data: root_path: ${oc.env:PROJECT_ROOT}/data/mp_20 prop: formation_energy_per_atom num_targets: 1 properties: - formation_energy_per_atom conditions: - formation_energy_per_atom niggli: true primitive: false graph_method: crystalnn lattice_scale_method: scale_length preprocess_workers: 30 readout: mean max_atoms: 20 otf_graph: false eval_model_name: mp20 tolerance: 0.1 use_space_group: false use_pos_index: false train_max_epochs: 3000 early_stopping_patience: 100000 teacher_forcing_max_epoch: 500 datamodule: _target_: diffcsp.pl_data.datamodule.CrystDataModule datasets: train: _target_: diffcsp.pl_data.dataset.CrystDataset name: Formation energy train path: ${data.root_path}/train.csv save_path: ${data.root_path}/train_ori.pt prop: ${data.prop} properties: ${data.properties} niggli: ${data.niggli} primitive: ${data.primitive} graph_method: ${data.graph_method} tolerance: ${data.tolerance} use_space_group: ${data.use_space_group} use_pos_index: ${data.use_pos_index} lattice_scale_method: ${data.lattice_scale_method} preprocess_workers: ${data.preprocess_workers} val: - _target_: diffcsp.pl_data.dataset.CrystDataset name: Formation energy val path: ${data.root_path}/val.csv save_path: ${data.root_path}/val_ori.pt prop: ${data.prop} properties: ${data.properties} niggli: ${data.niggli} primitive: ${data.primitive} graph_method: ${data.graph_method} tolerance: ${data.tolerance} use_space_group: ${data.use_space_group} use_pos_index: ${data.use_pos_index} lattice_scale_method: ${data.lattice_scale_method} preprocess_workers: ${data.preprocess_workers} test: - _target_: diffcsp.pl_data.dataset.CrystDataset name: Formation energy test path: ${data.root_path}/test.csv save_path: ${data.root_path}/test_ori.pt prop: ${data.prop} properties: ${data.properties} niggli: ${data.niggli} primitive: ${data.primitive} graph_method: ${data.graph_method} tolerance: ${data.tolerance} use_space_group: ${data.use_space_group} use_pos_index: ${data.use_pos_index} lattice_scale_method: ${data.lattice_scale_method} preprocess_workers: ${data.preprocess_workers} num_workers: train: 0 val: 0 test: 0 batch_size: train: 256 val: 128 test: 128 logging: val_check_interval: 1 progress_bar_refresh_rate: 10 wandb: name: ${expname} project: crystalflow-gridtest entity: null log_model: true mode: online group: ${expname} wandb_watch: log: all log_freq: 500 lr_monitor: logging_interval: step log_momentum: false model: decoder: _target_: diffcsp.pl_modules.cspnet.CSPNet hidden_dim: 512 latent_dim: 0 lattice_dim: 6 max_atoms: 100 num_layers: 6 act_fn: silu dis_emb: sin num_freqs: 256 rec_emb: sin num_millers: 8 edge_style: fc max_neighbors: ${model.max_neighbors} cutoff: ${model.radius} ln: true ip: false pred_type: true smooth: ${model.decoder.pred_type} na_emb: 0 beta_scheduler: _target_: diffcsp.pl_modules.diff_utils.BetaScheduler timesteps: ${model.timesteps} scheduler_mode: cosine sigma_scheduler: _target_: diffcsp.pl_modules.diff_utils.SigmaScheduler timesteps: ${model.timesteps} sigma_begin: 0.005 sigma_end: 0.5 conditions: cond_keys: ${data.conditions} types: e_above_hull: _target_: diffcsp.pl_modules.conditioning.ScalarEmbedding prop_name: e_above_hull batch_norm: false no_expansion: false n_basis: 50 start: -2 stop: 2 trainable_gaussians: false no_mlp: true hidden_dim: 128 fc_num_layers: 5 n_out: 128 energy_per_atom: _target_: diffcsp.pl_modules.conditioning.ScalarEmbedding prop_name: energy_per_atom batch_norm: false no_expansion: false n_basis: 50 start: -2 stop: 2 trainable_gaussians: false no_mlp: true hidden_dim: 128 fc_num_layers: 5 n_out: 128 enthalpy_per_atom: _target_: diffcsp.pl_modules.conditioning.ScalarEmbedding prop_name: enthalpy_per_atom batch_norm: false no_expansion: false n_basis: 50 start: -2 stop: 2 trainable_gaussians: false no_mlp: true hidden_dim: 128 fc_num_layers: 5 n_out: 128 energy: _target_: diffcsp.pl_modules.conditioning.ScalarEmbedding prop_name: energy batch_norm: false no_expansion: false n_basis: 50 start: -2 stop: 2 trainable_gaussians: false no_mlp: true hidden_dim: 128 fc_num_layers: 5 n_out: 128 enthalpy: _target_: diffcsp.pl_modules.conditioning.ScalarEmbedding prop_name: enthalpy batch_norm: false no_expansion: false n_basis: 50 start: -2 stop: 2 trainable_gaussians: false no_mlp: true hidden_dim: 128 fc_num_layers: 5 n_out: 128 formation_energy_per_atom: _target_: diffcsp.pl_modules.conditioning.ScalarEmbedding prop_name: formation_energy_per_atom batch_norm: false no_expansion: false n_basis: 50 start: -2 stop: 2 trainable_gaussians: false no_mlp: true hidden_dim: 128 fc_num_layers: 5 n_out: 128 pressure: _target_: diffcsp.pl_modules.conditioning.ScalarEmbedding prop_name: pressure batch_norm: false no_expansion: false n_basis: 50 start: -2 stop: 2 trainable_gaussians: false no_mlp: true hidden_dim: 128 fc_num_layers: 5 n_out: 128 spgno: _target_: diffcsp.pl_modules.conditioning.ScalarEmbedding prop_name: spgno batch_norm: false no_expansion: false n_basis: 50 start: -1 stop: 1 trainable_gaussians: false no_mlp: true hidden_dim: 128 fc_num_layers: 5 n_out: 128 _target_: diffcsp.pl_modules.flow.CSPFlow time_dim: 256 latent_dim: 0 cost_type: 10 cost_coord: 10 cost_lattice: 1 max_neighbors: 20 radius: 7.0 timesteps: 1000 lattice_polar: true type_encoding: table lattice_polar_sigma: 0.1 optim: optimizer: _target_: torch.optim.Adam lr: 0.001 betas: - 0.9 - 0.999 eps: 1.0e-08 weight_decay: 0 use_lr_scheduler: true lr_scheduler: _target_: torch.optim.lr_scheduler.ReduceLROnPlateau factor: 0.6 patience: 30 min_lr: 0.0001 train: deterministic: true random_seed: 42 float32_matmul_precision: medium pl_trainer: fast_dev_run: false devices: 4 accelerator: gpu precision: 32 max_epochs: ${data.train_max_epochs} accumulate_grad_batches: 1 num_sanity_val_steps: 2 gradient_clip_val: 0.5 gradient_clip_algorithm: value strategy: ddp_find_unused_parameters_true monitor_metric: val_loss monitor_metric_mode: min early_stopping: patience: ${data.early_stopping_patience} verbose: false model_checkpoints: save_top_k: 1 verbose: false save_last: false expname: abinit-BS1-LR1-WD1-RF1-K3-LW2-F1-X2-TE4-N1-H1-L1 core: version: 0.0.1 tags: - ${now:%Y-%m-%d}