code: 
  
  
  
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
  
  
  _lowercase		:     Optional[int] 					={
      """configuration_esm""": ["""ESM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """EsmConfig"""],
      """tokenization_esm""": ["""EsmTokenizer"""],
  }
  
  try:
  		if not is_torch_available():
  				raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  		pass
  else:
  		_lowercase		:     Dict 					=[
  		    """ESM_PRETRAINED_MODEL_ARCHIVE_LIST""",
  		    """EsmForMaskedLM""",
  		    """EsmForSequenceClassification""",
  		    """EsmForTokenClassification""",
  		    """EsmModel""",
  		    """EsmPreTrainedModel""",
  		]
  		_lowercase		:     List[str] 					=["""EsmForProteinFolding""", """EsmFoldPreTrainedModel"""]
  
  try:
  		if not is_tf_available():
  				raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  		pass
  else:
  		_lowercase		:     Optional[Any] 					=[
  		    """TF_ESM_PRETRAINED_MODEL_ARCHIVE_LIST""",
  		    """TFEsmForMaskedLM""",
  		    """TFEsmForSequenceClassification""",
  		    """TFEsmForTokenClassification""",
  		    """TFEsmModel""",
  		    """TFEsmPreTrainedModel""",
  		]
  
  if TYPE_CHECKING:
  		from .configuration_esm import ESM_PRETRAINED_CONFIG_ARCHIVE_MAP, EsmConfig
  		from .tokenization_esm import EsmTokenizer
  
  		try:
  				if not is_torch_available():
  						raise OptionalDependencyNotAvailable()
  		except OptionalDependencyNotAvailable:
  				pass
  		else:
  				from .modeling_esm import (
  				    ESM_PRETRAINED_MODEL_ARCHIVE_LIST,
  				    EsmForMaskedLM,
  				    EsmForSequenceClassification,
  				    EsmForTokenClassification,
  				    EsmModel,
  				    EsmPreTrainedModel,
  				)
  				from .modeling_esmfold import EsmFoldPreTrainedModel, EsmForProteinFolding
  
  		try:
  				if not is_tf_available():
  						raise OptionalDependencyNotAvailable()
  		except OptionalDependencyNotAvailable:
  				pass
  		else:
  				from .modeling_tf_esm import (
  				    TF_ESM_PRETRAINED_MODEL_ARCHIVE_LIST,
  				    TFEsmForMaskedLM,
  				    TFEsmForSequenceClassification,
  				    TFEsmForTokenClassification,
  				    TFEsmModel,
  				    TFEsmPreTrainedModel,
  				)
  
  
  else:
  		import sys
  
  		_lowercase		:     List[Any] 					=_LazyModule(__name__, globals()["""__file__"""], _import_structure)
  
style_context: 
  
  
  
  
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  _lowercase		:     Dict 					=logging.get_logger(__name__)
  
  _lowercase		:     Any 					={
      """dandelin/vilt-b32-mlm""": """https://huggingface.co/dandelin/vilt-b32-mlm/blob/main/config.json"""
  }
  
  
  
  
  
  
  class 	UpperCamelCase_     (     snake_case__       ):
  					_a			:	List[str]							=				'vilt'
  
  
  
  					def __init__(		self    :    int					,			lowerCamelCase    :    Any=3_05_22					,			lowerCamelCase    :    Union[str, Any]=2					,			lowerCamelCase    :    Optional[Any]=2					,			lowerCamelCase    :    str=40					,			lowerCamelCase    :    List[str]=7_68					,			lowerCamelCase    :    Optional[int]=12					,			lowerCamelCase    :    List[Any]=12					,			lowerCamelCase    :    List[str]=30_72					,			lowerCamelCase    :    Union[str, Any]="gelu"					,			lowerCamelCase    :    int=0.0					,			lowerCamelCase    :    str=0.0					,			lowerCamelCase    :    int=0.02					,			lowerCamelCase    :    Union[str, Any]=1E-12					,			lowerCamelCase    :    Dict=3_84					,			lowerCamelCase    :    List[str]=32					,			lowerCamelCase    :    Dict=3					,			lowerCamelCase    :    List[str]=True					,			lowerCamelCase    :    int=-1					,			lowerCamelCase    :    List[Any]=False					,			lowerCamelCase    :    Any=-1					,			**lowerCamelCase    :    str					,			):
  							super().__init__(tie_word_embeddings=lowerCamelCase					,			**lowerCamelCase	)
  
  							lowerCamelCase_  :    str   	=			vocab_size
  							lowerCamelCase_  :    Dict   	=			type_vocab_size
  							lowerCamelCase_  :    str   	=			modality_type_vocab_size
  							lowerCamelCase_  :    Optional[Any]   	=			max_position_embeddings
  
  							lowerCamelCase_  :    List[Any]   	=			hidden_size
  							lowerCamelCase_  :    Union[str, Any]   	=			num_hidden_layers
  							lowerCamelCase_  :    Any   	=			num_attention_heads
  							lowerCamelCase_  :    List[Any]   	=			intermediate_size
  							lowerCamelCase_  :    Union[str, Any]   	=			hidden_act
  							lowerCamelCase_  :    Any   	=			hidden_dropout_prob
  							lowerCamelCase_  :    Optional[int]   	=			attention_probs_dropout_prob
  							lowerCamelCase_  :    Any   	=			initializer_range
  							lowerCamelCase_  :    str   	=			layer_norm_eps
  
  							lowerCamelCase_  :    Optional[Any]   	=			image_size
  							lowerCamelCase_  :    List[Any]   	=			patch_size
  							lowerCamelCase_  :    Tuple   	=			num_channels
  							lowerCamelCase_  :    Optional[Any]   	=			qkv_bias
  							lowerCamelCase_  :    Optional[int]   	=			max_image_length
  							lowerCamelCase_  :    Optional[Any]   	=			num_images
  