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- #
- # 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")
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