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flowmm_mp20/best.ckpt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:1de375195ae59004b95a8eda3128792ba7159d0fa1e48b0f845b4f1441b0f63a
+size 226237480

flowmm_mp20/hparams.yaml

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+core:
+  version: ${get_flowmm_version:}
+  tags:
+  - ${now:%Y-%m-%d}
+logging:
+  val_check_interval: 5
+  wandb:
+    project: rfmcsp-${model.target_distribution}-${hydra:runtime.choices.data}
+    entity: null
+    log_model: true
+    mode: online
+    group: ${hydra:runtime.choices.model}-${hydra:runtime.choices.vectorfield}-${generate_id:}
+  wandb_watch:
+    log: all
+    log_freq: 500
+  lr_monitor:
+    logging_interval: step
+    log_momentum: false
+optim:
+  optimizer:
+    _target_: torch.optim.AdamW
+    lr: 0.0003
+    weight_decay: 0.0
+  lr_scheduler:
+    _target_: torch.optim.lr_scheduler.CosineAnnealingLR
+    T_max: ${data.train_max_epochs}
+    eta_min: 1.0e-05
+  interval: epoch
+  ema_decay: 0.999
+train:
+  deterministic: warn
+  random_seed: 42
+  pl_trainer:
+    fast_dev_run: false
+    devices: 1
+    accelerator: gpu
+    precision: 32
+    max_epochs: ${data.train_max_epochs}
+    accumulate_grad_batches: 1
+    num_sanity_val_steps: 1
+    gradient_clip_val: 0.5
+    gradient_clip_algorithm: value
+    profiler: simple
+  monitor_metric: val/loss
+  monitor_metric_mode: min
+  model_checkpoints:
+    save_top_k: 1
+    verbose: false
+    save_last: false
+  every_n_epochs_checkpoint:
+    every_n_epochs: 100
+    save_top_k: -1
+    verbose: false
+    save_last: false
+val:
+  compute_nll: false
+test:
+  compute_nll: false
+  compute_loss: true
+integrate:
+  div_mode: rademacher
+  method: euler
+  num_steps: 1000
+  normalize_loglik: true
+  inference_anneal_slope: 0.0
+  inference_anneal_offset: 0.0
+base_distribution_from_data: false
+data:
+  dataset_name: mp_20
+  dim_coords: 3
+  root_path: ${oc.env:PROJECT_ROOT}/data/mp_20
+  prop: formation_energy_per_atom
+  num_targets: 1
+  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: 2000
+  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}
+        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}
+        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}
+        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: 40
+      val: 40
+      test: 40
+    batch_size:
+      train: 256
+      val: 1024
+      test: 512
+model:
+  cost_coord: 400.0
+  cost_lattice: 1.0
+  cost_type: 40.0
+  cost_cross_ent: 0.0
+  affine_combine_costs: true
+  target_distribution: unconditional
+  self_cond: false
+  manifold_getter:
+    atom_type_manifold: analog_bits
+    coord_manifold: flat_torus_01
+    lattice_manifold: lattice_params
+    analog_bits_scale: 1.0
+    length_inner_coef: 1.0
+vectorfield:
+  _target_: flowmm.model.arch.CSPNet
+  hidden_dim: 512
+  time_dim: 256
+  num_layers: 6
+  act_fn: silu
+  dis_emb: sin
+  num_freqs: 128
+  edge_style: fc
+  max_neighbors: 20
+  cutoff: 7.0
+  ln: true
+  use_log_map: true
+  dim_atomic_rep: ${get_dim_atomic_rep:${model.manifold_getter.atom_type_manifold}}
+  lattice_manifold: ${model.manifold_getter.lattice_manifold}
+  concat_sum_pool: true
+  represent_num_atoms: true
+  represent_angle_edge_to_lattice: true
+  self_edges: false
+  self_cond: ${model.self_cond}