code: def test_masked_input(self, use_cpu_only, backend):
      input_shape = [4, 10, 8]
      val = np.random.rand(*input_shape).astype(np.float32)
  
      @make_tf_graph([input_shape])
      def build_model(input):
          sliced_input = input[..., 4]
          mask = tf.where_v2(sliced_input > 0)
          masked_input = tf.gather_nd(input, mask)
          return masked_input
  
      model, inputs, outputs = build_model
  
      input_values = [val]
      input_dict = dict(zip(inputs, input_values))
      run_compare_tf(
          model,
          input_dict,
          outputs,
          use_cpu_only=use_cpu_only,
          frontend_only=False,
          backend=backend,
      )
  
imports: from coremltools.converters.mil import testing_reqs
  from coremltools.converters.mil.testing_reqs import *
  from coremltools.converters.mil.frontend.tensorflow.test.testing_utils import make_tf_graph, run_compare_tf, layer_counts
  import math
label_desc: Use image node_id 1 for calling the TestTF1Graphs obj's underlying member method code with example usage: obj.test_masked_input(use_cpu_only, backend) and returns: masked_input