code: def run_hmc(args, model):
      nuts_kernel = NUTS(model)
      mcmc = MCMC(
          nuts_kernel,
          warmup_steps=args.num_warmup,
          num_samples=args.num_samples,
      )
      mcmc.run(args.param_a, args.param_b)
      mcmc.summary()
      return mcmc
  
imports: import argparse
  import logging
  import os
  from functools import partial
  import matplotlib.pyplot
  import seaborn
  import torch
  from matplotlib.gridspec import GridSpec
  from torch.distributions.utils import broadcast_all
  import pyro
  import pyro.distributions
  from pyro import optim, poutine
  from pyro.distributions import constraints
  from pyro.distributions.transforms import block_autoregressive, iterated
  from pyro.infer import MCMC, NUTS, SVI, Trace_ELBO
  from pyro.infer.autoguide import AutoDiagonalNormal, AutoNormalizingFlow
  from pyro.infer.reparam import NeuTraReparam
label_desc: Use image node_id 3 for calling a global function with example usage: run_hmc(args, model) and returns: mcmc