



'''simple docstring'''





import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


A					:       Any									=     get_tests_dir("""fixtures/test_sentencepiece.model""")


if is_torch_available():
      from transformers.models.mbart.modeling_mbart import shift_tokens_right

A					:       Union[str, Any]									=     250_004
A					:       str									=     250_020





@require_sentencepiece
@require_tokenizers
class 				lowerCAmelCase_						(			__a    ,     unittest.TestCase		):
    __UpperCAmelCase				=			MBartTokenizer
    __UpperCAmelCase				=			MBartTokenizerFast
    __UpperCAmelCase				=			True
    __UpperCAmelCase				=			True





    def 	__snake_case  (							self							:							Tuple      ):



       '''simple docstring'''







       super().setUp()

       # We have a SentencePiece fixture for testing
       snake_case       :				List[Any]		    =MBartTokenizer(lowerCAmelCase__,							keep_accents=lowerCAmelCase__      )
       tokenizer.save_pretrained(self.tmpdirname      )





    def 	__snake_case  (							self							:							Tuple      ):



       '''simple docstring'''







       snake_case       :				List[str]		    =MBartTokenizer(lowerCAmelCase__,							keep_accents=lowerCAmelCase__      )

       snake_case       :				Tuple		    =tokenizer.tokenize('''This is a test'''      )
       self.assertListEqual(lowerCAmelCase__,							['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']      )

       self.assertListEqual(
           tokenizer.convert_tokens_to_ids(lowerCAmelCase__      ),							[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]],							)

       snake_case       :				Union[str, Any]		    =tokenizer.tokenize('''I was born in 92000, and this is falsé.'''      )
       self.assertListEqual(
           lowerCAmelCase__,							[
               SPIECE_UNDERLINE + '''I''',
               SPIECE_UNDERLINE + '''was''',
               SPIECE_UNDERLINE + '''b''',
               '''or''',
               '''n''',
               SPIECE_UNDERLINE + '''in''',
               SPIECE_UNDERLINE + '''''',
               '''9''',
               '''2''',
               '''0''',
               '''0''',
               '''0''',
               ''',''',
               SPIECE_UNDERLINE + '''and''',
               SPIECE_UNDERLINE + '''this''',
               SPIECE_UNDERLINE + '''is''',
               SPIECE_UNDERLINE + '''f''',
               '''al''',
               '''s''',
               '''é''',
               '''.''',
           ],							)
       snake_case       :				List[Any]		    =tokenizer.convert_tokens_to_ids(lowerCAmelCase__      )
       self.assertListEqual(
           lowerCAmelCase__,							[
               value + tokenizer.fairseq_offset
               for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
               #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
           ],							)

       snake_case       :				int		    =tokenizer.convert_ids_to_tokens(lowerCAmelCase__      )
       self.assertListEqual(
           lowerCAmelCase__,							[
               SPIECE_UNDERLINE + '''I''',
               SPIECE_UNDERLINE + '''was''',
               SPIECE_UNDERLINE + '''b''',
               '''or''',
               '''n''',
               SPIECE_UNDERLINE + '''in''',
               SPIECE_UNDERLINE + '''''',
               '''<unk>''',
               '''2''',
               '''0''',
               '''0''',
               '''0''',
               ''',''',
               SPIECE_UNDERLINE + '''and''',
               SPIECE_UNDERLINE + '''this''',
               SPIECE_UNDERLINE + '''is''',
               SPIECE_UNDERLINE + '''f''',
               '''al''',
               '''s''',
               '''<unk>''',
               '''.''',
           ],							)






    def 	__snake_case  (							self							:							Any      ):



       '''simple docstring'''







       if not self.test_slow_tokenizer:
          # as we don't have a slow version, we can't compare the outputs between slow and fast versions
          return

       snake_case       :				Optional[Any]		    =(self.rust_tokenizer_class, '''hf-internal-testing/tiny-random-mbart''', {})
       for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
          with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''      ):
             snake_case       :				Tuple		    =self.rust_tokenizer_class.from_pretrained(lowerCAmelCase__,							**lowerCAmelCase__      )
             snake_case       :				List[str]		    =self.tokenizer_class.from_pretrained(lowerCAmelCase__,							**lowerCAmelCase__      )

             snake_case       :				Optional[int]		    =tempfile.mkdtemp()

             snake_case       :				Optional[Any]		    =tokenizer_r.save_pretrained(lowerCAmelCase__      )
             snake_case       :				Optional[Any]		    =tokenizer_p.save_pretrained(lowerCAmelCase__      )

             # Checks it save with the same files + the tokenizer.json file for the fast one
             self.assertTrue(any('''tokenizer.json''' in f for f in tokenizer_r_files      )      )
             snake_case       :				Dict		    =tuple(f for f in tokenizer_r_files if '''tokenizer.json''' not in f      )
             self.assertSequenceEqual(lowerCAmelCase__,							lowerCAmelCase__      )

