code: def __init__(
      self,
      device,
      num_nodes,
      h_dim,
      out_dim,
      num_rels,
      num_bases=None,
      num_hidden_layers=1,
      dropout=0,
      use_self_loop=False,
      layer_norm=False,
  ):
      super(EntityClassify, self).__init__()
      self.device = th.device(device if device >= 0 else "cpu")
      self.num_nodes = num_nodes
      self.h_dim = h_dim
      self.out_dim = out_dim
      self.num_rels = num_rels
      self.num_bases = None if num_bases < 0 else num_bases
      self.num_hidden_layers = num_hidden_layers
      self.dropout = dropout
      self.use_self_loop = use_self_loop
      self.layer_norm = layer_norm
  
      self.layers = nn.ModuleList()
      # i2h
      self.layers.append(
          RelGraphConv(
              self.h_dim,
              self.h_dim,
              self.num_rels,
              "basis",
              self.num_bases,
              activation=F.relu,
              self_loop=self.use_self_loop,
              dropout=self.dropout,
              layer_norm=layer_norm,
          )
      )
      # h2h
      for idx in range(self.num_hidden_layers):
          self.layers.append(
              RelGraphConv(
                  self.h_dim,
                  self.h_dim,
                  self.num_rels,
                  "basis",
                  self.num_bases,
                  activation=F.relu,
                  self_loop=self.use_self_loop,
                  dropout=self.dropout,
                  layer_norm=layer_norm,
              )
          )
      # h2o
      self.layers.append(
          RelGraphConv(
              self.h_dim,
              self.out_dim,
              self.num_rels,
              "basis",
              self.num_bases,
              activation=None,
              self_loop=self.use_self_loop,
              layer_norm=layer_norm,
          )
      )
  
imports: import argparse
  import gc
  import logging
  import time
  from pathlib import Path
  from types import SimpleNamespace
  import dgl
  import numpy
  import torch
  import torch.multiprocessing
  import torch.nn
  import torch.nn.functional
  from dgl.nn import RelGraphConv
  from torch.multiprocessing import Queue
  from torch.nn.parallel import DistributedDataParallel
  from torch.utils.data import DataLoader
  from ..None import utils
label_desc: Use image node_id 1 to create a new EntityClassify object from inherited base classes: nn with example: obj = EntityClassify(device, num_nodes, h_dim, out_dim, num_rels, num_bases, num_hidden_layers, dropout, use__loop, layer_norm)