add experiments

experiments/config.yaml

@@ -1,56 +0,0 @@
-# lightning.pytorch==2.5.5
-seed_everything: 1999
-trainer:
-  accelerator: gpu
-  strategy: auto
-  devices: 1
-  num_nodes: 1
-  precision: null
-  logger: null
-  callbacks:
-    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
-      init_args:
-        monitor: val/loss
-        mode: min
-        save_top_k: 1
-        filename: best-checkpoint
-    - class_path: lightning.pytorch.callbacks.EarlyStopping
-      init_args:
-        monitor: val/loss
-        mode: min
-        patience: 10
-        verbose: false
-  max_epochs: 2000
-  min_epochs: null
-  max_steps: -1
-  min_steps: null
-  overfit_batches: 0.0
-  log_every_n_steps: null
-  inference_mode: true
-  default_root_dir: null
-  accumulate_grad_batches: 2
-  gradient_clip_val: 1.0
-model: 
-  class_path: ThermalSolver.module.GraphSolver
-  init_args:
-    model_class_path: ThermalSolver.model.local_gno.GatingGNO
-    model_init_args:
-      x_ch_node: 1 
-      f_ch_node: 1 
-      hidden: 16
-      layers: 1
-      edge_ch: 3 
-      out_ch: 1
-    unrolling_steps: 64
-data: 
-  class_path: ThermalSolver.data_module.GraphDataModule
-  init_args:
-    hf_repo: "SISSAmathLab/thermal-conduction"
-    split_name: "2000_ref_1"
-    batch_size: 10
-    train_size: 0.8
-    test_size: 0.1
-    test_size: 0.1
-optimizer: null
-lr_scheduler: null
-ckpt_path: null

experiments/config_01.yaml

@@ -1,56 +0,0 @@
-# lightning.pytorch==2.5.5
-seed_everything: 1999
-trainer:
-  accelerator: gpu
-  strategy: auto
-  devices: 1
-  num_nodes: 1
-  precision: null
-  logger:
-    - class_path: lightning.pytorch.loggers.TensorBoardLogger
-      init_args:
-        save_dir: logs
-        name: "test"
-        version: null
-  callbacks:
-    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
-      init_args:
-        monitor: val/loss
-        mode: min
-        save_top_k: 1
-        filename: best-checkpoint
-    - class_path: lightning.pytorch.callbacks.EarlyStopping
-      init_args:
-        monitor: val/loss
-        mode: min
-        patience: 15
-        verbose: false
-  max_epochs: 1000
-  min_epochs: null
-  max_steps: -1
-  min_steps: null
-  overfit_batches: 0.0
-  log_every_n_steps: null
-  inference_mode: true
-  default_root_dir: null
-  accumulate_grad_batches: 4
-  gradient_clip_val: 1.0
-model: 
-  class_path: ThermalSolver.graph_module.GraphSolver
-  init_args:
-    model_class_path: ThermalSolver.model.LearnableGraphFiniteDifference
-    model_init_args:
-      max_iters: 250
-    unrolling_steps: 64
-data: 
-  class_path: ThermalSolver.graph_datamodule.GraphDataModule
-  init_args:
-    hf_repo: "SISSAmathLab/thermal-conduction"
-    split_name: "1000_40x30"
-    batch_size: 8
-    train_size: 0.8
-    test_size: 0.1
-    test_size: 0.1
-optimizer: null
-lr_scheduler: null
-# ckpt_path: lightning_logs/01/version_0/checkpoints/best-checkpoint.ckpt

experiments/config_02.yaml

@@ -1,62 +0,0 @@
-# lightning.pytorch==2.5.5
-seed_everything: 1999
-trainer:
-  accelerator: gpu
-  strategy: auto
-  devices: 1
-  num_nodes: 1
-  precision: null
-  logger:
-    - class_path: lightning.pytorch.loggers.TensorBoardLogger
-      init_args:
-        save_dir: lightning_logs
-        name: "02"
-        version: null
-  callbacks:
-    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
-      init_args:
-        monitor: val/loss
-        mode: min
-        save_top_k: 1
-        filename: best-checkpoint
-    - class_path: lightning.pytorch.callbacks.EarlyStopping
-      init_args:
-        monitor: val/loss
-        mode: min
-        patience: 10
-        verbose: false
-  max_epochs: 200
-  min_epochs: null
-  max_steps: -1
-  min_steps: null
-  overfit_batches: 0.0
-  log_every_n_steps: null
-  inference_mode: true
-  default_root_dir: null
-  accumulate_grad_batches: 6
-  gradient_clip_val: 1.0
-model: 
-  class_path: ThermalSolver.module.GraphSolver
-  init_args:
-    model_class_path: ThermalSolver.model.local_gno.GatingGNO
-    model_init_args:
-      x_ch_node: 1 
-      f_ch_node: 1 
-      hidden: 16
-      layers: 2
-      edge_ch: 3 
-      out_ch: 1
-    unrolling_steps: 32
-data: 
-  class_path: ThermalSolver.data_module.GraphDataModule
-  init_args:
-    hf_repo: "SISSAmathLab/thermal-conduction"
-    split_name: "2000_ref_1"
-    batch_size: 4
-    train_size: 0.8
-    test_size: 0.1
-    test_size: 0.1
-optimizer: null
-lr_scheduler: null
-# ckpt_path: lightning_logs/version_15/checkpoints/best-checkpoint.ckpt
-ckpt_path: null

