code: def setup_method(self):
      super().setup_method()
      self.end_index = transition_probabilities.size()[0] - 1
      self.beam_search = BeamSearch(
          self.end_index, max_steps=10, beam_size=3
      )
  
      # This is what the top k should look like for each item in the batch.
      self.expected_top_k = np.array(
          [[1, 2, 3, 4, 5], [2, 3, 4, 5, 5], [3, 4, 5, 5, 5]]
      )
  
      # This is what the log probs should look like for each item in the batch.
      self.expected_log_probs = np.log(np.array([0.4, 0.3, 0.2]))
  
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 1 for calling the BeamSearchTest obj's underlying member method code with example usage: obj.setup_method() without return types