code: def __init__(
      self,
      etypes,
      in_size,
      hidden_size,
      out_size,
      num_layers,
      dropout=0.1,
  ):
      super(GNNFiLM, self).__init__()
      self.film_layers = nn.ModuleList()
      self.film_layers.append(
          GNNFiLMLayer(in_size, hidden_size, etypes, dropout)
      )
      for i in range(num_layers - 1):
          self.film_layers.append(
              GNNFiLMLayer(hidden_size, hidden_size, etypes, dropout)
          )
      self.predict = nn.Linear(hidden_size, out_size, bias=True)
  
file_path: dgl/examples/pytorch/GNN-FiLM/main.py
imports: import argparse
  import os
  import dgl
  import dgl.function
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from data_loader import load_PPI
  from utils import evaluate_f1_score
label_desc: Use image node_id 1 to create a new GNNFiLM object from inherited base classes: nn with example: obj = GNNFiLM(etypes, in_size, hidden_size, out_size, num_layers, dropout)