experiments/config_04.yaml

@@ -1,62 +0,0 @@
-# lightning.pytorch==2.5.5
-seed_everything: 1999
-trainer:
-  accelerator: gpu
-  strategy: auto
-  devices: 1
-  num_nodes: 1
-  precision: null
-  logger:
-    - class_path: lightning.pytorch.loggers.TensorBoardLogger
-      init_args:
-        save_dir: lightning_logs
-        name: "04"
-        version: null
-  callbacks:
-    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
-      init_args:
-        monitor: val/loss
-        mode: min
-        save_top_k: 1
-        filename: best-checkpoint
-    - class_path: lightning.pytorch.callbacks.EarlyStopping
-      init_args:
-        monitor: val/loss
-        mode: min
-        patience: 10
-        verbose: false
-  max_epochs: 200
-  min_epochs: null
-  max_steps: -1
-  min_steps: null
-  overfit_batches: 0.0
-  log_every_n_steps: null
-  inference_mode: true
-  default_root_dir: null
-  accumulate_grad_batches: 6
-  gradient_clip_val: 1.0
-model: 
-  class_path: ThermalSolver.module.GraphSolver
-  init_args:
-    model_class_path: ThermalSolver.model.local_gno.GatingGNO
-    model_init_args:
-      x_ch_node: 1 
-      f_ch_node: 1 
-      hidden: 16
-      layers: 4
-      edge_ch: 3 
-      out_ch: 1
-    unrolling_steps: 16
-data: 
-  class_path: ThermalSolver.data_module.GraphDataModule
-  init_args:
-    hf_repo: "SISSAmathLab/thermal-conduction"
-    split_name: "2000_ref_1"
-    batch_size: 4
-    train_size: 0.8
-    test_size: 0.1
-    test_size: 0.1
-optimizer: null
-lr_scheduler: null
-# ckpt_path: lightning_logs/version_15/checkpoints/best-checkpoint.ckpt
-ckpt_path: null

experiments/config_08.yaml

@@ -1,62 +0,0 @@
-# lightning.pytorch==2.5.5
-seed_everything: 1999
-trainer:
-  accelerator: gpu
-  strategy: auto
-  devices: 1
-  num_nodes: 1
-  precision: null
-  logger:
-    - class_path: lightning.pytorch.loggers.TensorBoardLogger
-      init_args:
-        save_dir: lightning_logs
-        name: "08"
-        version: null
-  callbacks:
-    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
-      init_args:
-        monitor: val/loss
-        mode: min
-        save_top_k: 1
-        filename: best-checkpoint
-    - class_path: lightning.pytorch.callbacks.EarlyStopping
-      init_args:
-        monitor: val/loss
-        mode: min
-        patience: 10
-        verbose: false
-  max_epochs: 200
-  min_epochs: null
-  max_steps: -1
-  min_steps: null
-  overfit_batches: 0.0
-  log_every_n_steps: null
-  inference_mode: true
-  default_root_dir: null
-  accumulate_grad_batches: 6
-  gradient_clip_val: 1.0
-model: 
-  class_path: ThermalSolver.module.GraphSolver
-  init_args:
-    model_class_path: ThermalSolver.model.local_gno.GatingGNO
-    model_init_args:
-      x_ch_node: 1 
-      f_ch_node: 1 
-      hidden: 16
-      layers: 8
-      edge_ch: 3 
-      out_ch: 1
-    unrolling_steps: 8
-data: 
-  class_path: ThermalSolver.data_module.GraphDataModule
-  init_args:
-    hf_repo: "SISSAmathLab/thermal-conduction"
-    split_name: "2000_ref_1"
-    batch_size: 4
-    train_size: 0.8
-    test_size: 0.1
-    test_size: 0.1
-optimizer: null
-lr_scheduler: null
-# ckpt_path: lightning_logs/version_15/checkpoints/best-checkpoint.ckpt
-ckpt_path: null

experiments/config_16.yaml

@@ -1,62 +0,0 @@
-# lightning.pytorch==2.5.5
-seed_everything: 1999
-trainer:
-  accelerator: gpu
-  strategy: auto
-  devices: 1
-  num_nodes: 1
-  precision: null
-  logger:
-    - class_path: lightning.pytorch.loggers.TensorBoardLogger
-      init_args:
-        save_dir: lightning_logs
-        name: "16"
-        version: null
-  callbacks:
-    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
-      init_args:
-        monitor: val/loss
-        mode: min
-        save_top_k: 1
-        filename: best-checkpoint
-    - class_path: lightning.pytorch.callbacks.EarlyStopping
-      init_args:
-        monitor: val/loss
-        mode: min
-        patience: 10
-        verbose: false
-  max_epochs: 200
-  min_epochs: null
-  max_steps: -1
-  min_steps: null
-  overfit_batches: 0.0
-  log_every_n_steps: null
-  inference_mode: true
-  default_root_dir: null
-  accumulate_grad_batches: 6
-  gradient_clip_val: 1.0
-model: 
-  class_path: ThermalSolver.module.GraphSolver
-  init_args:
-    model_class_path: ThermalSolver.model.local_gno.GatingGNO
-    model_init_args:
-      x_ch_node: 1 
-      f_ch_node: 1 
-      hidden: 16
-      layers: 16
-      edge_ch: 3 
-      out_ch: 1
-    unrolling_steps: 4
-data: 
-  class_path: ThermalSolver.data_module.GraphDataModule
-  init_args:
-    hf_repo: "SISSAmathLab/thermal-conduction"
-    split_name: "2000_ref_1"
-    batch_size: 4
-    train_size: 0.8
-    test_size: 0.1
-    test_size: 0.1
-optimizer: null
-lr_scheduler: null
-# ckpt_path: lightning_logs/version_15/checkpoints/best-checkpoint.ckpt
-ckpt_path: null

