code: def make_identify_dilated_conv1d_tests(options):
      """Make a set of tests to do 1D dilated convolution."""
  
      test_parameters = [
          {
              "input_shape": [[1, 3, 3], [4, 6, 1]],
              "filter_size": [1, 2, 3],
              "stride": [1, 2],
              "dilations": [1, 2, 3],
              "padding": ["VALID", "SAME"],
              "num_filters": [1, 2],
          },
      ]
  
      def get_tensor_shapes(parameters):
          input_shape = parameters["input_shape"]
          filter_size = parameters["filter_size"]
          filter_shape = [
              filter_size,
              input_shape[2],
              parameters["num_filters"],
          ]
          return [input_shape, filter_shape]
  
      def build_graph(parameters):
          """Build a conv graph given `parameters`."""
          input_shape, filter_shape = get_tensor_shapes(parameters)
          filter_input = tf.compat.v1.placeholder(
              dtype=tf.float32, name="filter", shape=filter_shape
          )
          input_tensor = tf.compat.v1.placeholder(
              dtype=tf.float32, name="input", shape=input_shape
          )
          input_tensors = [input_tensor, filter_input]
  
          out = tf.nn.conv1d(
              input=input_tensor,
              filters=filter_input,
              stride=parameters["stride"],
              dilations=parameters["dilations"],
              padding=parameters["padding"],
          )
          return input_tensors, [out]
  
      def build_inputs(parameters, sess, inputs, outputs):
          input_shape, filter_shape = get_tensor_shapes(parameters)
          values = [
              create_tensor_data(
                  np.float32, input_shape, min_value=-1, max_value=1
              ),
              create_tensor_data(np.float32, filter_shape),
          ]
  
          return values, sess.run(
              outputs, feed_dict=dict(zip(inputs, values))
          )
  
      make_zip_of_tests(
          options,
          test_parameters,
          build_graph,
          build_inputs,
          expected_tf_failures=16,
      )
  
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
label_desc: Use image node_id 1 for calling a global function with example usage: make_identify_dilated_conv1d_tests(options) and returns: list, input_tensors,  list, values,  sess