code: def test_resize(
      dtype,
      shape,
      size,
      coordinate_transformation_mode,
      rounding_method,
  ):
      """Compare Resize output with TVM."""
  
      np.random.seed(0)
      zp_min = np.iinfo(dtype).min
      zp_max = np.iinfo(dtype).max
      inputs = {
          "x": tvm.nd.array(
              np.random.randint(
                  zp_min, high=zp_max + 1, size=shape, dtype=dtype
              )
          ),
      }
      outputs = []
      for npu in [False, True]:
          model = _get_model(
              shape=shape,
              dtype=dtype,
              size=size,
              coordinate_transformation_mode=coordinate_transformation_mode,
              rounding_method=rounding_method,
          )
          mod = tei.make_module(model, {})
          x = tei.build_and_run(mod, inputs, 1, {}, npu=npu)
          outputs.append(x)
  
      tei.verify(outputs, dtype, 1)
  
file_path: tvm/tests/python/contrib/test_ethosn/test_resize.py
imports: import pytest
  import numpy
  import tvm
  from tvm import relay
  from tvm.testing import requires_ethosn
  from .None import infrastructure
label_desc: Use image node_id 2 for calling a global function with example usage: test_resize(dtype, shape, size, coordinate_transformation_mode, rounding_method) without return types