code: def call(self, inputs, training=None, mask=None):
      # logging.info(f"xxxx input: {inputs}, training: {training}")
      speechs = inputs["inputs"]
      speechs = self.speech(speechs)
      texts = inputs["texts"]
      texts = self.text(texts)
      speechs = self.reshape1(speechs)
      speechs = self.speech_dense(speechs)
      speechs = self.speech_d(speechs)
  
      texts_mask = get_expand_pad_mask(texts, self.padding_id)
  
      text_embed = self.embed(texts)
      text_embed = self.embed_d(text_embed, training=training)
  
      text_enc, _ = self.text_enc_layer(
          text_embed, training=training, mask=texts_mask
      )
  
      text_enc = self.text_enc_d(text_enc, training=training)
  
      speech_enc, _ = self.speech_enc_layer(speechs, training=training)
      speech_enc = self.speech_enc_d(speech_enc, training=training)
  
      attn_outs, _ = self.align_attn_layer(
          (text_enc, speech_enc, speech_enc), training=training
      )
      attn_outs = self.attn_enc_d(attn_outs, training=training)
      attn_outs = self.reshape2(attn_outs)
  
      attn_outs = self.concatenate([attn_outs, text_enc])
      align_enc = self.align_enc_layer(
          attn_outs, training=training, mask=texts_mask
      )
  
      align_enc = self.align_enc_d(align_enc, training=training)
  
      scores = self.final_dense(align_enc)
      return scores
  
file_path: delta/delta/models/multimodal_cls_model.py
imports: import numpy
  from absl import logging
  import delta.compat
  import delta.layers
  from delta.models.base_model import Model
  from delta.utils.register import registers
  from delta.layers.utils import get_expand_pad_mask
  import pickle
label_desc: Use image node_id 3 for calling the AlignClassModel obj's underlying member method code with example usage: obj.call(inputs, training, mask) and returns: scores