





'''simple docstring'''

import inspect
import os
import unittest
from dataclasses import dataclass

import torch

from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cuda, require_multi_gpu
from accelerate.utils import KwargsHandler
@dataclass
class 							__lowerCAmelCase	(       __magic_name__					):






       """simple docstring"""
       _snake_case      :	int									=       0
       _snake_case      :	bool									=       False
       _snake_case      :	float									=       3.0

class 							__lowerCAmelCase	(       unittest.TestCase					):






       """simple docstring"""





       def snake_case__		(				self  :						str	)       ->	Union[str, Any]:

            '''simple docstring'''




            self.assertDictEqual(MockClass().to_kwargs()			,					{}	)
            self.assertDictEqual(MockClass(a=2	).to_kwargs()			,					{'''a''': 2}	)
            self.assertDictEqual(MockClass(a=2			,					b=lowerCAmelCase__	).to_kwargs()			,					{'''a''': 2, '''b''': True}	)
            self.assertDictEqual(MockClass(a=2			,					c=2.25	).to_kwargs()			,					{'''a''': 2, '''c''': 2.25}	)





       @require_cuda
       def snake_case__		(				self  :						int	)       ->	Optional[int]:

            '''simple docstring'''




            _UpperCamelCase							       =			GradScalerKwargs(init_scale=1024			,					growth_factor=2	)
            AcceleratorState._reset_state()
            _UpperCamelCase							       =			Accelerator(mixed_precision='''fp16'''			,					kwargs_handlers=[scaler_handler]	)
            print(accelerator.use_fpaa	)
            _UpperCamelCase							       =			accelerator.scaler

            # Check the kwargs have been applied
            self.assertEqual(scaler._init_scale			,					1024.0	)
            self.assertEqual(scaler._growth_factor			,					2.0	)

            # Check the other values are at the default
            self.assertEqual(scaler._backoff_factor			,					0.5	)
            self.assertEqual(scaler._growth_interval			,					2000	)
            self.assertEqual(scaler._enabled			,					lowerCAmelCase__	)







       @require_multi_gpu
       def snake_case__		(				self  :						List[Any]	)       ->	Union[str, Any]:

            '''simple docstring'''




            _UpperCamelCase							       =			['''torchrun''', f"""--nproc_per_node={torch.cuda.device_count()}""", inspect.getfile(self.__class__	)]
            execute_subprocess_async(lowerCAmelCase__			,					env=os.environ.copy()	)


if __name__ == "__main__":
   lowercase__		:     Dict			=							DistributedDataParallelKwargs(bucket_cap_mb=15, find_unused_parameters=True)
   lowercase__		:     List[str]			=							Accelerator(kwargs_handlers=[ddp_scaler])
   lowercase__		:     List[Any]			=							torch.nn.Linear(1_00, 2_00)
   lowercase__		:     Dict			=							accelerator.prepare(model)

   # Check the values changed in kwargs
   lowercase__		:     Any			=							''
   lowercase__		:     Union[str, Any]			=							model.bucket_bytes_cap // (10_24 * 10_24)
   if observed_bucket_cap_map != 15:
      error_msg += F"Kwargs badly passed, should have `15` but found {observed_bucket_cap_map}.\n"
   if model.find_unused_parameters is not True:
      error_msg += F"Kwargs badly passed, should have `True` but found {model.find_unused_parameters}.\n"

   # Check the values of the defaults
   if model.dim != 0:
      error_msg += F"Default value not respected, should have `0` but found {model.dim}.\n"
   if model.broadcast_buffers is not True:
      error_msg += F"Default value not respected, should have `True` but found {model.broadcast_buffers}.\n"
   if model.gradient_as_bucket_view is not False:
      error_msg += F"Default value not respected, should have `False` but found {model.gradient_as_bucket_view}.\n"

   # Raise error at the end to make sure we don't stop at the first failure.
   if len(error_msg) > 0:
      raise ValueError(error_msg)






'''simple docstring'''





from dataclasses import asdict, dataclass
from typing import Optional

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


UpperCamelCase_    						=       logging.get_logger(__name__)