experiments/config_16_layer_16_hidden_refined.yaml

@@ -0,0 +1,62 @@
+# lightning.pytorch==2.5.5
+seed_everything: 1999
+trainer:
+  accelerator: gpu
+  strategy: auto
+  devices: 1
+  num_nodes: 1
+  precision: null
+  logger:
+    - class_path: lightning.pytorch.loggers.WandbLogger
+      init_args:
+        save_dir: logs.autoregressive.wandb
+        project: "thermal-conduction-unsteady"
+        name: "16_refined"
+  callbacks:
+    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
+      init_args:
+        dirpath: logs.autoregressive.wandb/16_refined/checkpoints
+        monitor: val/loss
+        mode: min
+        save_top_k: 1
+        filename: best-checkpoint
+    - class_path: lightning.pytorch.callbacks.EarlyStopping
+      init_args:
+        monitor: val/loss
+        mode: min
+        patience: 10
+        verbose: false
+  max_epochs: 1000
+  min_epochs: null
+  max_steps: -1
+  min_steps: null
+  overfit_batches: 0.0
+  log_every_n_steps: null
+  accumulate_grad_batches: 4
+  default_root_dir: null
+
+model: 
+  class_path: ThermalSolver.autoregressive_module.GraphSolver
+  init_args:
+    model_class_path: ThermalSolver.model.diffusion_net.DiffusionNet
+    model_init_args: 
+      input_dim: 1
+      hidden_dim: 16
+      output_dim: 1
+      n_layers: 16
+    unrolling_steps: 5
+
+data: 
+  class_path: ThermalSolver.graph_datamodule_unsteady.GraphDataModule
+  init_args:
+    hf_repo: "SISSAmathLab/thermal-conduction-unsteady"
+    split_name: "100_samples_easy_refined"
+    batch_size: 8
+    train_size: 0.7
+    val_size: 0.2
+    test_size: 0.1
+    build_radial_graph: false
+    remove_boundary_edges: true
+    start_unrolling_steps: 5
+optimizer: null
+lr_scheduler: null

experiments/config_16_layer_8_hidden_refined.yaml

@@ -0,0 +1,62 @@
+# lightning.pytorch==2.5.5
+seed_everything: 1999
+trainer:
+  accelerator: gpu
+  strategy: auto
+  devices: 1
+  num_nodes: 1
+  precision: null
+  logger:
+    - class_path: lightning.pytorch.loggers.WandbLogger
+      init_args:
+        save_dir: logs.autoregressive.wandb
+        project: "thermal-conduction-unsteady"
+        name: "16_8_refined"
+  callbacks:
+    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
+      init_args:
+        dirpath: logs.autoregressive.wandb/16_8_refined/checkpoints
+        monitor: val/loss
+        mode: min
+        save_top_k: 1
+        filename: best-checkpoint
+    - class_path: lightning.pytorch.callbacks.EarlyStopping
+      init_args:
+        monitor: val/loss
+        mode: min
+        patience: 10
+        verbose: false
+  max_epochs: 1000
+  min_epochs: null
+  max_steps: -1
+  min_steps: null
+  overfit_batches: 0.0
+  log_every_n_steps: null
+  accumulate_grad_batches: 2
+  default_root_dir: null
+
+model: 
+  class_path: ThermalSolver.autoregressive_module.GraphSolver
+  init_args:
+    model_class_path: ThermalSolver.model.diffusion_net.DiffusionNet
+    model_init_args: 
+      input_dim: 1
+      hidden_dim: 8
+      output_dim: 1
+      n_layers: 16
+    unrolling_steps: 5
+
+data: 
+  class_path: ThermalSolver.graph_datamodule_unsteady.GraphDataModule
+  init_args:
+    hf_repo: "SISSAmathLab/thermal-conduction-unsteady"
+    split_name: "100_samples_easy_refined"
+    batch_size: 16
+    train_size: 0.7
+    val_size: 0.2
+    test_size: 0.1
+    build_radial_graph: false
+    remove_boundary_edges: true
+    start_unrolling_steps: 5
+optimizer: null
+lr_scheduler: null

