class_docstr: Args:
      n_feature: Number of input features
      n_hidden: Internal hidden unit size.
code: def __init__(
      self,
      n_feature: int,
      n_hidden: int,
      dropout: float,
      relu_max_clip: int = 20,
  ) -> None:
      super(FullyConnected, self).__init__()
      self.fc = torch.nn.Linear(n_feature, n_hidden, bias=True)
      self.relu_max_clip = relu_max_clip
      self.dropout = dropout
  
file_path: audio/src/torchaudio/models/deepspeech.py
imports: import torch
label_desc: Use image node_id 1 to create a new FullyConnected object from inherited base classes: torch.nn with example: obj = FullyConnected(n_feature, n_hidden, dropout, relu_max_clip)