             # Checks everything loads correctly in the same way
             snake_case       :				int		    =tokenizer_r.from_pretrained(lowerCAmelCase__      )
             snake_case       :				Optional[Any]		    =tokenizer_p.from_pretrained(lowerCAmelCase__      )

             # Check special tokens are set accordingly on Rust and Python
             for key in tokenizer_pp.special_tokens_map:
                self.assertTrue(hasattr(lowerCAmelCase__,							lowerCAmelCase__      )      )
                # self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
                # self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

             shutil.rmtree(lowerCAmelCase__      )

             # Save tokenizer rust, legacy_format=True
             snake_case       :				Tuple		    =tempfile.mkdtemp()

             snake_case       :				Any		    =tokenizer_r.save_pretrained(lowerCAmelCase__,							legacy_format=lowerCAmelCase__      )
             snake_case       :				Union[str, Any]		    =tokenizer_p.save_pretrained(lowerCAmelCase__      )

             # Checks it save with the same files
             self.assertSequenceEqual(lowerCAmelCase__,							lowerCAmelCase__      )

             # Checks everything loads correctly in the same way
             snake_case       :				Optional[int]		    =tokenizer_r.from_pretrained(lowerCAmelCase__      )
             snake_case       :				Union[str, Any]		    =tokenizer_p.from_pretrained(lowerCAmelCase__      )

             # Check special tokens are set accordingly on Rust and Python
             for key in tokenizer_pp.special_tokens_map:
                self.assertTrue(hasattr(lowerCAmelCase__,							lowerCAmelCase__      )      )

             shutil.rmtree(lowerCAmelCase__      )

             # Save tokenizer rust, legacy_format=False
             snake_case       :				Union[str, Any]		    =tempfile.mkdtemp()

             snake_case       :				Optional[int]		    =tokenizer_r.save_pretrained(lowerCAmelCase__,							legacy_format=lowerCAmelCase__      )
             snake_case       :				Any		    =tokenizer_p.save_pretrained(lowerCAmelCase__      )

             # Checks it saved the tokenizer.json file
             self.assertTrue(any('''tokenizer.json''' in f for f in tokenizer_r_files      )      )

             # Checks everything loads correctly in the same way
             snake_case       :				Any		    =tokenizer_r.from_pretrained(lowerCAmelCase__      )
             snake_case       :				List[Any]		    =tokenizer_p.from_pretrained(lowerCAmelCase__      )

             # Check special tokens are set accordingly on Rust and Python
             for key in tokenizer_pp.special_tokens_map:
                self.assertTrue(hasattr(lowerCAmelCase__,							lowerCAmelCase__      )      )

             shutil.rmtree(lowerCAmelCase__      )





@require_torch
@require_sentencepiece
@require_tokenizers
class 				lowerCAmelCase_						(			unittest.TestCase		):
    __UpperCAmelCase				=			'''facebook/mbart-large-en-ro'''
    __UpperCAmelCase				=			[
        ''' UN Chief Says There Is No Military Solution in Syria''',
        ''' Secretary-General Ban Ki-moon says his response to Russia\'s stepped up military support for Syria is that "there is no military solution" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.''',
    ]
    __UpperCAmelCase				=			[
        '''Şeful ONU declară că nu există o soluţie militară în Siria''',
        '''Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei'''
        ''' pentru Siria este că "nu există o soluţie militară" la conflictul de aproape cinci ani şi că noi arme nu vor'''
        ''' face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.''',
    ]
    __UpperCAmelCase				=			[8274, 12_7873, 2_5916, 7, 8622, 2071, 438, 6_7485, 53, 18_7895, 23, 5_1712, 2, EN_CODE]





    @classmethod
    def 	__snake_case  (							cls							:							Optional[int]      ):



       '''simple docstring'''







       snake_case       :				Optional[Any]		    =MBartTokenizer.from_pretrained(
           cls.checkpoint_name,							src_lang='''en_XX''',							tgt_lang='''ro_RO'''      )
       snake_case       :				str		    =1
       return cls





    def 	__snake_case  (							self							:							Optional[Any]      ):



       '''simple docstring'''







       self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''ar_AR'''],							250_001      )
       self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''en_EN'''],							250_004      )
       self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''ro_RO'''],							250_020      )





    def 	__snake_case  (							self							:							Optional[Any]      ):



       '''simple docstring'''







       snake_case       :				Optional[int]		    =self.tokenizer.batch_encode_plus(self.src_text      ).input_ids[0]
       self.assertListEqual(self.expected_src_tokens,							lowerCAmelCase__      )





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



       '''simple docstring'''







       self.assertIn(lowerCAmelCase__,							self.tokenizer.all_special_ids      )
       snake_case       :				int		    =[RO_CODE, 884, 9_019, 96, 9, 916, 86_792, 36, 18_743, 15_596, 5, 2]
       snake_case       :				int		    =self.tokenizer.decode(lowerCAmelCase__,							skip_special_tokens=lowerCAmelCase__      )
       snake_case       :				Any		    =self.tokenizer.decode(generated_ids[1:],							skip_special_tokens=lowerCAmelCase__      )
       self.assertEqual(lowerCAmelCase__,							lowerCAmelCase__      )
       self.assertNotIn(self.tokenizer.eos_token,							lowerCAmelCase__      )





