code: def forward(self, x):
      # PyTorch 1.9 does not support empty tensor inference yet
      if x.numel() == 0 and obsolete_torch_version(
          TORCH_VERSION, (1, 9)
      ):
          out_shape = list(x.shape[:2])
          for i, k, p, s, d in zip(
              x.shape[-2:],
              _pair(self.kernel_size),
              _pair(self.padding),
              _pair(self.stride),
              _pair(self.dilation),
          ):
              o = (i + 2 * p - (d * (k - 1) + 1)) / s + 1
              o = math.ceil(o) if self.ceil_mode else math.floor(o)
              out_shape.append(o)
          empty = NewEmptyTensorOp.apply(x, out_shape)
          return empty
  
      return super().forward(x)
  
imports: import math
  import torch
  import torch.nn
  from torch.nn.modules.utils import _pair, _triple
  from .registry import CONV_LAYERS, UPSAMPLE_LAYERS
label_desc: Use image node_id 1 for calling the MaxPool2d obj's underlying member method code with example usage: obj.forward(x) and returns: super, empty