def create_data_stream(args):
print(args)
sw = StopWatch()
if not args.no_copy:
with sw:
print('Copying data to local machine...')
rsync = Rsync(args.tmpdir)
rsync.sync(args.data_path)
args.data_path = os.path.join(args.tmpdir,
os.path.basename(args.data_path))
return fuel_utils.get_datastream(path=args.data_path,
which_set=args.dataset,
batch_size=args.batch_size)
if os.path.exists(reload_path):
print('Previously trained model detected: {}'.format(reload_path))
print('Training continues')
args.reload_model = reload_path
##############
# print args #
##############
print(args)
sw = StopWatch()
if not args.no_copy:
print('Loading data streams from {}'.format(args.data_path))
print('Copying data to local machine...')
rsync = Rsync(args.tmpdir)
rsync.sync(args.data_path)
args.data_path = os.path.join(args.tmpdir,
os.path.basename(args.data_path))
sw.print_elapsed()
####################
# load data stream #
####################
train_datastream = get_datastream(path=args.data_path,
which_set=args.train_dataset,
batch_size=args.batch_size)
valid_datastream = get_datastream(path=args.data_path,
which_set=args.valid_dataset,
batch_size=args.batch_size)
test_datastream = get_datastream(path=args.data_path,
