code: def test_multinomial_sampler(self):
      sampler = MultinomialSampler(temperature=0.9)
  
      probabilities, classes, state = sampler.sample_nodes(
          log_probabilities, 3, {"foo": "bar"}
      )
  
      assert probabilities.size() == classes.size()
      assert classes.size() == (2, 3)
      assert all([x < 4 for x in classes[0]])
      assert all([x > 1 for x in classes[1]])
  
imports: from typing import Dict, Tuple, Union
  import numpy
  import pytest
  import torch
  from allennlp.common.checks import ConfigurationError
  from allennlp.common.testing import AllenNlpTestCase
  from allennlp.nn.beam_search import MultinomialSampler, BeamSearch, TopKSampler, TopPSampler, GumbelSampler, LengthNormalizedSequenceLogProbabilityScorer, RepeatedNGramBlockingConstraint, StepFunctionTypeWithTimestep, StepFunctionTypeNoTimestep
  from allennlp.common.params import Params
  from allennlp.nn.util import min_value_of_dtype
label_desc: Use image node_id 24 for calling the BeamSearchTest obj's underlying member method code with example usage: obj.test_multinomial_sampler() without return types