args.py

# Copyright (c) 2020 PaddlePaddle 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.
# pylint: disable=doc-string-missing
import argparse


def parse_args():
    parser = argparse.ArgumentParser(description="PaddlePaddle CTR example")
    parser.add_argument(
        '--train_data_path',
        type=str,
        default='./data/raw/train.txt',
        help="The path of training dataset")
    parser.add_argument(
        '--sparse_only',
        type=bool,
        default=False,
        help="Whether we use sparse features only")
    parser.add_argument(
        '--test_data_path',
        type=str,
        default='./data/raw/valid.txt',
        help="The path of testing dataset")
    parser.add_argument(
        '--batch_size',
        type=int,
        default=1000,
        help="The size of mini-batch (default:1000)")
    parser.add_argument(
        '--embedding_size',
        type=int,
        default=10,
        help="The size for embedding layer (default:10)")
    parser.add_argument(
        '--num_passes',
        type=int,
        default=10,
        help="The number of passes to train (default: 10)")
    parser.add_argument(
        '--model_output_dir',
        type=str,
        default='models',
        help='The path for model to store (default: models)')
    parser.add_argument(
        '--sparse_feature_dim',
        type=int,
        default=1000001,
        help='sparse feature hashing space for index processing')
    parser.add_argument(
        '--is_local',
        type=int,
        default=1,
        help='Local train or distributed train (default: 1)')
    parser.add_argument(
        '--cloud_train',
        type=int,
        default=0,
        help='Local train or distributed train on paddlecloud (default: 0)')
    parser.add_argument(
        '--async_mode',
        action='store_true',
        default=False,
        help='Whether start pserver in async mode to support ASGD')
    parser.add_argument(
        '--no_split_var',
        action='store_true',
        default=False,
        help='Whether split variables into blocks when update_method is pserver')
    parser.add_argument(
        '--role',
        type=str,
        default='pserver',  # trainer or pserver
        help='The path for model to store (default: models)')
    parser.add_argument(
        '--endpoints',
        type=str,
        default='127.0.0.1:6000',
        help='The pserver endpoints, like: 127.0.0.1:6000,127.0.0.1:6001')
    parser.add_argument(
        '--current_endpoint',
        type=str,
        default='127.0.0.1:6000',
        help='The path for model to store (default: 127.0.0.1:6000)')
    parser.add_argument(
        '--trainer_id',
        type=int,
        default=0,
        help='The path for model to store (default: models)')
    parser.add_argument(
        '--trainers',
        type=int,
        default=1,
        help='The num of trianers, (default: 1)')
    return parser.parse_args()