def load_train_data(self):
train_data = model_utils.load_train_data(self.path_dataset)
test_bgs_data = model_utils.load_test_bgs_data(self.path_dataset)
factor = -1 * np.log(0.01)
norm_train_data = model_utils.normalize(train_data, factor)
norm_test_bgs_data = model_utils.normalize(test_bgs_data, factor)
return norm_train_data, norm_test_bgs_data
def load_train_data(self):
train_data = model_utils.load_train_data(self.path_dataset)
test_bgs_data = model_utils.load_test_bgs_data(self.path_dataset)
train_shape = (self.dataset_config['TRAIN_SIZE'], self.shape)
test_bgs_shape = (self.dataset_config['TEST_BACKGROUND_SIZE'], self.shape)
factor = -1 * np.log(0.01)
norm_train_data = model_utils.normalize(train_data.reshape(train_shape), factor)
norm_test_bgs_data = model_utils.normalize(test_bgs_data.reshape(test_bgs_shape), factor)
return norm_train_data, norm_test_bgs_data