74 lines
3.1 KiB
Python
74 lines
3.1 KiB
Python
# Copyright 2018 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# A program to perform training of an XGBoost model through a dataproc cluster.
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# Usage:
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# python train.py \
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# --project bradley-playground \
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# --region us-central1 \
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# --cluster ten4 \
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# --package gs://bradley-playground/xgboost4j-example-0.8-SNAPSHOT-jar-with-dependencies.jar \
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# --output gs://bradley-playground/train/model \
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# --conf gs://bradley-playground/trainconf.json \
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# --rounds 300 \
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# --workers 2 \
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# --train gs://bradley-playground/transform/train/part-* \
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# --eval gs://bradley-playground/transform/eval/part-* \
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# --analysis gs://bradley-playground/analysis \
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# --target resolution
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import argparse
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import logging
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from common import _utils
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def main(argv=None):
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parser = argparse.ArgumentParser(description='ML Trainer')
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parser.add_argument('--project', type=str, help='Google Cloud project ID to use.')
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parser.add_argument('--region', type=str, help='Which zone to run the analyzer.')
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parser.add_argument('--cluster', type=str, help='The name of the cluster to run job.')
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parser.add_argument('--package', type=str,
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help='GCS Path of XGBoost distributed trainer package.')
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parser.add_argument('--output', type=str, help='GCS path to use for output.')
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parser.add_argument('--conf', type=str, help='GCS path of the training json config file.')
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parser.add_argument('--rounds', type=int, help='Number of rounds to train.')
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parser.add_argument('--workers', type=int, help='Number of workers to use for training.')
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parser.add_argument('--train', type=str, help='GCS path of the training libsvm file pattern.')
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parser.add_argument('--eval', type=str, help='GCS path of the eval libsvm file pattern.')
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parser.add_argument('--analysis', type=str, help='GCS path of the analysis input.')
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parser.add_argument('--target', type=str, help='Target column name.')
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args = parser.parse_args()
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logging.getLogger().setLevel(logging.INFO)
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api = _utils.get_client()
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logging.info('Submitting job...')
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spark_args = [args.conf, str(args.rounds), str(args.workers), args.analysis, args.target,
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args.train, args.eval, args.output]
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job_id = _utils.submit_spark_job(
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api, args.project, args.region, args.cluster, [args.package],
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'ml.dmlc.xgboost4j.scala.example.spark.XGBoostTrainer', spark_args)
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logging.info('Job request submitted. Waiting for completion...')
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_utils.wait_for_job(api, args.project, args.region, job_id)
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with open('/output.txt', 'w') as f:
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f.write(args.output)
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logging.info('Job completed.')
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if __name__== "__main__":
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main()
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