Beispiel #1
0
    outputdir = args.outputdir

    embedding = ''
    if args.embedding == 'random':
        embedding = 'random'
    else:
        embedding = args.embedding

    model_name = args.model
    print(model_name)

    x = import_module('models.' + model_name)
    config = Config(dataset, outputdir, embedding)

    # reset config
    config.model_name = args.model
    config.save_path = os.path.join(outputdir, args.model + '.ckpt')
    config.log_path = os.path.join(outputdir, args.model + '.log')
    config.dropout = float(args.dropout)
    config.require_improvement = int(args.require_improvement)
    config.num_epochs = int(args.num_epochs)
    config.batch_size = int(args.batch_size)
    config.max_length = int(args.max_length)
    config.learning_rate = float(args.learning_rate)
    config.embed = int(args.embed_dim)
    config.bucket = int(args.bucket)
    config.wordNgrams = int(args.wordNgrams)
    config.lr_decay_rate = float(args.lr_decay_rate)

    start_time = time.time()
    print("Loading data...")