code: def test_ethosu_clz(accel_type):
      np.random.seed(0)
      ifm_shape = (1, 42, 5, 4)
  
      def create_model():
          ifm = relay.var("ifm", shape=ifm_shape, dtype="int32")
          clz = infra.make_ethosu_unary_elementwise(ifm, 4, "CLZ")
          return tvm.IRModule.from_expr(relay.Function([ifm], clz))
  
      def generate_output_data(input_data):
          def clz_comp(n):
              n_bin = np.binary_repr(n)
              if n_bin[0] == "-":
                  return 0
              else:
                  return 32 - len(n_bin)
  
          return [
              np.array([clz_comp(i) for i in input_data["ifm"].ravel()])
              .reshape(ifm_shape)
              .astype("int32")
          ]
  
      cpu_mod = create_model()
      input_data = {
          "ifm": np.random.randint(
              -500000, high=500000, size=ifm_shape, dtype="int32"
          )
      }
      output_data = {"output": generate_output_data(input_data)[0]}
      ethosu_mod = infra.create_ethosu_partition(cpu_mod)
  
      infra.compare_ethosu_with_reference(
          ethosu_mod, input_data, output_data, accel_type
      )
  
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 29 for calling a global function with example usage: test_ethosu_clz(accel_type) and returns: tvm, list, int, unknown