experiments/config_32.yaml

@@ -1,62 +0,0 @@
-# lightning.pytorch==2.5.5
-seed_everything: 1999
-trainer:
-  accelerator: gpu
-  strategy: auto
-  devices: 1
-  num_nodes: 1
-  precision: null
-  logger:
-    - class_path: lightning.pytorch.loggers.TensorBoardLogger
-      init_args:
-        save_dir: lightning_logs
-        name: "32"
-        version: null
-  callbacks:
-    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
-      init_args:
-        monitor: val/loss
-        mode: min
-        save_top_k: 1
-        filename: best-checkpoint
-    - class_path: lightning.pytorch.callbacks.EarlyStopping
-      init_args:
-        monitor: val/loss
-        mode: min
-        patience: 10
-        verbose: false
-  max_epochs: 200
-  min_epochs: null
-  max_steps: -1
-  min_steps: null
-  overfit_batches: 0.0
-  log_every_n_steps: null
-  inference_mode: true
-  default_root_dir: null
-  accumulate_grad_batches: 6
-  gradient_clip_val: 1.0
-model: 
-  class_path: ThermalSolver.module.GraphSolver
-  init_args:
-    model_class_path: ThermalSolver.model.local_gno.GatingGNO
-    model_init_args:
-      x_ch_node: 1 
-      f_ch_node: 1 
-      hidden: 16
-      layers: 32
-      edge_ch: 3 
-      out_ch: 1
-    unrolling_steps: 2
-data: 
-  class_path: ThermalSolver.data_module.GraphDataModule
-  init_args:
-    hf_repo: "SISSAmathLab/thermal-conduction"
-    split_name: "2000_ref_1"
-    batch_size: 4
-    train_size: 0.8
-    test_size: 0.1
-    test_size: 0.1
-optimizer: null
-lr_scheduler: null
-# ckpt_path: lightning_logs/version_15/checkpoints/best-checkpoint.ckpt
-ckpt_path: null

experiments/config_4_layer_16_hidden.yaml

@@ -7,14 +7,16 @@ trainer:
   num_nodes: 1
   precision: null
   logger:
-    - class_path: lightning.pytorch.loggers.TensorBoardLogger
+    - class_path: lightning.pytorch.loggers.WandbLogger
       init_args:
-        save_dir: logs.autoregressive
-        name: "test"
-        version: null
+        save_dir: logs.autoregressive.wandb/wandb
+        project: "thermal-conduction-unsteady"
+        name: "5_step_4_layers_16_hidden"
+        #        retain: true
   callbacks:
     - class_path: lightning.pytorch.callbacks.ModelCheckpoint
       init_args:
+        dirpath: logs.autoregressive.wandb/5_step_4_layers_16_hidden/checkpoints
         monitor: val/loss
         mode: min
         save_top_k: 1
@@ -23,7 +25,7 @@ trainer:
       init_args:
         monitor: val/loss
         mode: min
-        patience: 50
+        patience: 10
         verbose: false
   max_epochs: 1000
   min_epochs: null
@@ -31,40 +33,32 @@ trainer:
   min_steps: null
   overfit_batches: 0.0
   log_every_n_steps: null
-  accumulate_grad_batches: 1
-  # reload_dataloaders_every_n_epochs: 1
+  accumulate_grad_batches: 2
   default_root_dir: null
 
 model: 
   class_path: ThermalSolver.autoregressive_module.GraphSolver
   init_args:
-    model_class_path: ThermalSolver.model.learnable_finite_difference.CorrectionNet
+    model_class_path: ThermalSolver.model.diffusion_net.DiffusionNet
     model_init_args: 
       input_dim: 1
-      hidden_dim: 24
-      # output_dim: 1
-      n_layers: 1
-    start_unrolling_steps: 1
-    increase_every: 100000
-    increase_rate: 2
-    max_inference_iters: 300
-    max_unrolling_steps: 40
-    inner_steps: 1
+      hidden_dim: 16
+      output_dim: 1
+      n_layers: 4
+    unrolling_steps: 5
 
 data: 
   class_path: ThermalSolver.graph_datamodule_unsteady.GraphDataModule
   init_args:
     hf_repo: "SISSAmathLab/thermal-conduction-unsteady"
-    split_name: "50_samples_easy"
-    batch_size: 64
-    train_size: 0.02
-    val_size: 0.02
-    test_size: 0.96
+    split_name: "100_samples_easy_refined"
+    batch_size: 32
+    train_size: 0.7
+    val_size: 0.2
+    test_size: 0.1
     build_radial_graph: true
     radius: 0.5
     remove_boundary_edges: true
-    start_unrolling_steps: 1
-
+    start_unrolling_steps: 5
 optimizer: null
 lr_scheduler: null
-# ckpt_path: logs/test/version_0/checkpoints/best-checkpoint.ckpt

