code: def linear_model():
      # this model will test the fuse_matmul_weight_bias pass
      x = tf.keras.Input(
          batch_input_shape=(1, 10), name="input", dtype=tf.float32
      )
      y = tf.keras.layers.Dense(4)(x)
      y = tf.add(
          y, tf.constant([1, 2, 3, 4], shape=(4,), dtype=tf.float32)
      )
      out = tf.nn.relu(y)
      return tf.keras.Model(inputs=x, outputs=out)
  
imports: import itertools
  import os
  import platform
  from os import chdir, getcwd
  from shutil import rmtree
  from tempfile import mkdtemp
  import numpy
  import pytest
  import coremltools
  from coremltools.converters.mil.frontend.tensorflow.test.test_tf_conversion_api import TestInputOutputConversionAPI
  from coremltools.converters.mil.frontend.tensorflow.test.test_tf_conversion_api import TestiOS16DefaultIODtype
  from coremltools.converters.mil.mil import types
  from coremltools.converters.mil.testing_reqs import backends
  import tensorflow
  from tensorflow import keras
  from tensorflow.keras import layers
label_desc: Use image node_id 19 for calling a global function with example usage: linear_model() and returns: tf