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This commit is contained in:
FilippoOlivo
2025-12-18 09:30:37 +01:00
parent 0a034225ef
commit db50f5ed69
9 changed files with 397 additions and 36 deletions
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9
experiments/10_steps/config_16_layer_16_hidden_adaptive_refined.yaml
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@@ -29,8 +29,8 @@ trainer:
- class_path: ThermalSolver.switch_dataloader_callback.SwitchDataLoaderCallback - class_path: ThermalSolver.switch_dataloader_callback.SwitchDataLoaderCallback
init_args: init_args:
increase_unrolling_steps_by: 4 increase_unrolling_steps_by: 4
patience: 15 patience: 5
last_patience: 20 last_patience: 15
max_unrolling_steps: 10 max_unrolling_steps: 10
ckpt_path: logs.autoregressive.wandb/10_steps/basic.adaptive_refined/16_layer_16_hidden/ ckpt_path: logs.autoregressive.wandb/10_steps/basic.adaptive_refined/16_layer_16_hidden/
max_epochs: 1000 max_epochs: 1000
@@ -58,14 +58,15 @@ data:
class_path: ThermalSolver.graph_datamodule_unsteady.GraphDataModule class_path: ThermalSolver.graph_datamodule_unsteady.GraphDataModule
init_args: init_args:
hf_repo: "SISSAmathLab/thermal-conduction-unsteady" hf_repo: "SISSAmathLab/thermal-conduction-unsteady"
split_name: "3_stripes.basic.adaptive_refined" split_name: "3_stripes.basic.1_adaptive_refined"
n_elements: 100 n_elements: 100
batch_size: 32 batch_size: 24
train_size: 0.7 train_size: 0.7
val_size: 0.2 val_size: 0.2
test_size: 0.1 test_size: 0.1
build_radial_graph: false build_radial_graph: false
remove_boundary_edges: true remove_boundary_edges: true
unrolling_steps: 2 unrolling_steps: 2
min_normalized_diff: 1e-4
optimizer: null optimizer: null
lr_scheduler: null lr_scheduler: null

27
experiments/10_steps/config_16_layer_16_hidden_adaptive_refined_combined.yaml
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@@ -13,24 +13,11 @@ trainer:
project: "thermal-conduction-unsteady-10.steps" project: "thermal-conduction-unsteady-10.steps"
name: "16_layer_16_hidden.adaptive_refined.combined" name: "16_layer_16_hidden.adaptive_refined.combined"
callbacks: callbacks:
# - class_path: lightning.pytorch.callbacks.ModelCheckpoint
# init_args:
# dirpath: logs.autoregressive.wandb/16_refined.10_steps/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: 30
# verbose: false
- class_path: ThermalSolver.switch_dataloader_callback.SwitchDataLoaderCallback - class_path: ThermalSolver.switch_dataloader_callback.SwitchDataLoaderCallback
init_args: init_args:
increase_unrolling_steps_by: 4 increase_unrolling_steps_by: 4
patience: 15 patience: 5
last_patience: 20 last_patience: 10
max_unrolling_steps: 10 max_unrolling_steps: 10
ckpt_path: logs.autoregressive.wandb/10_steps/basic.adaptive_refined.combined/16_layer_16_hidden/ ckpt_path: logs.autoregressive.wandb/10_steps/basic.adaptive_refined.combined/16_layer_16_hidden/
max_epochs: 1000 max_epochs: 1000
@@ -59,16 +46,18 @@ data:
init_args: init_args:
hf_repo: "SISSAmathLab/thermal-conduction-unsteady" hf_repo: "SISSAmathLab/thermal-conduction-unsteady"
split_name: split_name:
- "4_stripes.basic.adaptive_refined" - "4_stripes.basic.1_adaptive_refined"
- "3_stripes.basic.adaptive_refined" - "3_stripes.basic.1_adaptive_refined"
- "2_stripes.basic.adaptive_refined" - "2_stripes.basic.1_adaptive_refined"
n_elements: 100 n_elements: 100
batch_size: 32 batch_size: 24
train_size: 0.7 train_size: 0.7
val_size: 0.2 val_size: 0.2
test_size: 0.1 test_size: 0.1
build_radial_graph: false build_radial_graph: false
remove_boundary_edges: true remove_boundary_edges: true
unrolling_steps: 2 unrolling_steps: 2
min_normalized_diff: 1e-4
optimizer: null optimizer: null
lr_scheduler: null lr_scheduler: null

