


"""simple docstring"""






from torch import nn


class     __lowerCamelCase  (					nn.Module				):

     '''simple docstring'''


     def __init__(      self    ,				__UpperCAmelCase    ,				__UpperCAmelCase							)       ->							str:
          super().__init__()
          _a    	=				class_size
          _a    	=				embed_size
          # self.mlp1 = nn.Linear(embed_size, embed_size)
          # self.mlp2 = (nn.Linear(embed_size, class_size))
          _a    	=				nn.Linear(__UpperCAmelCase    ,				__UpperCAmelCase							)





     def 							_UpperCAmelCase      (      self    ,				__UpperCAmelCase							)       ->							Dict:
          # hidden_state = nn.functional.relu(self.mlp1(hidden_state))
          # hidden_state = self.mlp2(hidden_state)
          _a    	=				self.mlp(__UpperCAmelCase							)
          return logits



"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


__snake_case		=       {'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __snake_case		=       [
       '''VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''ViTMAEForPreTraining''',
       '''ViTMAELayer''',
       '''ViTMAEModel''',
       '''ViTMAEPreTrainedModel''',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __snake_case		=       [
       '''TFViTMAEForPreTraining''',
       '''TFViTMAEModel''',
       '''TFViTMAEPreTrainedModel''',
   ]

if TYPE_CHECKING:
   from .configuration_vit_mae import VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTMAEConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_vit_mae import (
          VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST,
          ViTMAEForPreTraining,
          ViTMAELayer,
          ViTMAEModel,
          ViTMAEPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_vit_mae import TFViTMAEForPreTraining, TFViTMAEModel, TFViTMAEPreTrainedModel


else:
   import sys

   __snake_case		=       _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)