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



       '''simple docstring'''







       snake_case       :				Optional[int]		    =['''this is gunna be a long sentence ''' * 20]
       assert isinstance(src_text[0],							lowerCAmelCase__      )
       snake_case       :				Tuple		    =10
       snake_case       :				Optional[int]		    =self.tokenizer(lowerCAmelCase__,							max_length=lowerCAmelCase__,							truncation=lowerCAmelCase__      ).input_ids[0]
       self.assertEqual(ids[-2],							2      )
       self.assertEqual(ids[-1],							lowerCAmelCase__      )
       self.assertEqual(len(lowerCAmelCase__      ),							lowerCAmelCase__      )





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



       '''simple docstring'''







       self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['''<mask>''', '''ar_AR''']      ),							[250_026, 250_001]      )





    def 	__snake_case  (							self							:							List[str]      ):



       '''simple docstring'''







       snake_case       :				Tuple		    =tempfile.mkdtemp()
       snake_case       :				Any		    =self.tokenizer.fairseq_tokens_to_ids
       self.tokenizer.save_pretrained(lowerCAmelCase__      )
       snake_case       :				List[Any]		    =MBartTokenizer.from_pretrained(lowerCAmelCase__      )
       self.assertDictEqual(new_tok.fairseq_tokens_to_ids,							lowerCAmelCase__      )





    @require_torch
    def 	__snake_case  (							self							:							Union[str, Any]      ):



       '''simple docstring'''







       snake_case       :				int		    =self.tokenizer(self.src_text,							text_target=self.tgt_text,							padding=lowerCAmelCase__,							return_tensors='''pt'''      )
       snake_case       :				List[str]		    =shift_tokens_right(batch['''labels'''],							self.tokenizer.pad_token_id      )

       # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
       assert batch.input_ids[1][-2:].tolist() == [2, EN_CODE]
       assert batch.decoder_input_ids[1][0].tolist() == RO_CODE
       assert batch.decoder_input_ids[1][-1] == 2
       assert batch.labels[1][-2:].tolist() == [2, RO_CODE]





    @require_torch
    def 	__snake_case  (							self							:							Any      ):



       '''simple docstring'''







       snake_case       :				str		    =self.tokenizer(
           self.src_text,							text_target=self.tgt_text,							padding=lowerCAmelCase__,							truncation=lowerCAmelCase__,							max_length=len(self.expected_src_tokens      ),							return_tensors='''pt''',							)

       snake_case       :				Tuple		    =shift_tokens_right(batch['''labels'''],							self.tokenizer.pad_token_id      )

       self.assertIsInstance(lowerCAmelCase__,							lowerCAmelCase__      )

       self.assertEqual((2, 14),							batch.input_ids.shape      )
       self.assertEqual((2, 14),							batch.attention_mask.shape      )
       snake_case       :				List[Any]		    =batch.input_ids.tolist()[0]
       self.assertListEqual(self.expected_src_tokens,							lowerCAmelCase__      )
       self.assertEqual(2,							batch.decoder_input_ids[0, -1]      )  # EOS
       # Test that special tokens are reset
       self.assertEqual(self.tokenizer.prefix_tokens,							[]      )
       self.assertEqual(self.tokenizer.suffix_tokens,							[self.tokenizer.eos_token_id, EN_CODE]      )





    def 	__snake_case  (							self							:							List[str]      ):



       '''simple docstring'''







       snake_case       :				int		    =self.tokenizer(self.src_text,							padding=lowerCAmelCase__,							truncation=lowerCAmelCase__,							max_length=3,							return_tensors='''pt'''      )
       snake_case       :				Any		    =self.tokenizer(
           text_target=self.tgt_text,							padding=lowerCAmelCase__,							truncation=lowerCAmelCase__,							max_length=10,							return_tensors='''pt'''      )
       snake_case       :				Tuple		    =targets['''input_ids''']
       snake_case       :				Dict		    =shift_tokens_right(lowerCAmelCase__,							self.tokenizer.pad_token_id      )

       self.assertEqual(batch.input_ids.shape[1],							3      )
       self.assertEqual(batch.decoder_input_ids.shape[1],							10      )






    @require_torch
    def 	__snake_case  (							self							:							Union[str, Any]      ):



       '''simple docstring'''







       snake_case       :				Union[str, Any]		    =self.tokenizer._build_translation_inputs(
           '''A test''',							return_tensors='''pt''',							src_lang='''en_XX''',							tgt_lang='''ar_AR'''      )

       self.assertEqual(
           nested_simplify(lowerCAmelCase__      ),							{
               # A, test, EOS, en_XX
               '''input_ids''': [[62, 3_034, 2, 250_004]],
               '''attention_mask''': [[1, 1, 1, 1]],
               # ar_AR
               '''forced_bos_token_id''': 250_001,
           },							)







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__     )
