




'''simple docstring'''







from dataclasses import asdict, dataclass
from typing import Optional

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


A     :   Dict									=logging.get_logger(__name__)

# TODO Update this
A     :   List[str]									={
    '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     _a						(			__a				):
       __a       :  List[Any]            =      """esm"""
       def __init__(			self		:			str     ,       lowercase		:			Optional[Any]=None     ,       lowercase		:			Any=None     ,       lowercase		:			Union[str, Any]=None     ,       lowercase		:			Dict=768     ,       lowercase		:			Dict=12     ,       lowercase		:			str=12     ,       lowercase		:			Optional[int]=3_072     ,       lowercase		:			Dict=0.1     ,       lowercase		:			str=0.1     ,       lowercase		:			Tuple=1_026     ,       lowercase		:			int=0.02     ,       lowercase		:			int=1E-12     ,       lowercase		:			Any="absolute"     ,       lowercase		:			List[Any]=True     ,       lowercase		:			Any=None     ,       lowercase		:			Optional[Any]=False     ,       lowercase		:			Optional[Any]=False     ,       lowercase		:			str=None     ,       lowercase		:			List[Any]=None     ,       **lowercase		:			List[Any]     ,       ):



           '''simple docstring'''

           super().__init__(pad_token_id=lowercase     ,       mask_token_id=lowercase     ,       **lowercase       )

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







       def 					A   (			self		:			List[str]       ):



           '''simple docstring'''

           UpperCAmelCase     =	super().to_dict()
           if isinstance(self.esmfold_config     ,       lowercase       ):
               UpperCAmelCase     =	self.esmfold_config.to_dict()
           return output






@dataclass
class     _a						:
       __a       :  str            =      None
       __a       :  bool            =      True
       __a       :  bool            =      False
       __a       :  bool            =      False
       __a       :  bool            =      False
       __a       :  float            =      0

       __a       :  bool            =      True
       __a       :  bool            =      False

       __a       :  int            =      128
       __a       :  "TrunkConfig"            =      None
       def 					A   (			self		:			List[str]       ):



           '''simple docstring'''

           if self.trunk is None:
               UpperCAmelCase     =	TrunkConfig()
           elif isinstance(self.trunk     ,       lowercase       ):
               UpperCAmelCase     =	TrunkConfig(**self.trunk       )







       def 					A   (			self		:			Tuple       ):



           '''simple docstring'''

           UpperCAmelCase     =	asdict(self       )
           UpperCAmelCase     =	self.trunk.to_dict()
           return output






@dataclass
class     _a						:
       __a       :  int            =      48
       __a       :  int            =      1_024
       __a       :  int            =      128
       __a       :  int            =      32
       __a       :  int            =      32
       __a       :  int            =      32
       __a       :  float            =      0
       __a       :  float            =      0
       __a       :  bool            =      False
       __a       :  int            =      4
       __a       :  Optional[int]            =      128
       __a       :  "StructureModuleConfig"            =      None
       def 					A   (			self		:			List[Any]       ):



           '''simple docstring'''

           if self.structure_module is None:
               UpperCAmelCase     =	StructureModuleConfig()
           elif isinstance(self.structure_module     ,       lowercase       ):
               UpperCAmelCase     =	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}."       )

           UpperCAmelCase     =	self.sequence_state_dim // self.sequence_head_width
           UpperCAmelCase     =	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 					A   (			self		:			Union[str, Any]       ):



           '''simple docstring'''

           UpperCAmelCase     =	asdict(self       )
           UpperCAmelCase     =	self.structure_module.to_dict()
           return output






@dataclass
class     _a						:
       __a       :  int            =      384
       __a       :  int            =      128
       __a       :  int            =      16
       __a       :  int            =      128
       __a       :  int            =      12
       __a       :  int            =      4
       __a       :  int            =      8
       __a       :  float            =      0.1
       __a       :  int            =      8
       __a       :  int            =      1
       __a       :  int            =      2
       __a       :  int            =      7
       __a       :  int            =      10
       __a       :  float            =      1e-8
       __a       :  float            =      1e5
       def 					A   (			self		:			str       ):



           '''simple docstring'''

           return asdict(self       )






def 		snake_case_							():
    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>",
    )










'''simple docstring'''







from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
    MaskedBertForMultipleChoice,
    MaskedBertForQuestionAnswering,
    MaskedBertForSequenceClassification,
    MaskedBertForTokenClassification,
    MaskedBertModel,
)
from .modules import *




