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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 argparse
- import json
- from pipeline.backend.pipeline import PipeLine
- from pipeline.component import DataTransform
- from pipeline.component.evaluation import Evaluation
- from pipeline.component.intersection import Intersection
- from pipeline.component.reader import Reader
- from pipeline.interface.data import Data
- from pipeline.interface.model import Model
- from pipeline.component.data_statistics import DataStatistics
- from pipeline.utils.tools import load_job_config
- def prettify(response, verbose=True):
- if verbose:
- print(json.dumps(response, indent=4, ensure_ascii=False))
- print()
- return response
- def main(config="../../config.yaml", namespace=""):
- if isinstance(config, str):
- config = load_job_config(config)
- parties = config.parties
- guest = parties.guest[0]
- hosts = parties.host[0]
- guest_train_data = {"name": "ionosphere_scale_hetero_guest", "namespace": f"experiment{namespace}"}
- host_train_data = {"name": "ionosphere_scale_hetero_host", "namespace": f"experiment{namespace}"}
- # guest_train_data = {"name": "default_credit_hetero_guest", "namespace": f"experiment{namespace}"}
- # host_train_data = {"name": "default_credit_hetero_host", "namespace": f"experiment{namespace}"}
- # initialize pipeline
- pipeline = PipeLine()
- # set job initiator
- pipeline.set_initiator(role='guest', party_id=guest)
- # set participants information
- pipeline.set_roles(guest=guest, host=hosts)
- # define Reader components to read in data
- reader_0 = Reader(name="reader_0")
- # configure Reader for guest
- reader_0.get_party_instance(role='guest', party_id=guest).component_param(table=guest_train_data)
- # configure Reader for host
- reader_0.get_party_instance(role='host', party_id=hosts).component_param(table=host_train_data)
- data_transform_0 = DataTransform(name="data_transform_0", output_format='dense', missing_fill=False)
- # get DataTransform party instance of guest
- data_transform_0_guest_party_instance = data_transform_0.get_party_instance(role='guest', party_id=guest)
- # configure DataTransform for guest
- data_transform_0_guest_party_instance.component_param(with_label=True, label_name="label")
- # get and configure DataTransform party instance of host
- data_transform_0.get_party_instance(role='host', party_id=hosts).component_param(with_label=False)
- # define Intersection components
- intersection_0 = Intersection(name="intersection_0")
- 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))
- statistic_param = {
- "name": "statistic_0",
- "statistics": ["95%", "coefficient_of_variance", "stddev"],
- "column_indexes": [1, 2],
- "column_names": ["x3"]
- }
- statistic_0 = DataStatistics(**statistic_param)
- pipeline.add_component(statistic_0, data=Data(data=intersection_0.output.data))
- pipeline.compile()
- # fit model
- pipeline.fit()
- # query component summary
- prettify(pipeline.get_component("statistic_0").get_summary())
- 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()
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