code: def format(self, node):
      lstm_params = self._default_config_params(node)
      lstm_params["n_in"] = node.get_attr("n_in")
      lstm_params["n_out"] = node.get_attr("n_out")
      lstm_params["n_outputs"] = (
          node.get_attr("n_timesteps")
          if node.get_attr("return_sequences", False)
          else "1"
      )
  
      lstm_params["return_sequences"] = str(
          node.get_attr("return_sequences")
      ).lower()
      lstm_params["act_t"] = "{}_config{}".format(
          node.get_attr("activation"), str(node.index) + "_act"
      )
      lstm_params["act_recurrent_t"] = "{}_config{}".format(
          node.get_attr("recurrent_activation"),
          str(node.index) + "_rec_act",
      )
      lstm_config = self.template.format(**lstm_params)
  
      act_params = self._default_config_params(node)
      act_params["type"] = node.get_attr("activation")
      act_params["n_in"] = node.get_attr("n_out")
      act_params["index"] = str(node.index) + "_act"
      act_config = self.act_template.format(**act_params)
  
      recr_act_params = self._default_config_params(node)
      recr_act_params["type"] = node.get_attr("recurrent_activation")
      recr_act_params["n_in"] = node.get_attr("n_out")
      recr_act_params["index"] = str(node.index) + "_rec_act"
      recr_act_config = self.recr_act_template.format(**recr_act_params)
  
      return act_config + "\n" + recr_act_config + "\n" + lstm_config
  
imports: from hls4ml.backends.backend import get_backend
  from hls4ml.backends.template import FunctionCallTemplate, LayerConfigTemplate
  from hls4ml.model.layers import GRU, LSTM, SimpleRNN
label_desc: Use image node_id 2 for calling the LSTMConfigTemplate obj's underlying member method code with example usage: obj.format(node) and returns: unknown