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."
)
TEXT = data.Field(lower=True)
RELATION = data.Field(sequential=False)
train, dev, test = SQdataset.splits(TEXT, RELATION)
TEXT.build_vocab(train, dev, test)
RELATION.build_vocab(train, dev)
train_iter = data.Iterator(train,
batch_size=args.batch_size,
device=args.gpu,
train=True,
repeat=False,
sort=False,
shuffle=True)
dev_iter = data.Iterator(dev,
batch_size=args.batch_size,
device=args.gpu,
train=False,
repeat=False,
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."
)
TEXT = data.Field(lower=True)
RELATION = data.Field(sequential=False)
train, dev, test = SQdataset.splits(TEXT, RELATION, args.data_dir)
TEXT.build_vocab(train, dev, test)
RELATION.build_vocab(train, dev)
train_iter = data.Iterator(train,
batch_size=args.batch_size,
device="cuda",
train=True,
repeat=False,
sort=False,
shuffle=True)
dev_iter = data.Iterator(dev,
batch_size=args.batch_size,
device="cuda",
train=False,
repeat=False,