Missing some boosted trees operations in Tensorflow Lite

I have a Tensorflow model based on BoostedTreesClassifier and I want to deploy it on a mobile with the help of Tensorflow Lite.

However, when I try to convert my model to the Tensorflow Lite model I get an error saying that there are unsupported operations (as of Tensorflow v2.3.1):

tf.BoostedTreesBucketize
tf.BoostedTreesEnsembleResourceHandleOp
tf.BoostedTreesPredict
tf.BoostedTreesQuantileStreamResourceGetBucketBoundaries
tf.BoostedTreesQuantileStreamResourceHandleOp

Adding tf.lite.OpsSet.SELECT_TF_OPS option helps a bit, but still some operations need a custom implementation:

tf.BoostedTreesEnsembleResourceHandleOp
tf.BoostedTreesPredict
tf.BoostedTreesQuantileStreamResourceGetBucketBoundaries
tf.BoostedTreesQuantileStreamResourceHandleOp

I've also tried Tensorflow v2.4.0-rc3, which reduces the set to the following one:

tf.BoostedTreesEnsembleResourceHandleOp
tf.BoostedTreesPredict

Conversion code is like the following:

converter = tf.lite.TFLiteConverter.from_saved_model(model_path, signature_keys=['serving_default'])
converter.target_spec.supported_ops = [
    tf.lite.OpsSet.TFLITE_BUILTINS,
    tf.lite.OpsSet.SELECT_TF_OPS
]

tflite_model = converter.convert()

signature_keys is specified explicitly, because the model exported with BoostedTreesClassifier#export_saved_model has multiple signatures.

Is there a way to deploy this model on mobile other than writing custom implementation for non-supported ops?