code: def _make_poisson(
      self,
      rate,
      validate_args=True,
      force_probs_to_zero_outside_support=False,
  ):
      return poisson_lib.Poisson(
          log_rate=tf.math.log(rate),
          validate_args=validate_args,
          force_probs_to_zero_outside_support=force_probs_to_zero_outside_support,
      )
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import poisson
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import implementation_selection
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 1 for calling the PoissonLogRateTest obj's underlying member method code with example usage: obj._make_poisson(rate, validate_args, force_probs_to_zero_outside_support) and returns: poisson_lib