code: def export_averagepool_3d_dilations_large() -> None:
      x_shape = (32, 32, 32)
      dilations = (2, 2, 2)
      kernel_shape = (5, 5, 5)
      strides = (3, 3, 3)
      count_include_pad = 0
  
      for count_include_pad in (0, 1):
          for ceil_mode in (True, False):
              node = onnx.helper.make_node(
                  "AveragePool",
                  inputs=["x"],
                  outputs=["y"],
                  kernel_shape=kernel_shape,
                  strides=strides,
                  dilations=dilations,
                  count_include_pad=count_include_pad,
                  ceil_mode=ceil_mode,
              )
  
              x = np.random.randn(1, 1, *x_shape).astype(np.float32)
              out_shape, pads = get_output_shape_explicit_padding(
                  None,
                  x_shape,
                  kernel_shape,
                  strides,
                  dilations=dilations,
                  ceil_mode=ceil_mode,
              )
              padded = np.pad(
                  x,
                  (
                      (0, 0),
                      (0, 0),
                      (pads[0], pads[3]),
                      (pads[1], pads[4]),
                      (pads[2], pads[5]),
                  ),
                  mode="constant",
                  constant_values=0
                  if count_include_pad == 1
                  else np.nan,
              )
              y = pool(
                  padded,
                  (1, 1, *x_shape),
                  kernel_shape,
                  strides,
                  out_shape,
                  "AVG",
                  pads=pads,
                  dilations=dilations,
                  count_include_pad=count_include_pad,
              )
  
              test_name = f"test_averagepool_3d_dilations_large_count_include_pad_is_{count_include_pad}_ceil_mode_is_{ceil_mode}"
              expect(node, inputs=[x], outputs=[y], name=test_name)
  
imports: import numpy
  import onnx
  from onnx.backend.test.case.base import Base
  from onnx.backend.test.case.node import expect
  from onnx.reference.ops.op_pool_common import get_output_shape_auto_pad, get_output_shape_explicit_padding, get_pad_shape, pool
label_desc: Use image node_id 16 for calling the AveragePool obj's underlying member method code with example usage: obj.export_averagepool_3d_dilations_large() without return types