code: def test_relay_reshape_codegen(ifm_shape, new_shape, accel_type):
      np.random.seed(0)
  
      def create_model():
          ifm = relay.var("ifm", shape=ifm_shape, dtype="int8")
          reshape = relay.op.reshape(ifm, newshape=new_shape)
          return tvm.IRModule.from_expr(relay.Function([ifm], reshape))
  
      cpu_mod = create_model()
      input_data = {
          "ifm": np.random.randint(
              -128, high=127, size=ifm_shape, dtype="int8"
          )
      }
      output_data = generate_ref_data(cpu_mod, input_data)
      ethosu_mod = infra.create_ethosu_partition(cpu_mod)
  
      infra.compare_ethosu_with_reference(
          ethosu_mod,
          input_data,
          output_data,
          accel_type,
          enable_cascader=is_u55_accel_type(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 24 for calling a global function with example usage: test_relay_reshape_codegen(ifm_shape, new_shape, accel_type) and returns: tvm