class_docstr: Simpler version of CompositionalNN
class_docstr_tok: ["Simpler","version","of","CompositionalNN"]
code: def forward(
      self, x: List[torch.Tensor], device: str = "cpu"
  ) -> torch.Tensor:
      combined = torch.sum(torch.cat(x, dim=0), dim=0, keepdim=True)
      subtree_embedding = self.linear_seq(combined)
      return subtree_embedding
  
imports: from typing import Any, List, Sized, Tuple
  import torch
  import torch.nn
  from pytext.torchscript.utils import reverse_tensor_list
  from pytext.utils.cuda import FloatTensor
  from pytext.utils.tensor import xaviervar
label_desc: Use image node_id 2 for calling the CompositionalSummationNN obj's underlying member method code with example usage: obj.forward(x, device) and returns: subtree_embedding