


'''simple docstring'''


from torch import nn





class     lowercase__  (						nn.Module					):





							'''simple docstring'''


							def __init__(    self    ,					__snake_case    ,					__snake_case  ):
											super().__init__()
											_SCREAMING_SNAKE_CASE :       Any     		=      class_size
											_SCREAMING_SNAKE_CASE :       Optional[Any]     		=      embed_size
											# self.mlp1 = nn.Linear(embed_size, embed_size)
											# self.mlp2 = (nn.Linear(embed_size, class_size))
											_SCREAMING_SNAKE_CASE :       Dict     		=      nn.Linear(__snake_case    ,					__snake_case  )






							def UpperCAmelCase_	(    self    ,					__snake_case  ):
											# hidden_state = nn.functional.relu(self.mlp1(hidden_state))
											# hidden_state = self.mlp2(hidden_state)
											_SCREAMING_SNAKE_CASE :       str     		=      self.mlp(__snake_case  )
											return logits








'''simple docstring'''


UpperCAmelCase_		:   Union[str, Any]							   =		'\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'

UpperCAmelCase_		:   Dict							   =		[{'type': 'code', 'content': INSTALL_CONTENT}]
UpperCAmelCase_		:   Any							   =		{
    '{processor_class}': 'FakeProcessorClass',
    '{model_class}': 'FakeModelClass',
    '{object_class}': 'FakeObjectClass',
}




