# Ready made graphs created as follows python -m neural_lam.create_global_graph \ --config_path sample_data/global_ocean_1.yaml \ --name global_cluster_graph \ --type cluster \ --plot \ --levels 2 \ --grid_to_first_mesh_refinement 5 \ --connect_disconnected # ================================================== # Graph statistics # ================================================== # m2m (level 0): 8456 nodes, 48546 edges # m2m (level 1): 2097 nodes, 11640 edges # m2m (total): 10553 nodes, 60186 edges # mesh_up (level 0->1): 8456 edges # mesh_down (level 1->0): 8456 edges # g2m: 50804 nodes, 70640 edges # m2g: 50804 nodes, 126107 edges # ================================================== python -m neural_lam.create_global_graph \ --config_path sample_data/global_ocean_1.yaml \ --name global_hierarchical_graph \ --type hierarchical \ --plot \ --levels 2 \ --connect_disconnected \ --splits 5 # ================================================== # Graph statistics # ================================================== # m2m (level 0): 7193 nodes, 40638 edges # m2m (level 1): 1812 nodes, 9860 edges # m2m (total): 9005 nodes, 50498 edges # mesh_up (level 0->1): 7193 edges # mesh_down (level 1->0): 7193 edges # g2m: 49541 nodes, 67147 edges # m2g: 49541 nodes, 125603 edges # ================================================== # SeaCast training python -m neural_lam.train_model \ --config_path sample_data/global_ocean_1.yaml \ --num_workers 1 \ --precision bf16-mixed \ --model graph_fm \ --graph global_hierarchical_graph \ --hidden_dim 16 \ --hidden_dim_grid 8 \ --hidden_dim_mesh_nodes 8 \ --hidden_dim_edge 4 \ --processor_layers 3 \ --batch_size 1 \ --lr 0.001 \ --ar_steps_eval 2 \ --val_steps_to_log 1 2 \ --num_sanity_val_steps 0 \ --num_nodes 1 # Njord training python -m neural_lam.train_model \ --config_path sample_data/global_ocean_1.yaml \ --num_workers 1 \ --precision bf16-mixed \ --model graph_efm \ --graph global_cluster_graph \ --hidden_dim 16 \ --hidden_dim_grid 8 \ --hidden_dim_mesh_nodes 8 \ --hidden_dim_edge 4 \ --processor_layers 3 \ --batch_size 1 \ --epochs 10 \ --lr 0.001 \ --kl_beta 0 \ --num_sanity_val_steps 0 \ --ar_steps_train 1 \ --ar_steps_eval 2 \ --val_steps_to_log 1 2 \ --var_leads_val_plot '{"0":[1,2], "1":[1,2], "2":[1,2], "3":[1,2], "9":[1,2], "15":[1,2]}'