torch.backends.cudnn.deterministic = True
if not args.cuda:
args.gpu = -1
if torch.cuda.is_available() and args.cuda:
print('Note: You are using GPU for training')
torch.cuda.set_device(args.gpu)
torch.cuda.manual_seed(args.seed)
if torch.cuda.is_available() and not args.cuda:
print('Warning: You have Cuda but not use it. You are using CPU for training.')
np.random.seed(args.seed)
random.seed(args.seed)
logger = get_logger()
# Set up the data for training SST-1
if args.dataset == 'SST-1':
train_iter, dev_iter, test_iter = SST1.iters(args.data_dir, args.word_vectors_file, args.word_vectors_dir, batch_size=args.batch_size, device=args.gpu, unk_init=UnknownWordVecCache.unk)
# Set up the data for training SST-2
elif args.dataset == 'SST-2':
train_iter, dev_iter, test_iter = SST2.iters(args.data_dir, args.word_vectors_file, args.word_vectors_dir, batch_size=args.batch_size, device=args.gpu, unk_init=UnknownWordVecCache.unk)
elif args.dataset == 'Reuters':
train_iter, dev_iter, test_iter = Reuters.iters(args.data_dir, args.word_vectors_file, args.word_vectors_dir, batch_size=args.batch_size, device=args.gpu, unk_init=UnknownWordVecCache.unk)
else:
raise ValueError('Unrecognized dataset')
config = deepcopy(args)
config.dataset = train_iter.dataset
config.target_class = train_iter.dataset.NUM_CLASSES
config.words_num = len(train_iter.dataset.TEXT_FIELD.vocab)
print('Dataset {} Mode {}'.format(args.dataset, args.mode))
print('VOCAB num',len(train_iter.dataset.TEXT_FIELD.vocab))
print("Note: You are using GPU for training")
torch.cuda.set_device(args.gpu)
torch.cuda.manual_seed(args.seed)
if torch.cuda.is_available() and not args.cuda:
print(
"Warning: You have Cuda but not use it. You are using CPU for training."
)
np.random.seed(args.seed)
random.seed(args.seed)
logger = get_logger()
# Set up the data for training SST-1
if args.dataset == 'SST-1':
train_iter, dev_iter, test_iter = SST1.iters(
args.data_dir,
args.word_vectors_file,
args.word_vectors_dir,
batch_size=args.batch_size,
device=args.gpu)
# Set up the data for training SST-2
elif args.dataset == 'SST-2':
train_iter, dev_iter, test_iter = SST2.iters(
args.data_dir,
args.word_vectors_file,
args.word_vectors_dir,
batch_size=args.batch_size,
device=args.gpu)
else:
raise ValueError('Unrecognized dataset')
config = deepcopy(args)
config.dataset = train_iter.dataset