def test_method(gpu):
os.environ["CUDA_VISIBLE_DEVICES"] = gpu
config = TestConfig()
# config.checkpoints_dir = "/media/data2/xyz_data/CelebA_full/full_third_2019-6-19_0.9135_ckp"
print("{} model was initialized".format(config.model_name))
# dataset is test set or val
config.isTest = True
dataset = create_dataset(config=config)
model = create_model(config)
for j in range(0, 102, 1):
config.load_iter = j
model.setup()
model.clear_precision()
if config.eval:
model.eval()
dataset_size = len(dataset)
print("test dataset len: %d " % dataset_size)
total_iter = int(dataset_size / config.batch_size)
model.set_validate_size(dataset_size)
# fc_feature = np.zeros((dataset_size, 2048))
# label = np.zeros((dataset_size, 40))
for i, data in enumerate(dataset):
model.set_input(data)
print("[%s/%s]" % (i, total_iter))
model.test()
print(model.get_model_precision())
print(model.get_model_class_balance_precision())
print("mean accuracy: {}".format(torch.mean(model.get_model_precision())))
print("class_balance accuracy: {}".format(torch.mean(model.get_model_class_balance_precision())))
