASE__    ,						sep_token=SCREAMING_SNAKE_CASE__    ,						cls_token=SCREAMING_SNAKE_CASE__    ,						pad_token=SCREAMING_SNAKE_CASE__    ,						mask_token=SCREAMING_SNAKE_CASE__    ,						add_prefix_space=SCREAMING_SNAKE_CASE__    ,						**SCREAMING_SNAKE_CASE__    ,						)

         with open(SCREAMING_SNAKE_CASE__    ,						encoding="utf-8"		) as vocab_handle:
            lowerCamelCase__						=			json.load(SCREAMING_SNAKE_CASE__		)
         lowerCamelCase__						=			{v: k for k, v in self.encoder.items()}
         lowerCamelCase__						=			errors  # how to handle errors in decoding
         lowerCamelCase__						=			bytes_to_unicode()
         lowerCamelCase__						=			{v: k for k, v in self.byte_encoder.items()}
         with open(SCREAMING_SNAKE_CASE__    ,						encoding="utf-8"		) as merges_handle:
            lowerCamelCase__						=			merges_handle.read().split("\n"		)[1:-1]
         lowerCamelCase__						=			[tuple(merge.split()		) for merge in bpe_merges]
         lowerCamelCase__						=			dict(zip(SCREAMING_SNAKE_CASE__    ,						range(len(SCREAMING_SNAKE_CASE__		)		)		)		)
         lowerCamelCase__						=			{}
         lowerCamelCase__						=			add_prefix_space

         # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
         lowerCamelCase__						=			re.compile(r"'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"		)





      @property
      def 					_lowerCamelCase  (  self		)   ->					Optional[Any]:
         return len(self.encoder		)





      def 					_lowerCamelCase  (  self		)   ->					Optional[int]:
         return dict(self.encoder    ,						**self.added_tokens_encoder		)





      def 					_lowerCamelCase  (  self    ,						SCREAMING_SNAKE_CASE__		)   ->					Any:
         if token in self.cache:
            return self.cache[token]
         lowerCamelCase__						=			tuple(SCREAMING_SNAKE_CASE__		)
         lowerCamelCase__						=			get_pairs(SCREAMING_SNAKE_CASE__		)

         if not pairs:
            return token

         while True:
            lowerCamelCase__						=			min(SCREAMING_SNAKE_CASE__    ,						key=lambda SCREAMING_SNAKE_CASE__		: self.bpe_ranks.get(SCREAMING_SNAKE_CASE__    ,						float("inf"		)		)		)
            if bigram not in self.bpe_ranks:
               break
            lowerCamelCase__					,       lowerCamelCase__						=			bigram
            lowerCamelCase__						=			[]
            lowerCamelCase__						=			0
            while i < len(SCREAMING_SNAKE_CASE__		):
               try:
                  lowerCamelCase__						=			word.index(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__		)
               except ValueError:
                  new_word.extend(word[i:]		)
                  break
               else:
                  new_word.extend(word[i:j]		)
                  lowerCamelCase__						=			j

               if word[i] == first and i < len(SCREAMING_SNAKE_CASE__		) - 1 and word[i + 1] == second:
                  new_word.append(first + second		)
                  i += 2
               else:
                  new_word.append(word[i]		)
                  i += 1
            lowerCamelCase__						=			tuple(SCREAMING_SNAKE_CASE__		)
            lowerCamelCase__						=			new_word
            if len(SCREAMING_SNAKE_CASE__		) == 1:
               break
            else:
               lowerCamelCase__						=			get_pairs(SCREAMING_SNAKE_CASE__		)
         lowerCamelCase__						=			" ".join(SCREAMING_SNAKE_CASE__		)
         lowerCamelCase__						=			word
         return word





