class_docstr: This is a large test due to the moments computation taking some time.
code: def _Sampler(self, num, lam, dtype, use_gpu, seed=None):
      def func():
          with self.session(use_gpu=use_gpu, graph=ops.Graph()) as sess:
              rng = random_ops.random_poisson(
                  lam, [num], dtype=dtype, seed=seed
              )
              ret = np.empty([10, num])
              for i in range(10):
                  ret[i, :] = self.evaluate(rng)
          return ret
  
      return func
  
imports: import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.kernel_tests.random import util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.platform import test
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 1 for calling the RandomPoissonTest obj's underlying member method code with example usage: obj._Sampler(num, lam, dtype, use_gpu, seed) and returns: func, ret