code: def _darknet_maxpooling(inputs, params, attrs, prefix):
      """Process the max pool 2d operation."""
      new_attrs = {}
      kernel = attrs.get("kernel")
      strides = attrs.get("stride", 1)
      pads = attrs.get("pad", 1)
      new_attrs["pool_size"] = (kernel, kernel)
      new_attrs["strides"] = (strides, strides)
      new_attrs["padding"] = (pads, pads)
      extra_pad_size = attrs.get("extra_pad_size", 0)
      if extra_pad_size:
          pad_width = (
              (0, 0),
              (0, 0),
              (0, extra_pad_size),
              (0, extra_pad_size),
          )
          inputs = [
              get_relay_op("pad")(
                  *inputs,
                  pad_width=pad_width,
                  pad_value=np.finfo(np.float32).min,
              )
          ]
      return get_relay_op("max_pool2d")(*inputs, **new_attrs)
  
imports: from enum import Enum
  import numpy
  import tvm
  from tvm.ir import IRModule
  from ..None import analysis
  from ..None import expr
  from ..None import function
  from .common import get_relay_op, new_var
label_desc: Use image node_id 5 for calling a global function with example usage: _darknet_maxpooling(inputs, params, attrs, prefix) and returns: get_relay_op