11
experiments/10_steps/config_16_layer_16_hidden_refined.yaml
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@@ -29,10 +29,10 @@ trainer:
- class_path: ThermalSolver.switch_dataloader_callback.SwitchDataLoaderCallback - class_path: ThermalSolver.switch_dataloader_callback.SwitchDataLoaderCallback
init_args: init_args:
increase_unrolling_steps_by: 4 increase_unrolling_steps_by: 4
patience: 15 patience: 5
last_patience: 20 last_patience: 15
max_unrolling_steps: 10 max_unrolling_steps: 10
ckpt_path: logs.autoregressive.wandb/10_steps/basic.refined.combined/16_layer_16_hidden/ ckpt_path: logs.autoregressive.wandb/10_steps/basic.refined/16_layer_16_hidden/
max_epochs: 1000 max_epochs: 1000
min_epochs: null min_epochs: null
max_steps: -1 max_steps: -1
@@ -59,13 +59,14 @@ data:
init_args: init_args:
hf_repo: "SISSAmathLab/thermal-conduction-unsteady" hf_repo: "SISSAmathLab/thermal-conduction-unsteady"
split_name: "3_stripes.basic.refined" split_name: "3_stripes.basic.refined"
n_elements: 100 n_elements: 50
batch_size: 32 batch_size: 24
train_size: 0.7 train_size: 0.7
val_size: 0.2 val_size: 0.2
test_size: 0.1 test_size: 0.1
build_radial_graph: false build_radial_graph: false
remove_boundary_edges: true remove_boundary_edges: true
unrolling_steps: 2 unrolling_steps: 2
min_normalized_diff: 1e-4
optimizer: null optimizer: null
lr_scheduler: null lr_scheduler: null

17
experiments/10_steps/config_16_layer_16_hidden_refined_combined.yaml
View File

@@ -29,10 +29,10 @@ trainer:
- class_path: ThermalSolver.switch_dataloader_callback.SwitchDataLoaderCallback - class_path: ThermalSolver.switch_dataloader_callback.SwitchDataLoaderCallback
init_args: init_args:
increase_unrolling_steps_by: 4 increase_unrolling_steps_by: 4
patience: 15 patience: 5
last_patience: 20 last_patience: 10
max_unrolling_steps: 10 max_unrolling_steps: 10
ckpt_path: logs.autoregressive.wandb/10_steps/basic.refined/16_layer_16_hidden/ ckpt_path: logs.autoregressive.wandb/10_steps/basic.refined.combined/16_layer_16_hidden/
max_epochs: 1000 max_epochs: 1000
min_epochs: null min_epochs: null
max_steps: -1 max_steps: -1
@@ -52,7 +52,7 @@ model:
hidden_dim: 16 hidden_dim: 16
output_dim: 1 output_dim: 1
n_layers: 16 n_layers: 16
unrolling_steps: 2 unrolling_steps: 10
data: data:
class_path: ThermalSolver.graph_datamodule_unsteady.GraphDataModule class_path: ThermalSolver.graph_datamodule_unsteady.GraphDataModule
@@ -62,13 +62,16 @@ data:
- "4_stripes.basic.refined" - "4_stripes.basic.refined"
- "3_stripes.basic.refined" - "3_stripes.basic.refined"
- "2_stripes.basic.refined" - "2_stripes.basic.refined"
n_elements: 100 n_elements: 75
batch_size: 32 batch_size: 24
train_size: 0.7 train_size: 0.7
val_size: 0.2 val_size: 0.2
test_size: 0.1 test_size: 0.1
build_radial_graph: false build_radial_graph: false
remove_boundary_edges: true remove_boundary_edges: true
unrolling_steps: 2 unrolling_steps: 10
min_normalized_diff: 1e-4
optimizer: null optimizer: null
lr_scheduler: null lr_scheduler: null
ckpt_path: logs.autoregressive.wandb/10_steps/basic.refined.combined/16_layer_16_hidden/6_unrolling_best_checkpoint.ckpt

