code: def compute_hamiltonian(
      target_log_prob, momentum_parts, momentum_distribution
  ):
      """Compute the Hamiltonian of the current system."""
      kinetic_energy = get_kinetic_energy_fn(momentum_distribution)
      return target_log_prob - kinetic_energy(momentum_parts)
  
imports: import collections
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.experimental.mcmc import preconditioning_utils
  from tensorflow_probability.python.internal import broadcast_util
  from tensorflow_probability.python.internal import distribute_lib
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.math.generic import log_add_exp
  from tensorflow_probability.python.mcmc.internal import leapfrog_integrator
  from tensorflow_probability.python.mcmc.internal import util
  from tensorflow_probability.python.mcmc.kernel import TransitionKernel
label_desc: Use image node_id 5 for calling a global function with example usage: compute_hamiltonian(target_log_prob, momentum_parts, momentum_distribution) and returns: unknown