      def 					_lowerCamelCase  (  self    ,						SCREAMING_SNAKE_CASE__		)   ->					str:
         lowerCamelCase__						=			[]
         for token in re.findall(self.pat    ,						SCREAMING_SNAKE_CASE__		):
            lowerCamelCase__						=			"".join(
                self.byte_encoder[b] for b in token.encode("utf-8"		)		)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
            bpe_tokens.extend(bpe_token for bpe_token in self.bpe(SCREAMING_SNAKE_CASE__		).split(" "		)		)
         return bpe_tokens





      def 					_lowerCamelCase  (  self    ,						SCREAMING_SNAKE_CASE__		)   ->					Dict:
         return self.encoder.get(SCREAMING_SNAKE_CASE__    ,						self.encoder.get(self.unk_token		)		)





      def 					_lowerCamelCase  (  self    ,						SCREAMING_SNAKE_CASE__		)   ->					Union[str, Any]:
         return self.decoder.get(SCREAMING_SNAKE_CASE__		)





      def 					_lowerCamelCase  (  self    ,						SCREAMING_SNAKE_CASE__		)   ->					str:
         lowerCamelCase__						=			"".join(SCREAMING_SNAKE_CASE__		)
         lowerCamelCase__						=			bytearray([self.byte_decoder[c] for c in text]		).decode("utf-8"    ,						errors=self.errors		)
         return text





      def 					_lowerCamelCase  (  self    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__ = None		)   ->					Tuple[str]:
         if not os.path.isdir(SCREAMING_SNAKE_CASE__		):
            logger.error(f'Vocabulary path ({save_directory}) should be a directory'		)
            return
         lowerCamelCase__						=			os.path.join(
             SCREAMING_SNAKE_CASE__    ,						(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]		)
         lowerCamelCase__						=			os.path.join(
             SCREAMING_SNAKE_CASE__    ,						(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]		)

         with open(SCREAMING_SNAKE_CASE__    ,						"w"    ,						encoding="utf-8"		) as f:
            f.write(json.dumps(self.encoder    ,						indent=2    ,						sort_keys=SCREAMING_SNAKE_CASE__    ,						ensure_ascii=SCREAMING_SNAKE_CASE__		) + "\n"		)

         lowerCamelCase__						=			0
         with open(SCREAMING_SNAKE_CASE__    ,						"w"    ,						encoding="utf-8"		) as writer:
            writer.write("#version: 0.2\n"		)
            for bpe_tokens, token_index in sorted(self.bpe_ranks.items()    ,						key=lambda SCREAMING_SNAKE_CASE__		: kv[1]		):
               if index != token_index:
                  logger.warning(
                      f'Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'
                      " Please check that the tokenizer is not corrupted!"		)
                  lowerCamelCase__						=			token_index
               writer.write(" ".join(SCREAMING_SNAKE_CASE__		) + "\n"		)
               index += 1

         return vocab_file, merge_file





      def 					_lowerCamelCase  (  self    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__ = None		)   ->					List[int]:
         if token_ids_a is None:
            return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
         lowerCamelCase__						=			[self.cls_token_id]
         lowerCamelCase__						=			[self.sep_token_id]
         return cls + token_ids_a + sep + sep + token_ids_a + sep





      def 					_lowerCamelCase  (  self    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__ = None    ,						SCREAMING_SNAKE_CASE__ = False		)   ->					List[int]:
         if already_has_special_tokens:
            return super().get_special_tokens_mask(
                token_ids_a=SCREAMING_SNAKE_CASE__    ,						token_ids_a=SCREAMING_SNAKE_CASE__    ,						already_has_special_tokens=SCREAMING_SNAKE_CASE__		)

         if token_ids_a is None:
            return [1] + ([0] * len(SCREAMING_SNAKE_CASE__		)) + [1]
         return [1] + ([0] * len(SCREAMING_SNAKE_CASE__		)) + [1, 1] + ([0] * len(SCREAMING_SNAKE_CASE__		)) + [1]





      def 					_lowerCamelCase  (  self    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__ = None		)   ->					List[int]:
         lowerCamelCase__						=			[self.sep_token_id]
         lowerCamelCase__						=			[self.cls_token_id]

