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simergy-diffusion-tmo-alpha

mattergen
diffusion
crystal-generation
materials-science
transition-metal-oxides
energy-above-hull
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simergy-diffusion-tmo-alpha
File size: 6,929 Bytes
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adapter:
  adapter:
    _target_: mattergen.adapter.GemNetTAdapter
    atom_type_diffusion: mask
    denoise_atom_types: true
    gemnet:
      _target_: mattergen.common.gemnet.gemnet_ctrl.GemNetTCtrl
      atom_embedding:
        _target_: mattergen.common.gemnet.layers.embedding_block.AtomEmbedding
        emb_size: 512
        with_mask_type: true
      condition_on_adapt: []
      cutoff: 7.0
      emb_size_atom: 512
      emb_size_edge: 512
      latent_dim: 512
      max_cell_images_per_dim: 5
      max_neighbors: 50
      num_blocks: 4
      num_targets: 1
      otf_graph: true
      regress_stress: true
      scale_file: /scratch/amlt_code/mattergen/common/gemnet/gemnet-dT.json
    hidden_dim: 512
    property_embeddings: {}
    property_embeddings_adapt: {}
  full_finetuning: true
  load_epoch: last
  model_path: null
  pretrained_name: chemical_system_energy_above_hull
data_module:
  _recursive_: true
  _target_: mattergen.common.data.datamodule.CrystDataModule
  average_density: 0.06
  batch_size:
    test: 16
    train: 16
    val: 16
  dataset_transforms:
  - _partial_: true
    _target_: mattergen.common.data.dataset_transform.filter_sparse_properties
  num_workers:
    test: 0
    train: 4
    val: 0
  properties:
  - energy_above_hull
  root_dir: /home/sagemaker-user/simergy-diffusion-tmo-alpha/mattergen_repo/mattergen/../datasets/cache/tmo_ehull
  test_dataset:
    _target_: mattergen.common.data.dataset.CrystalDataset.from_cache_path
    cache_path: /home/sagemaker-user/simergy-diffusion-tmo-alpha/mattergen_repo/mattergen/../datasets/cache/tmo_ehull/val
    dataset_transforms:
    - _partial_: true
      _target_: mattergen.common.data.dataset_transform.filter_sparse_properties
    properties:
    - energy_above_hull
    transforms:
    - _partial_: true
      _target_: mattergen.common.data.transform.symmetrize_lattice
    - _partial_: true
      _target_: mattergen.common.data.transform.set_chemical_system_string
  train_dataset:
    _target_: mattergen.common.data.dataset.CrystalDataset.from_cache_path
    cache_path: /home/sagemaker-user/simergy-diffusion-tmo-alpha/mattergen_repo/mattergen/../datasets/cache/tmo_ehull/train
    dataset_transforms:
    - _partial_: true
      _target_: mattergen.common.data.dataset_transform.filter_sparse_properties
    properties:
    - energy_above_hull
    transforms:
    - _partial_: true
      _target_: mattergen.common.data.transform.symmetrize_lattice
    - _partial_: true
      _target_: mattergen.common.data.transform.set_chemical_system_string
  transforms:
  - _partial_: true
    _target_: mattergen.common.data.transform.symmetrize_lattice
  - _partial_: true
    _target_: mattergen.common.data.transform.set_chemical_system_string
  val_dataset:
    _target_: mattergen.common.data.dataset.CrystalDataset.from_cache_path
    cache_path: /home/sagemaker-user/simergy-diffusion-tmo-alpha/mattergen_repo/mattergen/../datasets/cache/tmo_ehull/val
    dataset_transforms:
    - _partial_: true
      _target_: mattergen.common.data.dataset_transform.filter_sparse_properties
    properties:
    - energy_above_hull
    transforms:
    - _partial_: true
      _target_: mattergen.common.data.transform.symmetrize_lattice
    - _partial_: true
      _target_: mattergen.common.data.transform.set_chemical_system_string