72
experiments/10_steps/config_16_layer_16_hidden_refined_star.yaml Normal file
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@@ -0,0 +1,72 @@
# 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-10.steps"
name: "16_layer_16_hidden.refined.star"
callbacks:
# - class_path: lightning.pytorch.callbacks.ModelCheckpoint
# init_args:
# dirpath: logs.autoregressive.wandb/16_refined.10_steps/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: 30
# verbose: false
- class_path: ThermalSolver.switch_dataloader_callback.SwitchDataLoaderCallback
init_args:
increase_unrolling_steps_by: 4
patience: 5
last_patience: 15
max_unrolling_steps: 10
ckpt_path: logs.autoregressive.wandb/10_steps/basic.refined.star/16_layer_16_hidden/
max_epochs: 1000
min_epochs: null
max_steps: -1
min_steps: null
overfit_batches: 0.0
log_every_n_steps: 0
accumulate_grad_batches: 1
default_root_dir: null
gradient_clip_val: 1.0
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: 2
data:
class_path: ThermalSolver.graph_datamodule_unsteady.GraphDataModule
init_args:
hf_repo: "SISSAmathLab/thermal-conduction-unsteady"
split_name: "3_stripes.star"
n_elements: 100
batch_size: 24
train_size: 0.7
val_size: 0.2
test_size: 0.1
build_radial_graph: false
remove_boundary_edges: true
unrolling_steps: 2
min_normalized_diff: 1e-4
optimizer: null
lr_scheduler: null

72
experiments/10_steps/config_16_layer_16_hidden_star.yaml Normal file
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@@ -0,0 +1,72 @@
# 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-10.steps"
name: "16_layer_16_hidden.star"
callbacks:
# - class_path: lightning.pytorch.callbacks.ModelCheckpoint
# init_args:
# dirpath: logs.autoregressive.wandb/16_refined.10_steps/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: 30
# verbose: false
- class_path: ThermalSolver.switch_dataloader_callback.SwitchDataLoaderCallback
init_args:
increase_unrolling_steps_by: 4
patience: 5
last_patience: 15
max_unrolling_steps: 10
ckpt_path: logs.autoregressive.wandb/10_steps/basic.star/16_layer_16_hidden/
max_epochs: 1000
min_epochs: null
max_steps: -1
min_steps: null
overfit_batches: 0.0
log_every_n_steps: 0
accumulate_grad_batches: 1
default_root_dir: null
gradient_clip_val: 1.0
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: 2
data:
class_path: ThermalSolver.graph_datamodule_unsteady.GraphDataModule
init_args:
hf_repo: "SISSAmathLab/thermal-conduction-unsteady"
split_name: "3_stripes.star.refined"
n_elements: 100
batch_size: 24
train_size: 0.7
val_size: 0.2
test_size: 0.1
build_radial_graph: false
remove_boundary_edges: true
unrolling_steps: 2
min_normalized_diff: 1e-4
optimizer: null
lr_scheduler: null

75
experiments/10_steps/config_16_layer_16_hidden_star_combined.yaml Normal file
View File

@@ -0,0 +1,75 @@
# 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-10.steps"
name: "16_layer_16_hidden.star.combined"
callbacks:
# - class_path: lightning.pytorch.callbacks.ModelCheckpoint
# init_args:
# dirpath: logs.autoregressive.wandb/16_refined.10_steps/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: 30
# verbose: false
- class_path: ThermalSolver.switch_dataloader_callback.SwitchDataLoaderCallback
init_args:
increase_unrolling_steps_by: 4
patience: 5
last_patience: 15
max_unrolling_steps: 10
ckpt_path: logs.autoregressive.wandb/10_steps/basic.star.combined/16_layer_16_hidden/
max_epochs: 1000
min_epochs: null
max_steps: -1
min_steps: null
overfit_batches: 0.0
log_every_n_steps: 0
accumulate_grad_batches: 1
default_root_dir: null
gradient_clip_val: 1.0
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: 2
data:
class_path: ThermalSolver.graph_datamodule_unsteady.GraphDataModule
init_args:
hf_repo: "SISSAmathLab/thermal-conduction-unsteady"
split_name:
- "4_stripes.star"
- "3_stripes.star"
- "2_stripes.star"
n_elements: 100
batch_size: 24
train_size: 0.7
val_size: 0.2
test_size: 0.1
build_radial_graph: false
remove_boundary_edges: true
unrolling_steps: 2
min_normalized_diff: 1e-4
optimizer: null
lr_scheduler: null

