
import json
import os
from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


_snake_case      :							Any     	=    logging.get_logger(__name__)


_snake_case      :							Tuple     	=    {
    "vocab_file": "vocab.json",
    "tokenizer_config_file": "tokenizer_config.json",
    "merges_file": "merges.txt",
}

_snake_case      :							Union[str, Any]     	=    {
    "vocab_file": {
        "facebook/s2t-wav2vec2-large-en-de": (
            "https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/vocab.json"
        ),
    },
    "tokenizer_config_file": {
        "facebook/s2t-wav2vec2-large-en-de": (
            "https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/tokenizer_config.json"
        ),
    },
    "merges_file": {
        "facebook/s2t-wav2vec2-large-en-de": (
            "https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/merges.txt"
        ),
    },
}

_snake_case      :							Dict     	=    "</w>"
_snake_case      :							str     	=    "@@ "

def  __snake_case							(	__magic_name__						):







				'''simple docstring'''


				lowercase         =      set()
				lowercase         =      word[0]
				for char in word[1:]:
								pairs.add((prev_char, char)						)
								lowercase         =      char
				return pairs


# Speech2Text2 has no max input length
_snake_case      :							Any     	=    {"facebook/s2t-wav2vec2-large-en-de": 10_24}





class   UpperCamelCase_      (      __a		):







						'''simple docstring'''



						UpperCamelCase      :  Tuple				   =					VOCAB_FILES_NAMES
						UpperCamelCase      :  Any				   =					PRETRAINED_VOCAB_FILES_MAP
						UpperCamelCase      :  Optional[Any]				   =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						UpperCamelCase      :  Any				   =					['''input_ids''', '''attention_mask''']





						def __init__(			self							:Tuple		,    lowerCAmelCase__							:Tuple		,    lowerCAmelCase__							:List[str]="<s>"		,    lowerCAmelCase__							:Any="<pad>"		,    lowerCAmelCase__							:List[Any]="</s>"		,    lowerCAmelCase__							:str="<unk>"		,    lowerCAmelCase__							:Tuple=False		,    lowerCAmelCase__							:Optional[int]=None		,    **lowerCAmelCase__							:Optional[int]		,    )  ->Optional[Any]:
										super().__init__(
										    unk_token=lowerCAmelCase__		,    bos_token=lowerCAmelCase__		,    eos_token=lowerCAmelCase__		,    pad_token=lowerCAmelCase__		,    do_lower_case=lowerCAmelCase__		,    **lowerCAmelCase__		,    )

										lowercase         =      do_lower_case

										with open(lowerCAmelCase__		,    encoding="utf-8"     ) as vocab_handle:
														lowercase         =      json.load(lowerCAmelCase__     )
										lowercase         =      {v: k for k, v in self.encoder.items()}

										if merges_file is None:
														logger.info(F'''No merges files provided. {self.__class__.__name__} can only be used for decoding.'''     )

														lowercase         =      None
														lowercase         =      None
										else:
														with open(lowerCAmelCase__		,    encoding="utf-8"     ) as merges_handle:
																		lowercase         =      merges_handle.read().split("\n"     )[:-1]

														lowercase         =      [tuple(merge.split()[:2]     ) for merge in merges]
														lowercase         =      dict(zip(lowerCAmelCase__		,    range(len(lowerCAmelCase__     )     )     )     )
														lowercase         =      {}





						@property
						def        SCREAMING_SNAKE_CASE(			self							:Dict     )  ->int:
										return len(self.decoder     )





						def        SCREAMING_SNAKE_CASE(			self							:Any     )  ->Dict:
										return dict(self.encoder		,    **self.added_tokens_encoder     )





						def        SCREAMING_SNAKE_CASE(			self							:Tuple		,    lowerCAmelCase__							:List[Any]     )  ->Union[str, Any]:
										lowercase         =      tuple(token[:-1]     ) + (token[-1] + BPE_TOKEN_MERGES,)
										if token in self.cache:
														return self.cache[token]
										lowercase         =      get_pairs(lowerCAmelCase__     )

										if not pairs:
														return token

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

																		if word[i] == first and i < len(lowerCAmelCase__     ) - 1 and word[i + 1] == second:
																						new_word.append(first + second     )
																						i += 2
																		else:
																						new_word.append(word[i]     )
																						i += 1
														lowercase         =      tuple(lowerCAmelCase__     )
														lowercase         =      new_word
														if len(lowerCAmelCase__     ) == 1:
																		break
														else:
																		lowercase         =      get_pairs(lowerCAmelCase__     )
										lowercase         =      " ".join(lowerCAmelCase__     )
										if word == "\n  " + BPE_TOKEN_MERGES:
														lowercase         =      "\n" + BPE_TOKEN_MERGES

										if word.endswith(lowerCAmelCase__     ):
														lowercase         =      word.replace(lowerCAmelCase__		,    ""     )

										lowercase         =      word.replace(" "		,    lowerCAmelCase__     )
										lowercase         =      word
										return word





						def        SCREAMING_SNAKE_CASE(			self							:Optional[int]		,    lowerCAmelCase__							:Optional[int]     )  ->List[str]:

										if self.bpe_ranks is None:
														raise ValueError(
														    "This tokenizer was instantiated without a `merges.txt` file, so"
														    " that it can only be used for decoding, not for encoding."
														    "Make sure to provide `merges.txt` file at instantiation to enable "
														    "encoding."     )

										if self.do_lower_case:
														lowercase         =      text.lower()

										lowercase         =      text.split()

										lowercase         =      []
										for token in text:
														if token:
																		split_tokens.extend(list(self.bpe(lowerCAmelCase__     ).split(" "     )     )     )

										return split_tokens





						def        SCREAMING_SNAKE_CASE(			self							:Union[str, Any]		,    lowerCAmelCase__							:str     )  ->int:
										return self.encoder.get(lowerCAmelCase__		,    self.encoder.get(self.unk_token     )     )





						def        SCREAMING_SNAKE_CASE(			self							:Union[str, Any]		,    lowerCAmelCase__							:int     )  ->str:
										lowercase         =      self.decoder.get(lowerCAmelCase__		,    self.unk_token     )
										return result





						def        SCREAMING_SNAKE_CASE(			self							:Optional[int]		,    lowerCAmelCase__							:List[str]     )  ->str:
										lowercase         =      " ".join(lowerCAmelCase__     )

										# make sure @@ tokens are concatenated
										lowercase         =      "".join(string.split(lowerCAmelCase__     )     )

										return string





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

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

										lowercase         =      0
										if self.bpe_ranks is None:
														return (vocab_file,)

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

										return (vocab_file, merges_file)


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__     )
