code: def test_warn_for_bad_log_probs(self):
      # The only valid next step from the initial predictions is the end index.
      # But with a beam size of 3, the call to `topk` to find the 3 most likely
      # next beams will result in 2 new beams that are invalid, in that have probability of 0.
      # The beam search should warn us of this.
      initial_predictions = torch.LongTensor(
          [self.end_index - 1, self.end_index - 1]
      )
      with pytest.warns(
          RuntimeWarning, match="Negligible log probabilities"
      ):
          self.beam_search.search(
              initial_predictions, {}, take_step_no_timestep
          )
  
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 14 for calling the BeamSearchTest obj's underlying member method code with example usage: obj.test_warn_for_bad_log_probs() without return types