sedna/examples/federated_learning/yolov5_coco128_mistnet/train.py

# Copyright 2021 The KubeEdge Authors.
#
# 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 os
from interface import mistnet, s3_transmitter
from interface import Dataset, Estimator
from sedna.common.config import BaseConfig
from sedna.core.federated_learning import FederatedLearningV2

def main():
    data = Dataset()
    estimator = Estimator()
    data.parameters["data_path"] = BaseConfig.train_dataset_url.replace("robot.txt", "")
    data.parameters["train_path"] = os.path.join(data.parameters["data_path"], "./coco128/images/train2017/")
    data.parameters["test_path"] = data.parameters["train_path"]
    fl_model = FederatedLearningV2(
        data=data,
        estimator=estimator,
        aggregation=mistnet,
        transmitter=s3_transmitter)

    fl_model.train()

if __name__ == '__main__':
    main()