code: def main(args):
      y = torch.randn(args.n, args.num_variables).to(dtype=torch.double)
      if args.cuda:
          y = y.cuda()
      nuts_kernel = NUTS(model, jit_compile=False, step_size=1e-5)
      MCMC(
          nuts_kernel,
          num_samples=args.num_samples,
          warmup_steps=args.warmup_steps,
          num_chains=args.num_chains,
      ).run(y)
  
file_path: pyro/examples/lkj.py
imports: import argparse
  import torch
  import pyro
  import pyro.distributions
  from pyro.infer.mcmc import NUTS
  from pyro.infer.mcmc.api import MCMC
label_desc: Use image node_id 2 for calling a global function with example usage: main(args) without return types