code: def _make_ops(self, num_samples, seed=None, dtype=dtypes.float32):
      prob_dist = constant_op.constant(
          [[0.15, 0.5, 0.3, 0.05]], dtype=dtype
      )
      logits = math_ops.log(prob_dist)
      # Two independent sets of samples from the same distribution
      sample_op1 = random_ops.multinomial(logits, num_samples, seed)
      sample_op2 = random_ops.multinomial(logits, num_samples, seed)
      return (sample_op1, sample_op2)
  
imports: import collections
  import timeit
  import numpy
  from tensorflow.core.protobuf import config_pb2
  from tensorflow.python.client import session
  from tensorflow.python.eager import context
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import random_seed
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 10 for calling the MultinomialTest obj's underlying member method code with example usage: obj._make_ops(num_samples, seed, dtype) and returns: sample_op1,  sample_op2