experiments/config_4_layer_8_hidden.yaml

@@ -0,0 +1,62 @@
+# lightning.pytorch==2.5.5
+seed_everything: 1999
+trainer:
+  accelerator: gpu
+  strategy: auto
+  devices: 1
+  num_nodes: 1
+  precision: null
+  logger:
+    - class_path: lightning.pytorch.loggers.WandbLogger
+      init_args:
+        save_dir: logs.autoregressive.wandb
+        project: "thermal-conduction-unsteady"
+        name: "5_step_4_layers_8_hidden"
+  callbacks:
+    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
+      init_args:
+        dirpath: logs.autoregressive.wandb/5_step_4_layers_8_hidden_0.7_radius/checkpoints
+        monitor: val/loss
+        mode: min
+        save_top_k: 1
+        filename: best-checkpoint
+    - class_path: lightning.pytorch.callbacks.EarlyStopping
+      init_args:
+        monitor: val/loss
+        mode: min
+        patience: 10
+        verbose: false
+  max_epochs: 1000
+  min_epochs: null
+  max_steps: -1
+  min_steps: null
+  overfit_batches: 0.0
+  log_every_n_steps: null
+  accumulate_grad_batches: 1
+  default_root_dir: null
+
+model: 
+  class_path: ThermalSolver.autoregressive_module.GraphSolver
+  init_args:
+    model_class_path: ThermalSolver.model.diffusion_net.DiffusionNet
+    model_init_args: 
+      input_dim: 1
+      hidden_dim: 8
+      output_dim: 1
+      n_layers: 4
+    unrolling_steps: 5
+
+data: 
+  class_path: ThermalSolver.graph_datamodule_unsteady.GraphDataModule
+  init_args:
+    hf_repo: "SISSAmathLab/thermal-conduction-unsteady"
+    split_name: "100_samples_easy_refined"
+    batch_size: 32
+    train_size: 0.7
+    val_size: 0.2
+    test_size: 0.1
+    build_radial_graph: false
+    remove_boundary_edges: true
+    start_unrolling_steps: 5
+optimizer: null
+lr_scheduler: null

experiments/config_64.yaml

@@ -1,63 +0,0 @@
-# lightning.pytorch==2.5.5
-seed_everything: 1999
-trainer:
-  accelerator: gpu
-  strategy: auto
-  devices: 1
-  num_nodes: 1
-  precision: null
-  logger:
-    - class_path: lightning.pytorch.loggers.TensorBoardLogger
-      init_args:
-        save_dir: lightning_logs
-        name: "64"
-        version: null
-  callbacks:
-    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
-      init_args:
-        monitor: val/loss
-        mode: min
-        save_top_k: 1
-        filename: best-checkpoint
-    - class_path: lightning.pytorch.callbacks.EarlyStopping
-      init_args:
-        monitor: val/loss
-        mode: min
-        patience: 15
-        verbose: false
-  max_epochs: 1000
-  min_epochs: null
-  max_steps: -1
-  min_steps: null
-  overfit_batches: 0.0
-  log_every_n_steps: null
-  inference_mode: true
-  default_root_dir: null
-  accumulate_grad_batches: 2
-  gradient_clip_val: 1.0
-
-model: 
-  class_path: ThermalSolver.graph_module.GraphSolver
-  init_args:
-    model_class_path: ThermalSolver.model.local_gno.GatingGNO
-    model_init_args:
-      x_ch_node: 1 
-      f_ch_node: 1 
-      hidden: 16
-      layers: 64
-      edge_ch: 3 
-      out_ch: 1
-    unrolling_steps: 1
-data: 
-  class_path: ThermalSolver.graph_datamodule.GraphDataModule
-  init_args:
-    hf_repo: "SISSAmathLab/thermal-conduction"
-    split_name: "2000_ref_1"
-    batch_size: 10
-    train_size: 0.8
-    test_size: 0.1
-    test_size: 0.1
-optimizer: null
-lr_scheduler: null
-# ckpt_path: lightning_logs/64/version_0/checkpoints/best-checkpoint.ckpt
-ckpt_path: null

experiments/config_8_layer_16_hidden.yaml

@@ -0,0 +1,62 @@
+# lightning.pytorch==2.5.5
+seed_everything: 1999
+trainer:
+  accelerator: gpu
+  strategy: auto
+  devices: 1
+  num_nodes: 1
+  precision: null
+  logger:
+    - class_path: lightning.pytorch.loggers.WandbLogger
+      init_args:
+        save_dir: logs.autoregressive.wandb
+        project: "thermal-conduction-unsteady"
+        name: "standard"
+  callbacks:
+    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
+      init_args:
+        dirpath: logs.autoregressive.wandb/standard/checkpoints
+        monitor: val/loss
+        mode: min
+        save_top_k: 1
+        filename: best-checkpoint
+    - class_path: lightning.pytorch.callbacks.EarlyStopping
+      init_args:
+        monitor: val/loss
+        mode: min
+        patience: 10
+        verbose: false
+  max_epochs: 1000
+  min_epochs: null
+  max_steps: -1
+  min_steps: null
+  overfit_batches: 0.0
+  log_every_n_steps: null
+  accumulate_grad_batches: 2
+  default_root_dir: null
+
+model: 
+  class_path: ThermalSolver.autoregressive_module.GraphSolver
+  init_args:
+    model_class_path: ThermalSolver.model.diffusion_net.DiffusionNet
+    model_init_args: 
+      input_dim: 1
+      hidden_dim: 16
+      output_dim: 1
+      n_layers: 8
+    unrolling_steps: 5
+
+data: 
+  class_path: ThermalSolver.graph_datamodule_unsteady.GraphDataModule
+  init_args:
+    hf_repo: "SISSAmathLab/thermal-conduction-unsteady"
+    split_name: "100_samples_easy"
+    batch_size: 16
+    train_size: 0.7
+    val_size: 0.2
+    test_size: 0.1
+    build_radial_graph: false
+    remove_boundary_edges: true
+    start_unrolling_steps: 5
+optimizer: null
+lr_scheduler: null

