eric-haibin-lin commented on a change in pull request #8767: Factorization machine example & sparse example folder re-org URL: https://github.com/apache/incubator-mxnet/pull/8767#discussion_r155362275
########## File path: example/sparse/factorization_machine/train.py ########## @@ -0,0 +1,142 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you 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 mxnet as mx +from metric import * +from mxnet.test_utils import * +from model import * +import argparse, os + +parser = argparse.ArgumentParser(description="Run factorization machine with criteo dataset", + formatter_class=argparse.ArgumentDefaultsHelpFormatter) +parser.add_argument('--data-train', type=str, default=None, + help='training dataset in LibSVM format.') +parser.add_argument('--data-test', type=str, default=None, + help='test dataset in LibSVM format.') +parser.add_argument('--num-epoch', type=int, default=1, + help='number of epochs to train') +parser.add_argument('--batch-size', type=int, default=1000, + help='number of examples per batch') +parser.add_argument('--input-size', type=int, default=1000000, + help='number of features in the input') +parser.add_argument('--factor-size', type=int, default=16, + help='number of latent variables') +parser.add_argument('--factor-lr', type=float, default=0.0001, + help='learning rate for factor terms') +parser.add_argument('--linear-lr', type=float, default=0.001, + help='learning rate for linear terms') +parser.add_argument('--bias-lr', type=float, default=0.1, + help='learning rate for bias terms') +parser.add_argument('--factor-wd', type=float, default=0.00001, + help='weight decay rate for factor terms') +parser.add_argument('--linear-wd', type=float, default=0.001, + help='weight decay rate for linear terms') +parser.add_argument('--bias-wd', type=float, default=0.01, + help='weight decay rate for bias terms') +parser.add_argument('--factor-sigma', type=float, default=0.001, + help='standard deviation for initialization of factor terms') +parser.add_argument('--linear-sigma', type=float, default=0.01, + help='standard deviation for initialization of linear terms') +parser.add_argument('--bias-sigma', type=float, default=0.01, + help='standard deviation for initialization of bias terms') +parser.add_argument('--log-interval', type=int, default=100, + help='number of batches between logging messages') +parser.add_argument('--kvstore', type=str, default='local', + help='what kvstore to use', choices=["dist_async", "local"]) + +if __name__ == '__main__': + import logging + head = '%(asctime)-15s %(message)s' + logging.basicConfig(level=logging.INFO, format=head) + + # arg parser + args = parser.parse_args() + logging.info(args) + num_epoch = args.num_epoch + batch_size = args.batch_size + kvstore = args.kvstore + factor_size = args.factor_size + num_features = args.input_size + log_interval = args.log_interval + assert(args.data_train is not None) + assert(args.data_test is not None) Review comment: sure ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
