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=100,

      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/kiba/',

      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='/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)