class_docstr: The Stack LSTM from Dyer et al: https://arxiv.org/abs/1505.08075
class_docstr_tok: ["The","Stack","LSTM","from","Dyer","et","al",":","https",":","\/\/arxiv.org\/abs\/1505.08075"]
docstr: Shapes:
      return value: (1, lstm_hidden_dim)
docstr_tok: ["Shapes",":","return","value",":","(","1",",","lstm_hidden_dim",")"]
code: def embedding(self) -> torch.Tensor:
      """
      Shapes:
          return value: (1, lstm_hidden_dim)
      """
      assert len(self.stack) > 0, "stack size must be greater than 0"
  
      top_state = self.stack[-1][0]
      return self._lstm_output(top_state)
  
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 5 for calling the StackLSTM obj's underlying member method code with example usage: obj.embedding() and returns: self