class_docstr: Wrapper around the base model for custom training logic.
code: def __init__(self, base_model):
      super().__init__()
      self.base_model = base_model
  
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 1 to create a new ModelWithCRFLoss object from inherited base classes: tf.keras with example: obj = ModelWithCRFLoss(base_model)