#   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
# 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.

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import argparse
import distutils.util


def parse_args():
    parser = argparse.ArgumentParser(description=__doc__)
    parser.add_argument(
        '--prepare',
        action='store_true',
        help='create the directories, prepare the vocabulary and embeddings')
    parser.add_argument('--train', action='store_true', help='train the model')
    parser.add_argument(
        '--evaluate', action='store_true', help='evaluate the model on dev set')
    parser.add_argument(
        '--predict',
        action='store_true',
        help='predict the answers for test set with trained model')

    parser.add_argument(
        "--embed_size",
        type=int,
        default=300,
        help="The dimension of embedding table. (default: %(default)d)")
    parser.add_argument(
        "--hidden_size",
        type=int,
        default=150,
        help="The size of rnn hidden unit. (default: %(default)d)")
    parser.add_argument(
        "--learning_rate",
        type=float,
        default=0.001,
        help="Learning rate used to train the model. (default: %(default)f)")
    parser.add_argument('--optim', default='adam', help='optimizer type')
    parser.add_argument(
        "--weight_decay",
        type=float,
        default=0.0001,
        help="Weight decay. (default: %(default)f)")

    parser.add_argument(
        '--drop_rate', type=float, default=0.0, help="Dropout probability")
    parser.add_argument('--random_seed', type=int, default=123)
    parser.add_argument(
        "--batch_size",
        type=int,
        default=32,
        help="The sequence number of a mini-batch data. (default: %(default)d)")
    parser.add_argument(
        "--pass_num",
        type=int,
        default=5,
        help="The number epochs to train. (default: %(default)d)")
    parser.add_argument(
        "--use_gpu",
        type=distutils.util.strtobool,
        default=True,
        help="Whether to use gpu. (default: %(default)d)")
    parser.add_argument(
        "--log_interval",
        type=int,
        default=50,
        help="log the train loss every n batches. (default: %(default)d)")

    parser.add_argument('--max_p_num', type=int, default=5)
    parser.add_argument('--max_a_len', type=int, default=200)
    parser.add_argument('--max_p_len', type=int, default=500)
    parser.add_argument('--max_q_len', type=int, default=60)
    parser.add_argument('--doc_num', type=int, default=5)

    parser.add_argument('--vocab_dir', default='data/vocab', help='vocabulary')
    parser.add_argument(
        "--save_dir",
        type=str,
        default="data/models",
        help="Specify the path to save trained models.")
    parser.add_argument(
        "--save_interval",
        type=int,
        default=1,
        help="Save the trained model every n passes. (default: %(default)d)")
    parser.add_argument(
        "--load_dir",
        type=str,
        default="",
        help="Specify the path to load trained models.")
    parser.add_argument(
        '--log_path',
        help='path of the log file. If not set, logs are printed to console')
    parser.add_argument(
        '--result_dir',
        default='data/results/',
        help='the dir to output the results')
    parser.add_argument(
        '--result_name',
        default='test_result',
        help='the file name of the predicted results')

    parser.add_argument(
        '--trainset',
        nargs='+',
        default=['data/demo/trainset/search.train.json'],
        help='train dataset')
    parser.add_argument(
        '--devset',
        nargs='+',
        default=['data/demo/devset/search.dev.json'],
        help='dev dataset')
    parser.add_argument(
        '--testset',
        nargs='+',
        default=['data/demo/testset/search.test.json'],
        help='test dataset')

    parser.add_argument(
        "--enable_ce",
        action='store_true',
        help="If set, run the task with continuous evaluation logs.")
    parser.add_argument(
        '--para_print', action='store_true', help="Print debug info")
    parser.add_argument(
        "--dev_interval",
        type=int,
        default=-1,
        help="evaluate on dev set loss every n batches. (default: %(default)d)")
    args = parser.parse_args()
    return args