123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293 |
- #
- # 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 argparse
- from pipeline.backend.pipeline import PipeLine
- from pipeline.component import DataTransform
- from pipeline.component import Evaluation
- from pipeline.component import HeteroPoisson
- from pipeline.component import Intersection
- from pipeline.component import Reader
- from pipeline.interface import Data, Model
- from pipeline.utils.tools import load_job_config
- def main(config="../../config.yaml", namespace=""):
- # obtain config
- if isinstance(config, str):
- config = load_job_config(config)
- parties = config.parties
- guest = parties.guest[0]
- host = parties.host[0]
- arbiter = parties.arbiter[0]
- guest_train_data = {"name": "dvisits_hetero_guest", "namespace": f"experiment{namespace}"}
- host_train_data = {"name": "dvisits_hetero_host", "namespace": f"experiment{namespace}"}
- pipeline = PipeLine().set_initiator(role='guest', party_id=guest).set_roles(guest=guest, host=host, arbiter=arbiter)
- reader_0 = Reader(name="reader_0")
- reader_0.get_party_instance(role='guest', party_id=guest).component_param(table=guest_train_data)
- reader_0.get_party_instance(role='host', party_id=host).component_param(table=host_train_data)
- data_transform_0 = DataTransform(name="data_transform_0")
- data_transform_0.get_party_instance(
- role='guest',
- party_id=guest).component_param(
- with_label=True,
- label_name="doctorco",
- label_type="float",
- output_format="dense")
- data_transform_0.get_party_instance(role='host', party_id=host).component_param(with_label=False)
- intersection_0 = Intersection(name="intersection_0")
- hetero_poisson_0 = HeteroPoisson(name="hetero_poisson_0", early_stop="weight_diff", max_iter=3,
- alpha=100.0, batch_size=-1, learning_rate=0.01, optimizer="rmsprop",
- exposure_colname="exposure", decay_sqrt=False, tol=0.001,
- callback_param={"callbacks": ["ModelCheckpoint"]},
- init_param={"init_method": "zeros"}, penalty="L2")
- hetero_poisson_1 = HeteroPoisson(name="hetero_poisson_1", early_stop="weight_diff", max_iter=10,
- alpha=100.0, batch_size=-1, learning_rate=0.01, optimizer="rmsprop",
- exposure_colname="exposure", decay_sqrt=False, tol=0.001, penalty="L2")
- evaluation_0 = Evaluation(name="evaluation_0", eval_type="regression", pos_label=1)
- evaluation_0.get_party_instance(role='host', party_id=host).component_param(need_run=False)
- pipeline.add_component(reader_0)
- pipeline.add_component(data_transform_0, data=Data(data=reader_0.output.data))
- pipeline.add_component(intersection_0, data=Data(data=data_transform_0.output.data))
- pipeline.add_component(hetero_poisson_0, data=Data(train_data=intersection_0.output.data))
- pipeline.add_component(hetero_poisson_1, data=Data(train_data=intersection_0.output.data),
- model=Model(model=hetero_poisson_0.output.model))
- pipeline.add_component(evaluation_0, data=Data(data=hetero_poisson_1.output.data))
- pipeline.compile()
- pipeline.fit()
- if __name__ == "__main__":
- parser = argparse.ArgumentParser("PIPELINE DEMO")
- parser.add_argument("-config", type=str,
- help="config file")
- args = parser.parse_args()
- if args.config is not None:
- main(args.config)
- else:
- main()
|