experiments/config_8_layer_16_hidden_refined.yaml

@@ -0,0 +1,62 @@
+# lightning.pytorch==2.5.5
+seed_everything: 1999
+trainer:
+  accelerator: gpu
+  strategy: auto
+  devices: 1
+  num_nodes: 1
+  precision: null
+  logger:
+    - class_path: lightning.pytorch.loggers.WandbLogger
+      init_args:
+        save_dir: logs.autoregressive.wandb
+        project: "thermal-conduction-unsteady"
+        name: "refined"
+  callbacks:
+    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
+      init_args:
+        dirpath: logs.autoregressive.wandb/refined/checkpoints
+        monitor: val/loss
+        mode: min
+        save_top_k: 1
+        filename: best-checkpoint
+    - class_path: lightning.pytorch.callbacks.EarlyStopping
+      init_args:
+        monitor: val/loss
+        mode: min
+        patience: 10
+        verbose: false
+  max_epochs: 1000
+  min_epochs: null
+  max_steps: -1
+  min_steps: null
+  overfit_batches: 0.0
+  log_every_n_steps: null
+  accumulate_grad_batches: 2
+  default_root_dir: null
+
+model: 
+  class_path: ThermalSolver.autoregressive_module.GraphSolver
+  init_args:
+    model_class_path: ThermalSolver.model.diffusion_net.DiffusionNet
+    model_init_args: 
+      input_dim: 1
+      hidden_dim: 16
+      output_dim: 1
+      n_layers: 8
+    unrolling_steps: 5
+
+data: 
+  class_path: ThermalSolver.graph_datamodule_unsteady.GraphDataModule
+  init_args:
+    hf_repo: "SISSAmathLab/thermal-conduction-unsteady"
+    split_name: "100_samples_easy_refined"
+    batch_size: 16
+    train_size: 0.7
+    val_size: 0.2
+    test_size: 0.1
+    build_radial_graph: false
+    remove_boundary_edges: true
+    start_unrolling_steps: 5
+optimizer: null
+lr_scheduler: null

experiments/config_8_layer_8_hidden.yaml

@@ -0,0 +1,62 @@
+# lightning.pytorch==2.5.5
+seed_everything: 1999
+trainer:
+  accelerator: gpu
+  strategy: auto
+  devices: 1
+  num_nodes: 1
+  precision: null
+  logger:
+    - class_path: lightning.pytorch.loggers.WandbLogger
+      init_args:
+        save_dir: logs.autoregressive.wandb
+        project: "thermal-conduction-unsteady"
+        name: "standard"
+  callbacks:
+    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
+      init_args:
+        dirpath: logs.autoregressive.wandb/standard/checkpoints
+        monitor: val/loss
+        mode: min
+        save_top_k: 1
+        filename: best-checkpoint
+    - class_path: lightning.pytorch.callbacks.EarlyStopping
+      init_args:
+        monitor: val/loss
+        mode: min
+        patience: 10
+        verbose: false
+  max_epochs: 1000
+  min_epochs: null
+  max_steps: -1
+  min_steps: null
+  overfit_batches: 0.0
+  log_every_n_steps: null
+  accumulate_grad_batches: 1
+  default_root_dir: null
+
+model: 
+  class_path: ThermalSolver.autoregressive_module.GraphSolver
+  init_args:
+    model_class_path: ThermalSolver.model.diffusion_net.DiffusionNet
+    model_init_args: 
+      input_dim: 1
+      hidden_dim: 8
+      output_dim: 1
+      n_layers: 8
+    unrolling_steps: 5
+
+data: 
+  class_path: ThermalSolver.graph_datamodule_unsteady.GraphDataModule
+  init_args:
+    hf_repo: "SISSAmathLab/thermal-conduction-unsteady"
+    split_name: "100_samples_easy_refined"
+    batch_size: 32
+    train_size: 0.7
+    val_size: 0.2
+    test_size: 0.1
+    build_radial_graph: false
+    remove_boundary_edges: true
+    start_unrolling_steps: 5
+optimizer: null
+lr_scheduler: null