# TODO Update this
UpperCamelCase_    						=       {
    """facebook/esm-1b""": """https://huggingface.co/facebook/esm-1b/resolve/main/config.json""",
    # See all ESM models at https://huggingface.co/models?filter=esm
}





class 		__SCREAMING_SNAKE_CASE							(			lowercase__      ):
				lowerCamelCase_		       =    'esm'







				def __init__(       self     :		Optional[Any]		,					UpperCAmelCase__     :		str=None		,					UpperCAmelCase__     :		Dict=None		,					UpperCAmelCase__     :		Any=None		,					UpperCAmelCase__     :		int=768		,					UpperCAmelCase__     :		Union[str, Any]=12		,					UpperCAmelCase__     :		List[Any]=12		,					UpperCAmelCase__     :		Optional[Any]=3072		,					UpperCAmelCase__     :		Dict=0.1		,					UpperCAmelCase__     :		int=0.1		,					UpperCAmelCase__     :		int=1026		,					UpperCAmelCase__     :		Tuple=0.02		,					UpperCAmelCase__     :		Optional[int]=1E-12		,					UpperCAmelCase__     :		List[Any]="absolute"		,					UpperCAmelCase__     :		int=True		,					UpperCAmelCase__     :		Dict=None		,					UpperCAmelCase__     :		str=False		,					UpperCAmelCase__     :		int=False		,					UpperCAmelCase__     :		Optional[Any]=None		,					UpperCAmelCase__     :		List[str]=None		,					**UpperCAmelCase__     :		int		,					):
										'''simple docstring'''
										super().__init__(pad_token_id=UpperCAmelCase__		,					mask_token_id=UpperCAmelCase__		,					**UpperCAmelCase__   )

										lowercase :							Any    		=vocab_size
										lowercase :							List[Any]    		=hidden_size
										lowercase :							Any    		=num_hidden_layers
										lowercase :							Optional[Any]    		=num_attention_heads
										lowercase :							Tuple    		=intermediate_size
										lowercase :							int    		=hidden_dropout_prob
										lowercase :							Dict    		=attention_probs_dropout_prob
										lowercase :							Optional[int]    		=max_position_embeddings
										lowercase :							Union[str, Any]    		=initializer_range
										lowercase :							Tuple    		=layer_norm_eps
										lowercase :							Union[str, Any]    		=position_embedding_type
										lowercase :							List[Any]    		=use_cache
										lowercase :							Dict    		=emb_layer_norm_before
										lowercase :							Optional[Any]    		=token_dropout
										lowercase :							Union[str, Any]    		=is_folding_model
										if is_folding_model:
																if esmfold_config is None:
																						logger.info('''No esmfold_config supplied for folding model, using default values.'''   )
																						lowercase :							Any    		=EsmFoldConfig()
																elif isinstance(UpperCAmelCase__		,					UpperCAmelCase__   ):
																						lowercase :							Optional[int]    		=EsmFoldConfig(**UpperCAmelCase__   )
																lowercase :							Union[str, Any]    		=esmfold_config
																if vocab_list is None:
																						logger.warning('''No vocab_list supplied for folding model, assuming the ESM-2 vocabulary!'''   )
																						lowercase :							int    		=get_default_vocab_list()
																else:
																						lowercase :							Tuple    		=vocab_list
										else:
																lowercase :							Union[str, Any]    		=None
																lowercase :							Dict    		=None
										if self.esmfold_config is not None and getattr(self.esmfold_config		,					'''use_esm_attn_map'''		,					UpperCAmelCase__   ):
																raise ValueError('''The HuggingFace port of ESMFold does not support use_esm_attn_map at this time!'''   )







				def  lowerCamelCase_	(       self     :		Union[str, Any]   ):
										'''simple docstring'''
										lowercase :							Union[str, Any]    		=super().to_dict()
										if isinstance(self.esmfold_config		,					UpperCAmelCase__   ):
																lowercase :							Optional[Any]    		=self.esmfold_config.to_dict()
										return output





@dataclass
class 		__SCREAMING_SNAKE_CASE							:
				lowerCamelCase_		       =    None
				lowerCamelCase_		       =    True
				lowerCamelCase_		       =    False
				lowerCamelCase_		       =    False
				lowerCamelCase_		       =    False
				lowerCamelCase_		       =    0

				lowerCamelCase_		       =    True
				lowerCamelCase_		       =    False

				lowerCamelCase_		       =    1_28
				lowerCamelCase_		       =    None







				def  lowerCamelCase_	(       self     :		Tuple   ):
										'''simple docstring'''
										if self.trunk is None:
																lowercase :							str    		=TrunkConfig()
										elif isinstance(self.trunk		,					UpperCAmelCase__   ):
																lowercase :							int    		=TrunkConfig(**self.trunk   )







				def  lowerCamelCase_	(       self     :		List[Any]   ):
										'''simple docstring'''
										lowercase :							str    		=asdict(self   )
										lowercase :							Union[str, Any]    		=self.trunk.to_dict()
										return output





