code: def __init__(
      self, hidden_channels, out_emb_channels, num_output_layers, act
  ):
      super(update_v, self).__init__()
      self.act = act
  
      self.lin_up = nn.Linear(
          hidden_channels, out_emb_channels, bias=True
      )
      self.lins = torch.nn.ModuleList()
      for _ in range(num_output_layers - 1):
          self.lins.append(
              nn.Linear(out_emb_channels, out_emb_channels)
          )
      self.lin = nn.Linear(out_emb_channels, hidden_channels)
  
      self.reset_parameters()
  
imports: import torch
  from torch import nn
  from torch.nn import Linear, Embedding
  from torch_geometric.nn.inits import glorot_orthogonal
  from torch_geometric.nn import radius_graph
  from torch_scatter import scatter
  import torch.nn.functional
  from math import sqrt
  from .geometric_computing import xyztodat
  from .features import dist_emb, angle_emb, torsion_emb
label_desc: Use image node_id 1 to create a new update_v object from inherited base classes: torch.nn with example: obj = update_v(hidden_channels, out_emb_channels, num_output_layers, act)