code: def test_ethosu_section_name():
      np.random.seed(0)
  
      @tf.function
      def depthwise_conv2d(x):
          weight_shape = [3, 3, 3, 1]
          weight = tf.constant(
              np.random.uniform(size=weight_shape), dtype=tf.float32
          )
          tf_strides = [1, 1, 1, 1]
          op = tf.nn.depthwise_conv2d(
              x,
              weight,
              strides=tf_strides,
              padding="SAME",
              dilations=(2, 2),
          )
          return op
  
      mod, tflite_graph = infra.get_tflite_graph(
          depthwise_conv2d, [(1, 55, 55, 3)]
      )
  
      # Generate reference data
      input_data, output_data = infra.generate_ref_data_tflite(
          tflite_graph
      )
  
      test_runner = infra.create_test_runner()
      compiled_models = infra.build_source(
          mod, input_data, output_data, test_runner
      )
  
      # Assumes only two runtime.Modules are created -- i.e. single offload module
      ethosu_module = (
          compiled_models[0]
          .executor_factory.lib.imported_modules[0]
          .imported_modules[0]
      )
  
      # Verify generated C source
      source = ethosu_module.get_source()
      assert (
          '__attribute__((section(".rodata.tvm"), aligned(16))) static int8_t tvmgen_default_ethos_u_main_0_cms_data_data'
          in source
      )
      assert (
          '__attribute__((section(".rodata.tvm"), aligned(16))) static int8_t tvmgen_default_ethos_u_main_0_weights'
          in source
      )
  
imports: import pytest
  import numpy
  import tflite.Model
  import tvm
  import tensorflow
  from tvm import relay
  from tvm.relay.backend.contrib.ethosu import util
  from tvm.relay.op.contrib.ethosu import partition_for_ethosu
  from tvm.testing.aot import generate_ref_data
  from .None import infra
label_desc: Use image node_id 28 for calling a global function with example usage: test_ethosu_section_name() and returns: op