code: def make_cond_tests(options):
      """Make a set of tests to do relu1."""
  
      # Chose a set of parameters
      test_parameters = [
          {
              # Note: The `tf.string` test case also serves as a regression test to
              # ensure that branch subgraph with dynamically allocated inputs/outputs
              # are handled correctly.
              "dtype": [tf.float32, tf.string],
              "pred": [False, True],
          }
      ]
  
      def build_graph(parameters):
          """Build the graph for cond tests."""
          input1 = tf.compat.v1.placeholder(
              dtype=parameters["dtype"], shape=(1,)
          )
          input2 = tf.compat.v1.placeholder(
              dtype=parameters["dtype"], shape=(1,)
          )
          # MLIR TFLite converter can't handle scalar inputs. This is a workaround
          # to input (1,) tensors and then reshape to scalar.
          # TODO(b/129003347): Remove the workaround after scalar inputs are
          # supported.
          pred = tf.compat.v1.placeholder(dtype=tf.bool, shape=(1,))
          pred_scalar = tf.reshape(pred, ())
  
          out = tf.cond(
              pred=pred_scalar,
              true_fn=lambda: input1,
              false_fn=lambda: input2,
          )
          return [input1, input2, pred], [out]
  
      def build_inputs(parameters, sess, inputs, outputs):
          input_values = [
              create_tensor_data(parameters["dtype"], (1,)),
              create_tensor_data(parameters["dtype"], (1,)),
              np.array([parameters["pred"]], dtype=np.bool_),
          ]
          return input_values, sess.run(
              outputs, feed_dict=dict(zip(inputs, input_values))
          )
  
      make_zip_of_tests(
          options, test_parameters, build_graph, build_inputs
      )
  
imports: import numpy
  import tensorflow
  from tensorflow.lite.testing.zip_test_utils import create_tensor_data
  from tensorflow.lite.testing.zip_test_utils import make_zip_of_tests
  from tensorflow.lite.testing.zip_test_utils import register_make_test_function
  from tensorflow.python.framework import test_util
label_desc: Use image node_id 1 for calling a global function with example usage: make_cond_tests(options) and returns: list,  list, input_values,  sess