arguments.py

import argparse
import os


def argparser():
    parser = argparse.ArgumentParser()
    # for model
    parser.add_argument(
        '--seq_window_lengths',
        type=int,
        nargs='+',
        help='Space seperated list of motif filter lengths. (ex, --window_lengths 4 8 12)'
    )
    parser.add_argument(
        '--smi_window_lengths',
        type=int,
        nargs='+',
        help='Space seperated list of motif filter lengths. (ex, --window_lengths 4 8 12)'
    )
    parser.add_argument(
        '--num_windows',
        type=int,
        nargs='+',
        help='Space seperated list of the number of motif filters corresponding to length list. (ex, --num_windows 100 200 100)'
    )
    parser.add_argument(
        '--num_hidden',
        type=int,
        default=0,
        help='Number of neurons in hidden layer.'
    )
    parser.add_argument(
        '--num_classes',
        type=int,
        default=0,
        help='Number of classes (families).'
    )
    parser.add_argument(
        '--max_seq_len',
        type=int,
        default=0,
        help='Length of input sequences.'
    )
    parser.add_argument(
        '--max_smi_len',
        type=int,
        default=0,
        help='Length of input sequences.'
    )
    # for learning
    parser.add_argument(
        '--learning_rate',
        type=float,
        default=0.001,
        help='Initial learning rate.'
    )
    parser.add_argument(
        '--num_epoch',
        type=int,
        default=500,
        help='Number of epochs to train.'
    )
    parser.add_argument(
        '--batch_size',
        type=int,
        default=256,
        help='Batch size. Must divide evenly into the dataset sizes.'
    )
    parser.add_argument(
        '--dataset_path',
        type=str,
        default='data/davis/',
        help='Directory for input data.'
    )
    parser.add_argument(
        '--problem_type',
        type=int,
        default=1,
        help='Type of the prediction problem (1-4)'
    )
    parser.add_argument(
        '--binary_th',
        type=float,
        default=0.0,
        help='Threshold to split data into binary classes'
    )
    parser.add_argument(
        '--is_log',
        type=int,
        default=0,
        help='use log transformation for Y'
    )
    parser.add_argument(
        '--checkpoint_path',
        type=str,
        default='',
        help='Path to write checkpoint file.'
    )
    parser.add_argument(
        '--log_dir',
        type=str,
        default='loggg/tmp',
        help='Directory for log data.'
    )

    FLAGS, unparsed = parser.parse_known_args()

    # check validity
    # assert( len(FLAGS.window_lengths) == len(FLAGS.num_windows) )

    return FLAGS


def logging(msg, FLAGS):
    fpath = os.path.join(FLAGS.log_dir, "log.txt")
    with open(fpath, "a") as fw:
        fw.write("%s\n" % msg)
    # print(msg)