class_docstr: Wrapper around the base model for custom training logic.
code: def test_step(self, data):
      x, y, sample_weight = unpack_data(data)
      crf_loss, internal_losses = self.compute_loss(x, y, sample_weight)
      return {
          "crf_loss_val": crf_loss,
          "internal_losses_val": internal_losses,
      }
  
imports: import itertools
  import os
  import math
  import tempfile
  import pytest
  import numpy
  import tensorflow
  from tensorflow_addons.layers.crf import CRF
  from tensorflow_addons.text.crf import crf_log_likelihood
  from tensorflow_addons.utils import test_utils
label_desc: Use image node_id 5 for calling the ModelWithCRFLoss obj's underlying member method code with example usage: obj.test_step(data) and returns: dict