text: # Copyright 2021 The Trieste Contributors
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  r"""
  This package contains the primary interface for deep Gaussian process models. It also contains a
  number of :class:`TrainableProbabilisticModel` wrappers for GPflux-based models. Note that currently
  copying/saving models is not supported, so in a Bayes Opt loop `track_state` should be set False.
  Note as well that `tf.keras.backend.set_floatx()` should be used to set the desired float type,
  consistent with the GPflow float type being used.
  """
  
  from . import config
  from .architectures import build_vanilla_deep_gp
  from .interface import GPfluxPredictor
  from .models import DeepGaussianProcess
  