experiments/config_fd.yaml

@@ -1,58 +0,0 @@
-# lightning.pytorch==2.5.5
-seed_everything: 1999
-trainer:
-  accelerator: gpu
-  strategy: auto
-  devices: 1
-  num_nodes: 1
-  precision: null
-  logger:
-    - class_path: lightning.pytorch.loggers.TensorBoardLogger
-      init_args:
-        save_dir: logs
-        name: "fd"
-        version: null
-  callbacks:
-    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
-      init_args:
-        monitor: val/loss
-        mode: min
-        save_top_k: 1
-        filename: best-checkpoint
-    - class_path: lightning.pytorch.callbacks.EarlyStopping
-      init_args:
-        monitor: val/loss
-        mode: min
-        patience: 2
-        verbose: false
-  max_epochs: 1000
-  min_epochs: null
-  max_steps: -1
-  min_steps: null
-  overfit_batches: 0.0
-  log_every_n_steps: null
-  inference_mode: true
-  default_root_dir: null
-  accumulate_grad_batches: 4
-  gradient_clip_val: 1.0
-model: 
-  class_path: ThermalSolver.graph_module.GraphSolver
-  init_args:
-    model_class_path: ThermalSolver.model.GraphFiniteDifference
-    # model_init_args:
-    max_iters: 10000
-    # unrolling_steps: 64
-data: 
-  class_path: ThermalSolver.graph_datamodule.GraphDataModule
-  init_args:
-    hf_repo: "SISSAmathLab/thermal-conduction"
-    split_name: "1000_1_40x30"
-    batch_size: 8
-    train_size: 0.8
-    test_size: 0.1
-    test_size: 0.1
-    # build_radial_graph: true
-    # radius: 1.5
-optimizer: null
-lr_scheduler: null
-# ckpt_path: lightning_logs/01/version_0/checkpoints/best-checkpoint.ckpt

experiments/config_gino.yaml

@@ -1,74 +0,0 @@
-# lightning.pytorch==2.5.5
-seed_everything: 1999
-trainer:
-  accelerator: gpu
-  strategy: auto
-  devices: 1
-  num_nodes: 1
-  precision: null
-  logger:
-    - class_path: lightning.pytorch.loggers.TensorBoardLogger
-      init_args:
-        save_dir: logs
-        name: "test"
-        version: null
-  callbacks:
-    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
-      init_args:
-        monitor: val/loss
-        mode: min
-        save_top_k: 1
-        filename: best-checkpoint
-    - class_path: lightning.pytorch.callbacks.EarlyStopping
-      init_args:
-        monitor: val/loss
-        mode: min
-        patience: 15
-        verbose: false
-  max_epochs: 1000
-  min_epochs: null
-  max_steps: -1
-  min_steps: null
-  overfit_batches: 0.0
-  log_every_n_steps: null
-  inference_mode: true
-  default_root_dir: null
-  # accumulate_grad_batches: 2
-  # gradient_clip_val: 1.0
-model: 
-  class_path: ThermalSolver.graph_module.GraphSolver
-  init_args:
-    model_class_path: neuralop.models import GINO
-    model_init_args:
-      in_channels: 3           # Es: coordinate (x, y, z) + valore della conducibilità k
-      out_channels: 1            # Es: temperatura T
-
-      # Parametri per l'encoder e il decoder GNO
-      gno_coord_features=3,      # Dimensionalità delle coordinate per GNO (es. 3D)
-      gno_n_layers=2,            # Numero di layer GNO nell'encoder e nel decoder
-      gno_hidden_channels=64,    # Canali nascosti per i layer GNO
-
-      # Parametri per il processore FNO
-      fno_n_modes=(16, 16, 16),  # Numero di modi di Fourier per ogni dimensione
-      fno_n_layers=4,            # Numero di layer FNO
-      fno_hidden_channels=64,    # Canali nascosti per i layer FNO
-      
-      # Canali per il lifting e la proiezione
-      lifting_channels=256,      # Dimensione dello spazio latente dopo il lifting iniziale
-      projection_channels=256,   # Dimensione prima della proiezione finale
-      
-      # Padding del dominio per il processore FNO
-      domain_padding=0.05
-    # unrolling_steps: 64
-data: 
-  class_path: ThermalSolver.graph_datamodule.GraphDataModule
-  init_args:
-    hf_repo: "SISSAmathLab/thermal-conduction"
-    split_name: "2000_ref_1"
-    batch_size: 64
-    train_size: 0.8
-    test_size: 0.1
-    test_size: 0.1
-optimizer: null
-lr_scheduler: null
-# ckpt_path: lightning_logs/01/version_0/checkpoints/best-checkpoint.ckpt

experiments/config_gno.yaml

@@ -1,62 +0,0 @@
-# lightning.pytorch==2.5.5
-seed_everything: 1999
-trainer:
-  accelerator: gpu
-  strategy: auto
-  devices: 1
-  num_nodes: 1
-  precision: null
-  logger:
-    - class_path: lightning.pytorch.loggers.TensorBoardLogger
-      init_args:
-        save_dir: logs
-        name: "test"
-        version: null
-  callbacks:
-    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
-      init_args:
-        monitor: val/loss
-        mode: min
-        save_top_k: 1
-        filename: best-checkpoint
-    - class_path: lightning.pytorch.callbacks.EarlyStopping
-      init_args:
-        monitor: val/loss
-        mode: min
-        patience: 25
-        verbose: false
-  max_epochs: 1000
-  min_epochs: null
-  max_steps: -1
-  min_steps: null
-  overfit_batches: 0.0
-  log_every_n_steps: null
-  # inference_mode: true
-  default_root_dir: null
-  # accumulate_grad_batches: 2
-  # gradient_clip_val: 1.0
-model: 
-  class_path: ThermalSolver.graph_module.GraphSolver
-  init_args:
-    model_class_path: ThermalSolver.model.learnable_finite_difference.CorrectionNet
-    curriculum_learning: true
-    start_iters: 5
-    increase_every: 10
-    increase_rate: 2
-    max_iters: 2000
-    accumulation_iters: 160
-data: 
-  class_path: ThermalSolver.graph_datamodule.GraphDataModule
-  init_args:
-    hf_repo: "SISSAmathLab/thermal-conduction"
-    split_name: "1000_1_40x30"
-    batch_size: 32
-    train_size: 0.8
-    test_size: 0.1
-    test_size: 0.1
-    build_radial_graph: false
-    radius: 0.6
-    remove_boundary_edges: false
-optimizer: null
-lr_scheduler: null
-# ckpt_path: logs/test/version_0/checkpoints/best-checkpoint.ckpt

