code: def run_model_tflite(
      model, inputs, CONFIG, truncated, speaker_id=None, style_mel=None
  ):
      if CONFIG.use_gst and style_mel is not None:
          raise NotImplementedError(
              " [!] GST inference not implemented for TfLite"
          )
      if truncated:
          raise NotImplementedError(
              " [!] Truncated inference not implemented for TfLite"
          )
      if speaker_id is not None:
          raise NotImplementedError(
              " [!] Multi-Speaker not implemented for TfLite"
          )
      # get input and output details
      input_details = model.get_input_details()
      output_details = model.get_output_details()
      # reshape input tensor for the new input shape
      model.resize_tensor_input(input_details[0]["index"], inputs.shape)
      model.allocate_tensors()
      detail = input_details[0]
      # input_shape = detail['shape']
      model.set_tensor(detail["index"], inputs)
      # run the model
      model.invoke()
      # collect outputs
      decoder_output = model.get_tensor(output_details[0]["index"])
      postnet_output = model.get_tensor(output_details[1]["index"])
      # tflite model only returns feature frames
      return decoder_output, postnet_output, None, None
  
file_path: TTS/TTS/tts/utils/synthesis.py
imports: import pkg_resources
  import torch
  import numpy
  from .text import text_to_sequence, phoneme_to_sequence
label_desc: Use image node_id 7 for calling a global function with example usage: run_model_tflite(model, inputs, CONFIG, truncated, speaker_id, style_mel) and returns: decoder_output,  postnet_output,  None,  None