code: def __init__(
      self,
      input_dim,
      output_dim,
      fc=None,
      virtual_batch_size=128,
      momentum=0.02,
  ):
      super(GLU_Layer, self).__init__()
  
      self.output_dim = output_dim
      if fc:
          self.fc = fc
      else:
          self.fc = Linear(input_dim, 2 * output_dim, bias=False)
      initialize_glu(self.fc, input_dim, 2 * output_dim)
  
      self.bn = GBN(
          2 * output_dim,
          virtual_batch_size=virtual_batch_size,
          momentum=momentum,
      )
  
imports: import torch
  from torch.nn import Linear, BatchNorm1d, ReLU
  import numpy
  from pytorch_tabnet import sparsemax
label_desc: Use image node_id 1 to create a new GLU_Layer object from inherited base classes: torch.nn with example: obj = GLU_Layer(input_dim, output_dim, fc, virtual_batch_size, momentum)