code: def initialize_glu(module, input_dim, output_dim):
      gain_value = np.sqrt(
          (input_dim + output_dim) / np.sqrt(input_dim)
      )
      torch.nn.init.xavier_normal_(module.weight, gain=gain_value)
      return
  
file_path: pytorch_tabular/src/pytorch_tabular/models/danet/arch_blocks.py
imports: from functools import partial
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from pytorch_tabular.models.common.layers.activations import entmax15
  from pytorch_tabular.models.common.layers.batch_norm import GBN
label_desc: Use image node_id 1 for calling a global function with example usage: initialize_glu(module, input_dim, output_dim) without return types