code: def simulate(self, times):
      x0 = torch.cat([self.initial_pos, self.initial_aug]).reshape(-1)
      solution = odeint(
          self, x0, times, atol=1e-8, rtol=1e-8, method="dopri5"
      )
      trajectory = solution[:, 0]
      return trajectory, []
  
imports: import argparse
  import os
  import math
  import matplotlib.pyplot
  import torch
  import torch.nn
  from torchdiffeq import odeint, odeint_event
  from bouncing_ball import BouncingBallExample
label_desc: Use image node_id 3 for calling the NeuralODE obj's underlying member method code with example usage: obj.simulate(times) and returns: trajectory,  list