ADDA.PyTorch-resnet/train_source.py

import argparse
import os

from torch import nn, optim
from torch.utils.data import DataLoader
from torchvision.datasets import SVHN
from torchvision import transforms

from models import CNN
from trainer import train_source_cnn
from utils import get_logger


def main(args):
    if not os.path.exists(args.logdir):
        os.makedirs(args.logdir)
    logger = get_logger(os.path.join(args.logdir, 'train_source.log'))
    logger.info(args)

    # data
    source_transform = transforms.Compose([
        transforms.ToTensor()]
    )
    source_dataset_train = SVHN(
        './input', 'train', transform=source_transform, download=True)
    source_dataset_test = SVHN(
        './input', 'test', transform=source_transform, download=True)
    source_train_loader = DataLoader(
        source_dataset_train, args.batch_size, shuffle=True,
        drop_last=True,
        num_workers=args.n_workers)
    source_test_loader = DataLoader(
        source_dataset_test, args.batch_size, shuffle=False,
        num_workers=args.n_workers)

    # train source CNN
    source_cnn = CNN(in_channels=args.in_channels).to(args.device)
    criterion = nn.CrossEntropyLoss()
    optimizer = optim.Adam(
        source_cnn.parameters(),
        lr=args.lr, weight_decay=args.weight_decay)
    source_cnn = train_source_cnn(
        source_cnn, source_train_loader, source_test_loader,
        criterion, optimizer, args=args)


if __name__ == '__main__':
    parser = argparse.ArgumentParser()
    # NN
    parser.add_argument('--in_channels', type=int, default=3)
    parser.add_argument('--n_classes', type=int, default=10)
    parser.add_argument('--trained', type=str, default='')
    parser.add_argument('--slope', type=float, default=0.2)
    # train
    parser.add_argument('--lr', type=float, default=1e-3)
    parser.add_argument('--weight_decay', type=float, default=2.5e-5)
    parser.add_argument('--epochs', type=int, default=50)
    parser.add_argument('--batch_size', type=int, default=128)
    # misc
    parser.add_argument('--device', type=str, default='cuda:0')
    parser.add_argument('--n_workers', type=int, default=0)
    parser.add_argument('--logdir', type=str, default='outputs/garbage')
    parser.add_argument('--message', '-m',  type=str, default='')
    args, unknown = parser.parse_known_args()
    main(args)