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