@dataclass
class 		__SCREAMING_SNAKE_CASE							:
				lowerCamelCase_		       =    48
				lowerCamelCase_		       =    10_24
				lowerCamelCase_		       =    1_28
				lowerCamelCase_		       =    32
				lowerCamelCase_		       =    32
				lowerCamelCase_		       =    32
				lowerCamelCase_		       =    0
				lowerCamelCase_		       =    0
				lowerCamelCase_		       =    False
				lowerCamelCase_		       =    4
				lowerCamelCase_		       =    1_28
				lowerCamelCase_		       =    None







				def  lowerCamelCase_	(       self     :		List[str]   ):
										'''simple docstring'''
										if self.structure_module is None:
																lowercase :							Any    		=StructureModuleConfig()
										elif isinstance(self.structure_module		,					UpperCAmelCase__   ):
																lowercase :							Union[str, Any]    		=StructureModuleConfig(**self.structure_module   )

										if self.max_recycles <= 0:
																raise ValueError(F'''`max_recycles` should be positive, got {self.max_recycles}.'''   )
										if self.sequence_state_dim % self.sequence_state_dim != 0:
																raise ValueError(
																    '''`sequence_state_dim` should be a round multiple of `sequence_state_dim`, got'''
																    F''' {self.sequence_state_dim} and {self.sequence_state_dim}.'''   )
										if self.pairwise_state_dim % self.pairwise_state_dim != 0:
																raise ValueError(
																    '''`pairwise_state_dim` should be a round multiple of `pairwise_state_dim`, got'''
																    F''' {self.pairwise_state_dim} and {self.pairwise_state_dim}.'''   )

										lowercase :							str    		=self.sequence_state_dim // self.sequence_head_width
										lowercase :							int    		=self.pairwise_state_dim // self.pairwise_head_width

										if self.sequence_state_dim != sequence_num_heads * self.sequence_head_width:
																raise ValueError(
																    '''`sequence_state_dim` should be equal to `sequence_num_heads * sequence_head_width, got'''
																    F''' {self.sequence_state_dim} != {sequence_num_heads} * {self.sequence_head_width}.'''   )
										if self.pairwise_state_dim != pairwise_num_heads * self.pairwise_head_width:
																raise ValueError(
																    '''`pairwise_state_dim` should be equal to `pairwise_num_heads * pairwise_head_width, got'''
																    F''' {self.pairwise_state_dim} != {pairwise_num_heads} * {self.pairwise_head_width}.'''   )
										if self.pairwise_state_dim % 2 != 0:
																raise ValueError(F'''`pairwise_state_dim` should be even, got {self.pairwise_state_dim}.'''   )

										if self.dropout >= 0.4:
																raise ValueError(F'''`dropout` should not be greater than 0.4, got {self.dropout}.'''   )







				def  lowerCamelCase_	(       self     :		Any   ):
										'''simple docstring'''
										lowercase :							List[Any]    		=asdict(self   )
										lowercase :							Any    		=self.structure_module.to_dict()
										return output





@dataclass
class 		__SCREAMING_SNAKE_CASE							:
				lowerCamelCase_		       =    3_84
				lowerCamelCase_		       =    1_28
				lowerCamelCase_		       =    16
				lowerCamelCase_		       =    1_28
				lowerCamelCase_		       =    12
				lowerCamelCase_		       =    4
				lowerCamelCase_		       =    8
				lowerCamelCase_		       =    0.1
				lowerCamelCase_		       =    8
				lowerCamelCase_		       =    1
				lowerCamelCase_		       =    2
				lowerCamelCase_		       =    7
				lowerCamelCase_		       =    10
				lowerCamelCase_		       =    1E-8
				lowerCamelCase_		       =    1E5







				def  lowerCamelCase_	(       self     :		Dict   ):
										'''simple docstring'''
										return asdict(self   )






def 				_lowerCAmelCase			(   )				->  Optional[int]:
						return (
						    "<cls>",
						    "<pad>",
						    "<eos>",
						    "<unk>",
						    "L",
						    "A",
						    "G",
						    "V",
						    "S",
						    "E",
						    "R",
						    "T",
						    "I",
						    "D",
						    "P",
						    "K",
						    "Q",
						    "N",
						    "F",
						    "Y",
						    "M",
						    "H",
						    "W",
						    "C",
						    "X",
						    "B",
						    "U",
						    "Z",
						    "O",
						    ".",
						    "-",
						    "<null_1>",
						    "<mask>",
						)





