INNER CODE UNIT · Python
num_nodes
graphdeeplearning/benchmarking-gnns · main_CSL_graph_classification.py:436
num_nodes = num_nodes_train + num_nodes_test
net_params['avg_node_num'] = int(np.ceil(np.mean(num_nodes)))
# RingGNN, 3WLGNN
if MODEL_NAME in ['RingGNN', '3WLGNN']:
if net_params['pos_enc']:
net_params['in_dim'] = net_params['pos_enc_dim']
else:
net_params['in_dim'] = 1
root_log_dir = out_dir + 'logs/' + MODEL_NAME + "_" + DATASET_NAME + "_GPU" + str(config['gpu']['id']) + "_" + time.strftime('%Hh%Mm%Ss_on_%b_%d_%Y')
root_ckpt_dir = out_dir + 'checkpoints/' + MODEL_NAME + "_" + DATASET_NAME + "_GPU" + str(config['gpu']['id']) + "_" + time.strftime('%Hh%Mm%Ss_on_%b_%d_%Y')
write_file_name = out_dir + 'results/result_' + MODEL_NAME + "_" + DATASET_NAME + "_GPU" + str(config['gpu']['id']) + "_" + time.strftime('%Hh%Mm%Ss_on_%b_%d_%Y')
write_config_file = out_dir + 'configs/config_' + MODEL_NAME + "_" + DATASET_NAME + "_GPU" + str(config['gpu']['id']) + "_" + time.strftime('%Hh%Mm%Ss_on_%b_%d_%Y')
dirs = root_log_dir, root_ckpt_dir, write_file_name, write_config_file
if not os.path.exists(out_dir + 'results'):
os.makedirs(out_dir + 'results')