code: def get_some_model(x_np, y_np, sanity_check=True):
      x_input = tf.keras.layers.Input(shape=x_np.shape[1:])
      crf_outputs = CRF(5, name="L")(x_input)
      base_model = tf.keras.Model(x_input, crf_outputs)
  
      model = ModelWithCRFLoss(base_model)
  
      model.compile("adam")
      if sanity_check:
          model.fit(x=x_np, y=y_np)
          model.evaluate(x_np, y_np)
      model.predict(x_np)
      return 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 7 for calling a global function with example usage: get_some_model(x_np, y_np, sanity_check) and returns: model