         if token_ids_a is None:
            return len(cls + token_ids_a + sep		) * [0]
         return len(cls + token_ids_a + sep + sep + token_ids_a + sep		) * [0]





      def 					_lowerCamelCase  (  self    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__=False    ,						**SCREAMING_SNAKE_CASE__		)   ->					int:
         lowerCamelCase__						=			kwargs.pop("add_prefix_space"    ,						self.add_prefix_space		)
         if (is_split_into_words or add_prefix_space) and (len(SCREAMING_SNAKE_CASE__		) > 0 and not text[0].isspace()):
            lowerCamelCase__						=			" " + text
         return (text, kwargs)







"""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__   (				)      ->      List[Any]:




   """simple docstring"""
   lowerCamelCase__						=			torch.nn.Linear(2	,    4   )
   lowerCamelCase__						=			torch.optim.AdamW(model.parameters()	,    lr=1.0   )
   lowerCamelCase__						=			torch.optim.lr_scheduler.OneCycleLR(A__	,    max_lr=0.01	,    steps_per_epoch=2	,    epochs=1   )
   lowerCamelCase__						=			DataLoader(TensorDataset(torch.tensor([1, 2, 3]   )   )   )
   lowerCamelCase__						=			DataLoader(TensorDataset(torch.tensor([4, 5, 6]   )   )   )

   return model, optimizer, scheduler, train_dl, valid_dl



def 	UpperCAmelCase__   (				A__   )      ->      Any:




   """simple docstring"""
   return (model.weight.abs().sum() + model.bias.abs().sum()).item()



def 	UpperCAmelCase__   (				A__   )      ->      Any:




   """simple docstring"""
   lowerCamelCase__						=			torch.nn.Linear(*tuple(model.weight.T.shape   )   ).state_dict()
   model.load_state_dict(A__   )


class 		_A       (			__a					):





      @require_cuda
      def 					_lowerCamelCase  (  self		)   ->					Optional[Any]:
         lowerCamelCase__						=			Accelerator()
         assert PartialState._shared_state["_cpu"] is False
         assert PartialState._shared_state["device"].type == "cuda"
         with self.assertRaises(SCREAMING_SNAKE_CASE__		):
            lowerCamelCase__						=			Accelerator(cpu=SCREAMING_SNAKE_CASE__		)





      def 					_lowerCamelCase  (  self		)   ->					Union[str, Any]:
         lowerCamelCase__						=			Accelerator()
         lowerCamelCase__						=			GradientState()
         assert state.num_steps == 1
         lowerCamelCase__						=			4
         assert state.num_steps == 4

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





      def 					_lowerCamelCase  (  self		)   ->					str:
         lowerCamelCase__						=			Accelerator()
         lowerCamelCase__					,       lowerCamelCase__					,       lowerCamelCase__					,       lowerCamelCase__					,       lowerCamelCase__						=			create_components()

         (
             (
             lowerCamelCase__
         )					,       (
             lowerCamelCase__
         )					,       (
             lowerCamelCase__
         )					,       (
             lowerCamelCase__
         )					,       (
             lowerCamelCase__
         )					,       
         )						=			accelerator.prepare(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_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 					_lowerCamelCase  (  self		)   ->					Union[str, Any]:
         lowerCamelCase__						=			Accelerator()
         lowerCamelCase__					,       lowerCamelCase__					,       lowerCamelCase__					,       lowerCamelCase__					,       lowerCamelCase__						=			create_components()
         accelerator.prepare(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_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 					_lowerCamelCase  (  self		)   ->					Dict:
         PartialState._reset_state()

         # Mock torch.cuda.set_device to avoid an exception as the device doesn't exist
         def noop(*SCREAMING_SNAKE_CASE__    ,						**SCREAMING_SNAKE_CASE__		):
            pass

