code: 
  
  
  import torch
  
  from transformers import PreTrainedModel
  
  from .custom_configuration import CustomConfig, NoSuperInitConfig
  
  
  
  class 			a      (      UpperCamelCase_   ):
  		__lowercase													=		CustomConfig
  
  
  
  
  
  
  		def __init__(  self	,     __UpperCamelCase							)->			List[Any]:
  						'''simple docstring'''
  
  
  						super().__init__(__UpperCamelCase							)
  						A__     :							List[Any]   				=torch.nn.Linear(config.hidden_size	,     config.hidden_size							)
  
  
  
  
  
  
  		def       lowerCAmelCase_  (  self	,     __UpperCamelCase							)->			Dict:
  						'''simple docstring'''
  
  
  						return self.linear(__UpperCamelCase							)
  
  
  
  
  
  
  		def       lowerCAmelCase_  (  self	,     __UpperCamelCase							)->			Union[str, Any]:
  						'''simple docstring'''
  
  
  						pass
  
  
  
  
  
  
  
  class 			a      (      UpperCamelCase_   ):
  		__lowercase													=		NoSuperInitConfig
  
  
  
  
  
  
  		def __init__(  self	,     __UpperCamelCase							)->			Dict:
  						'''simple docstring'''
  
  
  						super().__init__(__UpperCamelCase							)
  						A__     :							Union[str, Any]   				=torch.nn.Linear(config.attribute	,     config.attribute							)
  
  
  
  
  
  
  		def       lowerCAmelCase_  (  self	,     __UpperCamelCase							)->			Union[str, Any]:
  						'''simple docstring'''
  
  
  						return self.linear(__UpperCamelCase							)
  
  
  
  
  
  
  		def       lowerCAmelCase_  (  self	,     __UpperCamelCase							)->			Dict:
  						'''simple docstring'''
  
  
  						pass
  
  
  
  
style_context: 
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_torch_available,
  )
  
  
  __lowerCamelCase       :       str				   =			{
      "configuration_align": [
          "ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP",
          "AlignConfig",
          "AlignTextConfig",
          "AlignVisionConfig",
      ],
      "processing_align": ["AlignProcessor"],
  }
  
  try:
  						if not is_torch_available():
  												raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  						pass
  else:
  						__lowerCamelCase       :       Dict				   =			[
  						    "ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST",
  						    "AlignModel",
  						    "AlignPreTrainedModel",
  						    "AlignTextModel",
  						    "AlignVisionModel",
  						]
  
  if TYPE_CHECKING:
  						from .configuration_align import (
  						    ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP,
  						    AlignConfig,
  						    AlignTextConfig,
  						    AlignVisionConfig,
  						)
  						from .processing_align import AlignProcessor
  
  						try:
  												if not is_torch_available():
  																		raise OptionalDependencyNotAvailable()
  						except OptionalDependencyNotAvailable:
  												pass
  						else:
  												from .modeling_align import (
  												    ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST,
  												    AlignModel,
  												    AlignPreTrainedModel,
  												    AlignTextModel,
  												    AlignVisionModel,
  												)
  
  else:
  						import sys
  
  						__lowerCamelCase       :       List[str]				   =			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
  
  
  
  