code: def count_parameters(args):
      model = gen_model(args)
      return sum(
          [p.numel() for p in model.parameters() if p.requires_grad]
      )
  
imports: import argparse
  import math
  import os
  import random
  import time
  import dgl
  import numpy
  import torch
  import torch.nn.functional
  import torch.optim
  from matplotlib import pyplot
  from matplotlib.ticker import AutoMinorLocator, MultipleLocator
  from models import GAT
  from ogb.nodeproppred import DglNodePropPredDataset, Evaluator
label_desc: Use image node_id 11 for calling a global function with example usage: count_parameters(args) and returns: sum