experiments/config_gno_inference.yaml

@@ -1,62 +0,0 @@
-# lightning.pytorch==2.5.5
-seed_everything: 1999
-trainer:
-  accelerator: gpu
-  strategy: auto
-  devices: 1
-  num_nodes: 1
-  precision: null
-  logger:
-    - class_path: lightning.pytorch.loggers.TensorBoardLogger
-      init_args:
-        save_dir: logs_inference
-        name: "test"
-        version: null
-  callbacks:
-    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
-      init_args:
-        monitor: val/loss
-        mode: min
-        save_top_k: 1
-        filename: best-checkpoint
-    - class_path: lightning.pytorch.callbacks.EarlyStopping
-      init_args:
-        monitor: val/loss
-        mode: min
-        patience: 25
-        verbose: false
-  max_epochs: 1000
-  min_epochs: null
-  max_steps: -1
-  min_steps: null
-  overfit_batches: 0.0
-  log_every_n_steps: null
-  # inference_mode: true
-  default_root_dir: null
-  # accumulate_grad_batches: 2
-  # gradient_clip_val: 1.0
-model: 
-  class_path: ThermalSolver.graph_module.GraphSolver
-  init_args:
-    model_class_path: ThermalSolver.model.finite_difference.FiniteDifferenceStep
-    curriculum_learning: true
-    start_iters: 5
-    increase_every: 10
-    increase_rate: 2
-    max_iters: 2000
-    accumulation_iters: 320
-data: 
-  class_path: ThermalSolver.graph_datamodule.GraphDataModule
-  init_args:
-    hf_repo: "SISSAmathLab/thermal-conduction"
-    split_name: "1000_3_40x30"
-    batch_size: 10
-    train_size: 0.8
-    test_size: 0.1
-    test_size: 0.1
-    build_radial_graph: True
-    radius: 1.2
-    remove_boundary_edges: false
-optimizer: null
-lr_scheduler: null
-# ckpt_path: logs/test/version_2/checkpoints/best-checkpoint.ckpt

experiments/config_pointnet.yaml

@@ -1,56 +0,0 @@
-# lightning.pytorch==2.5.5
-seed_everything: 1999
-trainer:
-  accelerator: gpu
-  strategy: auto
-  devices: 1
-  num_nodes: 1
-  precision: null
-  logger:
-      - class_path: lightning.pytorch.loggers.TensorBoardLogger
-        init_args:
-          save_dir: lightning_logs
-          name: "pointnet"
-          version: null
-  callbacks:
-    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
-      init_args:
-        monitor: val/loss
-        mode: min
-        save_top_k: 1
-        filename: best-checkpoint
-    - class_path: lightning.pytorch.callbacks.EarlyStopping
-      init_args:
-        monitor: val/loss
-        mode: min
-        patience: 10
-        verbose: false
-  max_epochs: 200
-  min_epochs: null
-  max_steps: -1
-  min_steps: null
-  overfit_batches: 0.0
-  log_every_n_steps: null
-  inference_mode: true
-  default_root_dir: null
-  accumulate_grad_batches: 2
-  gradient_clip_val: 1.0
-model: 
-  class_path: ThermalSolver.point_module.PointSolver
-  init_args:
-    model_class_path: ThermalSolver.model.point_net.PointNet
-    model_init_args:
-      input_dim: 4
-      output_dim: 1
-data: 
-  class_path: ThermalSolver.point_datamodule.PointDataModule
-  init_args:
-    hf_repo: "SISSAmathLab/thermal-conduction"
-    split_name: "2000"
-    batch_size: 10
-    train_size: 0.8
-    test_size: 0.1
-    test_size: 0.1
-optimizer: null
-lr_scheduler: null
-# ckpt_path: lightning_logs/pointnet/version_0/checkpoints/best-checkpoint.ckpt

submit.sh

@@ -0,0 +1,8 @@
+#!/bin/bash
+# python run.py fit --config experiments/config_4_layer_8_hidden.yaml
+# python run.py fit --config experiments/config_8_layer_8_hidden.yaml
+python run.py fit --config experiments/config_8_layer_16_hidden_refined.yaml 
+python run.py fit --config experiments/config_16_layer_8_hidden_refined.yaml
+python run.py fit --config experiments/config_16_layer_16_hidden_refined.yaml
+python run.py fit --config experiments/config_8_layer_16_hidden.yaml
+# python run.py fit --config experiments/config_4_layer_16_hidden.yaml