if save_output:
for f in os.listdir(exp_dir):
if 'exp_stdout.txt' in f:
os.remove(exp_dir + f)
write_to_file = exp_dir + 'exp_stdout.txt'
###########################################################################################
###########################################################################################
# LOAD DATA
if args.dataset == 'clevr':
# # CLEVR DATA
dataset = load_clevr(batch_size=args.batch_size,
vws=args.vws,
quick=args.quick)
elif args.dataset == 'cifar':
# CIFAR DATA
# train_image_dataset = load_cifar(data_dir=args.data_dir)
dataset = load_cifar(data_dir=home + '/Documents/')
print(len(dataset), dataset[0].shape)
###########################################################################################
###########################################################################################
# Init Model
# ------------------------------------------------------------------------------
sampling_batch_size = 64
shape = dataset[0].shape
write_to_file = exp_dir + 'exp_stdout.txt'
###########################################################################################
###########################################################################################
# LOAD DATA
print('\nLoading Data')
if args.dataset == 'clevr':
# # CLEVR DATA
if args.machine in ['vws', 'vector', 'vaughn']:
data_dir = home + "/vl_data/two_objects_large/" #vws
else:
data_dir = home + "/VL/data/two_objects_no_occ/" #boltz
train_x, test_x = load_clevr(batch_size=args.batch_size,
data_dir=data_dir,
quick=args.quick)
shape = train_x[0].shape
elif args.dataset == 'cifar':
# CIFAR DATA
# train_image_dataset = load_cifar(data_dir=args.data_dir)
train_x, test_x = load_cifar(data_dir=home + '/Documents/',
dataset_size=args.dataset_size)
shape = train_x[0].shape
# print (len(test_x), 'test set len')
svhn_test_x = load_svhn(data_dir=home + '/Documents/')
# svhn_test_x = test_x
# dataset = train_x