title: Failed to do full integer quantization using tflite converter from a saved model: ValueError: Failed to parse the model: pybind11::init():
body: <p>I am using tflite converter and input generators to create an end to end quantized tflite file from a saved model.</p>
  <p>Tensorflow version is 2.3, and I am running the following code:</p>
  <pre><code>input_shape=(int(dataDimension / inputDims), inputDims,1)
  batch_input_shape= (1,) + input_shape
  def representative_dataset_gen():
  
  for i in range(110):
      image = Xtrain_[i].reshape(batch_input_shape)
      yield [image]
  
  converter = tf.lite.TFLiteConverter.from_saved_model('saved_model/my_model')
  converter.optimizations = [tf.lite.Optimize.DEFAULT]
  
  converter.representative_dataset = representative_dataset_gen
  converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS_INT8]
  converter.inference_input_type = tf.int8  
  converter.inference_output_type = tf.int8  
  tflite_quant_model = converter.convert()
  tflite_file = &quot;FGRNN_Q.tflite&quot;
  open(tflite_file, 'wb').write(tflite_quant_model)
  </code></pre>
  <p>and the error that I receive is:</p>
  <p><code>ValueError: Failed to parse the model: pybind11::init(): factory function returned nullptr</code></p>