code: def test_int_samples(self):
      rhat_reducer = psrr.PotentialScaleReductionReducer(
          independent_chain_ndims=1
      )
      state = rhat_reducer.initialize(tf.zeros((5, 3), dtype=tf.int64))
      chain_state = np.arange(60).reshape((4, 5, 3))
      for sample in chain_state:
          state = rhat_reducer.one_step(sample, state)
      rhat = rhat_reducer.finalize(state)
      true_rhat = diagnostic.potential_scale_reduction(
          chains_states=chain_state, independent_chain_ndims=1
      )
      self.assertEqual(tf.float64, rhat.dtype)
      rhat, true_rhat = self.evaluate([rhat, true_rhat])
      self.assertAllClose(true_rhat, rhat, rtol=1e-6)
  
file_path: probability/tensorflow_probability/python/experimental/mcmc/potential_scale_reduction_reducer_test.py
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.experimental.mcmc import potential_scale_reduction_reducer
  from tensorflow_probability.python.experimental.mcmc import tracing_reducer
  from tensorflow_probability.python.experimental.mcmc.internal import test_fixtures
  from tensorflow_probability.python.experimental.mcmc.sample_fold import sample_fold
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.mcmc import diagnostic
  from tensorflow_probability.python.mcmc import hmc
label_desc: Use image node_id 1 for calling the PotentialScaleReductionReducerTest obj's underlying member method code with example usage: obj.test_int_samples() without return types