code: def test_extract_task_arm_conv2d_nchwc():
      data_shape = (1, 64, 128, 128)
      weight_shape = (32, 64, 1, 1)
      bias_shape = (weight_shape[0],)
      padding = (1, 1)
  
      data = relay.var("data", shape=data_shape, dtype="int8")
      weight = relay.var("weight", shape=weight_shape, dtype="int8")
      bias = relay.var("bias", shape=bias_shape, dtype="int32")
      conv2d = relay.nn.conv2d(
          data=data,
          weight=weight,
          kernel_size=weight_shape[2:],
          channels=weight_shape[0],
          padding=padding,
          strides=(1, 1),
          out_dtype="int32",
      )
      bias_add = relay.nn.bias_add(conv2d, bias)
      relay_mod = tvm.IRModule.from_expr(bias_add)
  
      weight_np = np.random.uniform(1, 10, size=weight_shape).astype(
          "int8"
      )
      bias_np = np.random.uniform(1, 10, size=bias_shape).astype(
          "int32"
      )
  
      params = {"weight": weight_np, "bias": bias_np}
  
      target = (
          "llvm -device arm_cpu -mtriple aarch64-linux-gnu -mattr=+neon"
      )
      extracted_tasks = ms.relay_integration.extract_tasks(
          relay_mod, target, params
      )
      tune_tasks = list(
          filter(
              lambda task: "conv2d" in task.task_name,
              extracted_tasks,
          )
      )
  
      assert len(tune_tasks) == 1
  
      relay_func = list(tune_tasks[0].mod.functions.values())[0]
      out_type = relay_func.body.checked_type
  
      # Check that the output is in NCHWc layout
      assert list(out_type.shape) == [1, 8, 130, 130, 4]
  
imports: import platform
  import tempfile
  from typing import List
  import numpy
  import pytest
  import tvm
  import tvm.testing
  from tvm import IRModule
  from tvm import meta_schedule
  from tvm import relay, te, tir
  from tvm._ffi import register_func
  from tvm.contrib import graph_executor
  from tvm.ir.transform import PassContext
  from tvm.meta_schedule.database import TuningRecord, Workload
  from tvm.meta_schedule.testing.relay_workload import get_network
  from tvm.meta_schedule.testing.tlcbench import load_quantized_bert_base
  from tvm.meta_schedule.tune_context import _normalize_mod
  from tvm.script import tir
  from tvm.target import Target
label_desc: Use image node_id 10 for calling a global function with example usage: test_extract_task_arm_conv2d_nchwc() without return types