code: def call(self, inputs, training=None, mask=None):
      logging.info(f"xxxx input: {inputs}, training: {training}")
      if isinstance(inputs, dict):
          x = inputs["inputs"]
      elif isinstance(inputs, list):
          x = inputs[0]
      else:
          x = inputs
      x = self.reshape(x)
      x = self.lstm1(x)
      x = self.lstm2(x)
      x = self.dense1(x)
      # x = self.drop1(x, training=training)
      logits = self.dense2(x)
      return logits
  
imports: import numpy
  from absl import logging
  import delta.compat
  from tensorflow.python.keras import backend
  from delta.models.base_model import Model
  from delta.layers.base_layer import Layer
  from delta import utils
  from delta.utils.register import registers
label_desc: Use image node_id 3 for calling the EmoLstmModel obj's underlying member method code with example usage: obj.call(inputs, training, mask) and returns: logits