50 lines
1.6 KiB
YAML
50 lines
1.6 KiB
YAML
process_dir: processed # directory for torch geometric processed dataset
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cache_dir: cache # directory for infinite summation processed files
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checkpoint_dir: checkpoint # directory for checkpoints
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dataset: dft_3d
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# JARVIS dataset: dft_3d
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# MP dataset: megnet
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target: formation_energy_peratom
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# JARVIS dataset entries: formation_energy_peratom, mbj_bandgap, optb88vdw_bandgap, optb88vdw_total_energy, ehull
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# MP dataset entries: e_form, gap pbe
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# If using custom dataset, please set this to the corresponding entry name, e.g., target
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atom_features: cgcnn
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epochs: 2
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batch_size: 64
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num_workers: 8
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weight_decay: 0.0
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learning_rate: 1e-3
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criterion: mse
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optimizer: adamw
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scheduler: onecycle
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pin_memory: False
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write_checkpoint: True
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write_predictions: True
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store_outputs: True
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progress: True
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log_tensorboard: False
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normalize: False # scaling the targets by their mean and std
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euclidean: False # disable infinite summation or not
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cutoff: 4.0 # local graph cutoff
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max_neighbors: 16
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infinite_funcs: ["zeta", "zeta", "exp"]
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infinite_params: [0.5, 3.0, 3.0] # Coulomb, London dispersion, Pauli
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R: 3 # half of the grid length
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model:
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name: potnet
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conv_layers: 3
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rbf_min: -4.0
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rbf_max: 4.0
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potentials: [-0.801, -0.074, 0.145] # coefficients for infinite summations; should be negative, negative, positive w.r.t. their mathematical form
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# potentials: [ -0.703, -0.0617, 0.142 ]
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# potentials: [-0.816, -0.052, 0.149]
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charge_map: False # if including information of periodic table
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transformer: False # enable transformer structure for infinite potential summation; only works when euclidean is False
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