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





      def 					_lowerCamelCase  (  self		)   ->					Optional[Any]:
         lowerCamelCase__						=			Accelerator()
         lowerCamelCase__					,       lowerCamelCase__					,       lowerCamelCase__					,       lowerCamelCase__					,       lowerCamelCase__						=			create_components()
         accelerator.prepare(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__		)

         lowerCamelCase__						=			get_signature(SCREAMING_SNAKE_CASE__		)

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

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

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





      def 					_lowerCamelCase  (  self		)   ->					Any:
         lowerCamelCase__						=			Accelerator()
         lowerCamelCase__					,       lowerCamelCase__					,       lowerCamelCase__					,       lowerCamelCase__					,       lowerCamelCase__						=			create_components()
         accelerator.prepare(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__		)

         lowerCamelCase__						=			get_signature(SCREAMING_SNAKE_CASE__		)

         # saving hook
         def save_config(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__		):
            lowerCamelCase__						=			{"class_name": models[0].__class__.__name__}

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

        # loading hook
         def load_config(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__		):
            with open(os.path.join(SCREAMING_SNAKE_CASE__    ,						"data.json"		)    ,						"r"		) as f:
               lowerCamelCase__						=			json.load(SCREAMING_SNAKE_CASE__		)

            lowerCamelCase__						=			config["class_name"]

         lowerCamelCase__						=			accelerator.register_save_state_pre_hook(SCREAMING_SNAKE_CASE__		)
         lowerCamelCase__						=			accelerator.register_load_state_pre_hook(SCREAMING_SNAKE_CASE__		)

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

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

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

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

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

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

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

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





      def 					_lowerCamelCase  (  self		)   ->					Union[str, Any]:
         lowerCamelCase__						=			Accelerator()
         lowerCamelCase__					,       lowerCamelCase__					,       lowerCamelCase__					,       lowerCamelCase__					,       lowerCamelCase__						=			create_components()
         lowerCamelCase__						=			None

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





      def 					_lowerCamelCase  (  self		)   ->					List[str]:
         lowerCamelCase__						=			Accelerator()
         lowerCamelCase__					,       lowerCamelCase__					,       lowerCamelCase__					,       lowerCamelCase__					,       lowerCamelCase__						=			create_components()
         lowerCamelCase__						=			[1, 2, 3]

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





      @slow
      @require_bnb
      def 					_lowerCamelCase  (  self		)   ->					str:
         from transformers import AutoModelForCausalLM

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

         # This should work
         lowerCamelCase__						=			accelerator.prepare(SCREAMING_SNAKE_CASE__		)





      @slow
      @require_bnb
      def 					_lowerCamelCase  (  self		)   ->					Tuple:
         from transformers import AutoModelForCausalLM

         lowerCamelCase__						=			Accelerator()

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

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

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





      @slow
      @require_bnb
      @require_multi_gpu
      def 					_lowerCamelCase  (  self		)   ->					Dict:
         from transformers import AutoModelForCausalLM

         lowerCamelCase__						=			{"distributed_type": DistributedType.MULTI_GPU}

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

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

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

         PartialState._reset_state()





      @slow
      @require_bnb
      @require_multi_gpu
      def 					_lowerCamelCase  (  self		)   ->					List[Any]:
         from transformers import AutoModelForCausalLM

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

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

         # This should work
         lowerCamelCase__						=			accelerator.prepare(SCREAMING_SNAKE_CASE__		)





      @require_cuda
      def 					_lowerCamelCase  (  self		)   ->					List[str]:
         lowerCamelCase__						=			torch.nn.Linear(10    ,						10		)
         lowerCamelCase__						=			torch.optim.SGD(model.parameters()    ,						lr=0.01		)
         lowerCamelCase__						=			Accelerator(cpu=SCREAMING_SNAKE_CASE__		)
         lowerCamelCase__						=			accelerator.prepare(SCREAMING_SNAKE_CASE__		)




