code: def inference_tflite(self, characters):
      B, T = shape_list(characters)
      embedding_vectors = self.embedding(characters, training=False)
      encoder_output = self.encoder(embedding_vectors, training=False)
      decoder_states = self.decoder.build_decoder_initial_states(
          B, 512, T
      )
      decoder_frames, stop_tokens, attentions = self.decoder(
          encoder_output, decoder_states, training=False
      )
      postnet_frames = self.postnet(decoder_frames, training=False)
      output_frames = decoder_frames + postnet_frames
      print(output_frames.shape)
      return decoder_frames, output_frames, attentions, stop_tokens
  
file_path: TTS/TTS/tts/tf/models/tacotron2.py
imports: import tensorflow
  from tensorflow import keras
  from TTS.tts.tf.layers.tacotron2 import Encoder, Decoder, Postnet
  from TTS.tts.tf.utils.tf_utils import shape_list
label_desc: Use image node_id 5 for calling the Tacotron2 obj's underlying member method code with example usage: obj.inference_tflite(characters) and returns: decoder_frames,  output_frames,  attentions,  stop_tokens