code: def setup_method(self):
      super().setup_method()
  
      self.label_weights = torch.FloatTensor([1.0, 1.0, 1.0, 1.0, 1.0])
  
      self.crf = ConditionalRandomFieldWeightLannoy(
          5, label_weights=self.label_weights
      )
      self.crf.transitions = torch.nn.Parameter(self.transitions)
      self.crf.start_transitions = torch.nn.Parameter(
          self.transitions_from_start
      )
      self.crf.end_transitions = torch.nn.Parameter(
          self.transitions_to_end
      )
  
      # Use the CRF Module with labels weights.
      self.crf.label_weights = torch.nn.Parameter(
          self.label_weights, requires_grad=False
      )
  
imports: import itertools
  import math
  from pytest import approx, raises
  import torch
  from numpy.testing import assert_allclose
  from allennlp.modules import ConditionalRandomField
  from allennlp.modules.conditional_random_field import ConditionalRandomFieldWeightEmission, ConditionalRandomFieldWeightTrans, ConditionalRandomFieldWeightLannoy
  from allennlp.modules.conditional_random_field.conditional_random_field import allowed_transitions
  from allennlp.common.checks import ConfigurationError
  from allennlp.common.testing import AllenNlpTestCase
label_desc: Use image node_id 1 for calling the TestConditionalRandomFieldWeightLannoy obj's underlying member method code with example usage: obj.setup_method() without return types