lightning_module:
  _target_: mattergen.diffusion.lightning_module.DiffusionLightningModule
  diffusion_module:
    _target_: mattergen.diffusion.diffusion_module.DiffusionModule
    corruption:
      _target_: mattergen.diffusion.corruption.multi_corruption.MultiCorruption
      discrete_corruptions:
        atomic_numbers:
          _target_: mattergen.diffusion.corruption.d3pm_corruption.D3PMCorruption
          d3pm:
            _target_: mattergen.diffusion.d3pm.d3pm.MaskDiffusion
            dim: 101
            schedule:
              _target_: mattergen.diffusion.d3pm.d3pm.create_discrete_diffusion_schedule
              kind: standard
              num_steps: 1000
          offset: 1
      sdes:
        cell:
          _target_: mattergen.common.diffusion.corruption.LatticeVPSDE.from_vpsde_config
          vpsde_config:
            beta_max: 20
            beta_min: 0.1
            limit_density: 0.05771451654022283
            limit_var_scaling_constant: 0.25
        pos:
          _target_: mattergen.common.diffusion.corruption.NumAtomsVarianceAdjustedWrappedVESDE
          limit_info_key: num_atoms
          sigma_max: 5.0
          wrapping_boundary: 1.0
    loss_fn:
      _target_: mattergen.common.loss.MaterialsLoss
      d3pm_hybrid_lambda: 0.01
      include_atomic_numbers: true
      include_cell: true
      include_pos: true
      reduce: sum
      weights:
        atomic_numbers: 1.0
        cell: 1.0
        pos: 0.1
    model:
      _target_: mattergen.adapter.GemNetTAdapter
      atom_type_diffusion: mask
      denoise_atom_types: true
      gemnet:
        _target_: mattergen.common.gemnet.gemnet_ctrl.GemNetTCtrl
        atom_embedding:
          _target_: mattergen.common.gemnet.layers.embedding_block.AtomEmbedding
          emb_size: 512
          with_mask_type: true
        condition_on_adapt: []
        cutoff: 7.0
        emb_size_atom: 512
        emb_size_edge: 512
        latent_dim: 512
        max_cell_images_per_dim: 5
        max_neighbors: 50
        num_blocks: 4
        num_targets: 1
        otf_graph: true
        regress_stress: true
        scale_file: /scratch/amlt_code/mattergen/common/gemnet/gemnet-dT.json
      hidden_dim: 512
      property_embeddings: {}
      property_embeddings_adapt: {}
    pre_corruption_fn:
      _target_: mattergen.property_embeddings.SetEmbeddingType
      dropout_fields_iid: false
      p_unconditional: 0.2
  optimizer_partial:
    _partial_: true
    _target_: torch.optim.Adam
    lr: 5.0e-06
  scheduler_partials:
  - frequency: 1
    interval: epoch
    monitor: loss_train
    scheduler:
      _partial_: true
      _target_: torch.optim.lr_scheduler.ReduceLROnPlateau
      factor: 0.6
      min_lr: 1.0e-06
      patience: 100
      verbose: true
    strict: true
trainer:
  _target_: pytorch_lightning.Trainer
  accelerator: gpu
  accumulate_grad_batches: 8
  callbacks:
  - _target_: pytorch_lightning.callbacks.ModelCheckpoint
    every_n_epochs: 1
    filename: '{epoch}-{loss_val:.2f}'
    mode: min
    monitor: loss_val
    save_last: true
    save_top_k: 1
    verbose: false
  - _target_: pytorch_lightning.callbacks.TQDMProgressBar
    refresh_rate: 50
  - _target_: mattergen.common.data.callback.SetPropertyScalers
  check_val_every_n_epoch: 5
  devices: 1
  gradient_clip_algorithm: value
  gradient_clip_val: 0.5
  log_every_n_steps: 10
  logger:
    _target_: pytorch_lightning.loggers.CSVLogger
    name: tmo_ehull_finetune
    save_dir: /home/sagemaker-user/simergy-diffusion-tmo-alpha/results/tmo_ehull_finetune
  max_epochs: 100
  num_nodes: 1
  precision: 32