72
experiments/10_steps/config_8_layer_16_hidden_star.yaml Normal file
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@@ -0,0 +1,72 @@
# 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-10.steps"
name: "8_layer_16_hidden.star"
callbacks:
# - class_path: lightning.pytorch.callbacks.ModelCheckpoint
# init_args:
# dirpath: logs.autoregressive.wandb/16_refined.10_steps/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: 30
# verbose: false
- class_path: ThermalSolver.switch_dataloader_callback.SwitchDataLoaderCallback
init_args:
increase_unrolling_steps_by: 4
patience: 5
last_patience: 15
max_unrolling_steps: 10
ckpt_path: logs.autoregressive.wandb/10_steps/basic.star/8_layer_16_hidden/
max_epochs: 1000
min_epochs: null
max_steps: -1
min_steps: null
overfit_batches: 0.0
log_every_n_steps: 0
accumulate_grad_batches: 1
default_root_dir: null
gradient_clip_val: 1.0
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: 2
data:
class_path: ThermalSolver.graph_datamodule_unsteady.GraphDataModule
init_args:
hf_repo: "SISSAmathLab/thermal-conduction-unsteady"
split_name: "3_stripes.star.refined"
n_elements: 100
batch_size: 24
train_size: 0.7
val_size: 0.2
test_size: 0.1
build_radial_graph: false
remove_boundary_edges: true
unrolling_steps: 2
min_normalized_diff: 1e-4
optimizer: null
lr_scheduler: null

76
experiments/10_steps/test_config_16_layer_16_hidden_star.yaml Normal file
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@@ -0,0 +1,76 @@
# lightning.pytorch==2.5.5
seed_everything: 1999
trainer:
accelerator: cpu
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-10.steps"
# name: "16_layer_16_hidden.adaptive_refined.combined"
# callbacks:
# - class_path: lightning.pytorch.callbacks.ModelCheckpoint
# init_args:
# dirpath: logs.autoregressive.wandb/16_refined.10_steps/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: 30
# verbose: false
# - class_path: ThermalSolver.switch_dataloader_callback.SwitchDataLoaderCallback
# init_args:
# increase_unrolling_steps_by: 4
# patience: 15
# last_patience: 20
# max_unrolling_steps: 10
# ckpt_path: logs.autoregressive.wandb/10_steps/basic.adaptive_refined.combined/16_layer_16_hidden/
max_epochs: 1000
min_epochs: null
max_steps: -1
min_steps: null
overfit_batches: 0.0
log_every_n_steps: 0
accumulate_grad_batches: 1
default_root_dir: null
gradient_clip_val: 1.0
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: 2
data:
class_path: ThermalSolver.graph_datamodule_unsteady.GraphDataModule
init_args:
hf_repo: "SISSAmathLab/thermal-conduction-unsteady"
split_name:
# - "2_stripes.basic.refined"
# - "3_stripes.basic.refined"
# - "4_stripes.basic.1_adaptive_refined"
- "3_stripes.star"
n_elements: 50
batch_size: 32
train_size: 0.7
val_size: 0.2
test_size: 0.1
build_radial_graph: false
remove_boundary_edges: true
unrolling_steps: 2
optimizer: null
lr_scheduler: null
ckpt_path: /home/folivo/storage/thermal-conduction-ml/logs.autoregressive.wandb/10_steps/basic.star.combined/16_layer_16_hidden/10_unrolling_best_checkpoint.ckpt