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ACEsuit / mace

MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.
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some parameters are `None` in foundation branch #361

Closed jungsdao closed 4 weeks ago

jungsdao commented 6 months ago

Describe the bug When I train model with foundation model branch, some of inherited parameters are given as None in the train logfile. For example, num_channels=None and max_L=None. I guess these parameters are from foundation model but not properly displayed.
folowing is part of training logfile. 

2024-03-14 13:56:04.855 INFO: Configuration: Namespace(name='umbrella', seed=123, log_dir='logs', model_dir='.', checkpoints_dir='checkpoints', results_    dir='results', downloads_dir='downloads', device='cuda', default_dtype='float64', log_level='INFO', error_table='PerAtomMAE', model='MACE', r_max=6.0, r    adial_type='bessel', num_radial_basis=8, num_cutoff_basis=5, pair_repulsion=False, distance_transform=False, interaction='RealAgnosticResidualInteractio    nBlock', interaction_first='RealAgnosticResidualInteractionBlock', max_ell=3, correlation=3, num_interactions=2, MLP_irreps='16x0e', radial_MLP='[64, 64    , 64]', hidden_irreps='128x0e + 128x1o', num_channels=None, max_L=None, gate='silu', scaling='rms_forces_scaling', avg_num_neighbors=1, compute_avg_num_    neighbors=True, compute_stress=False, compute_forces=True, train_file='/work/home/hjung/Calculation/4_Free_energy_calculation/1_Rh/2_CHO_foundation/MACE    /training_14.xyz', valid_file=None, valid_fraction=0.1, test_file=None, E0s='{1: -14.9005442054276, 6: -162.973421385767, 8: -438.578998764142, 45: -308    9.70420527816}', energy_key='DFT_energy', forces_key='DFT_forces', virials_key='virials', stress_key='stress', dipole_key='dipole', charges_key='charges    ', loss='weighted', forces_weight=10.0, swa_forces_weight=100.0, energy_weight=1.0, swa_energy_weight=1000.0, virials_weight=1.0, swa_virials_weight=10.    0, stress_weight=1.0, swa_stress_weight=10.0, dipole_weight=1.0, swa_dipole_weight=1.0, config_type_weights='{"Default":1.0}', huber_delta=0.01, optimiz    er='adam', batch_size=2, valid_batch_size=1, lr=0.01, swa_lr=0.001, weight_decay=5e-07, amsgrad=True, scheduler='ReduceLROnPlateau', lr_factor=0.8, sche    duler_patience=15, lr_scheduler_gamma=0.9993, swa=True, start_swa=4050, ema=True, ema_decay=0.99, max_num_epochs=4200, patience=30, foundation_model='me    dium', foundation_model_readout=True, eval_interval=4, keep_checkpoints=False, restart_latest=True, save_cpu=True, clip_grad=10.0, wandb=False, wandb_pr    oject='', wandb_entity='', wandb_name='', wandb_log_hypers=['num_channels', 'max_L', 'correlation', 'lr', 'swa_lr', 'weight_decay', 'batch_size', 'max_n    um_epochs', 'start_swa', 'energy_weight', 'forces_weight'])
ilyes319 commented 4 weeks ago

That is fixed in develop now.