#
#  Copyright 2019 The FATE Authors. All Rights Reserved.
#
#  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.
#

import typing

from federatedml.framework.weights import Weights


class NNModel(object):
    def get_model_weights(self) -> Weights:
        pass

    def set_model_weights(self, weights: Weights):
        pass

    def export_model(self):
        pass

    def load_model(self):
        pass

    def train(self, data, **kwargs):
        pass

    def predict(self, data, **kwargs):
        pass

    def evaluate(self, data, **kwargs):
        pass

    def modify(self, func: typing.Callable[[Weights], Weights]) -> Weights:
        weights = self.get_model_weights()
        self.set_model_weights(func(weights))
        return weights


class DataConverter(object):
    def convert(self, data, *args, **kwargs):
        pass


def get_nn_builder(config_type):

    if config_type == "keras":
        from federatedml.transfer_learning.hetero_ftl.backend.tf_keras.nn_model import build_keras
        return build_keras
    else:
        raise ValueError(f"{config_type} is not supported")