class_docstr: Applies a max_pool2d on top of the last feature map
code: def forward(
      self, x: List[Tensor], y: List[Tensor], names: List[str]
  ) -> Tuple[List[Tensor], List[str]]:
      names.append("pool")
      x.append(
          F.max_pool2d(x[-1], 1, 2, 0)
      )  # input, kernel_size, stride, padding
      return x, names
  
imports: from collections import OrderedDict
  import torch.nn
  import torch
  from torch import Tensor
  import torch.nn.functional
  from torch.jit.annotations import Tuple, List, Dict
label_desc: Use image node_id 1 for calling the LastLevelMaxPool obj's underlying member method code with example usage: obj.forward(x, y, names) and returns: x,  names