docstr: Load and run TFLite model under the interpreter.
docstr_tok: ["Load","and","run","TFLite","model","under","the","interpreter","."]
code: def RunTfliteModel(self, tflite_model_path):
      """Load and run TFLite model under the interpreter."""
      interpreter = tf.lite.Interpreter(tflite_model_path)
      interpreter.allocate_tensors()
      input_details = interpreter.get_input_details()
      interpreter.set_tensor(
          input_details[0]["index"],
          np.array(self._test_waveform, dtype=np.float32),
      )
      interpreter.invoke()
      output_details = interpreter.get_output_details()
      output_data = interpreter.get_tensor(output_details[0]["index"])
      return output_data
  
imports: import tempfile
  from magenta.models.onsets_frames_transcription import melspec_input
  import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 12 for calling the MelspecInputTest obj's underlying member method code with example usage: obj.RunTfliteModel(tflite_model_path) and returns: output_data