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ckpt/mp20_PathRefine/.hydra/config.yaml

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+core:
+  version: ${get_flowmm_version:}
+  tags:
+  - ${now:%Y-%m-%d}
+logging:
+  val_check_interval: 25
+  wandb:
+    project: uniug_uni
+    entity: null
+    log_model: true
+    mode: cloud
+    experiment_name: mp20_PathRefine_wuns0.001_wc0.01_e400_e450
+  wandb_watch:
+    log: all
+    log_freq: 500
+  lr_monitor:
+    logging_interval: step
+    log_momentum: false
+optim:
+  optimizer:
+    _target_: torch.optim.AdamW
+    lr: 0.0005
+    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
+    strategy: ddp_find_unused_parameters_true
+    num_nodes: 1
+    devices: 8
+    accelerator: gpu
+    precision: 32
+    max_epochs: ${data.train_max_epochs}
+    accumulate_grad_batches: 1
+    num_sanity_val_steps: 1
+    gradient_clip_val: 10.0
+    gradient_clip_algorithm: norm
+    profiler: simple
+    log_every_n_steps: 500
+  monitor_metric: val/loss_csp
+  monitor_metric_mode: min
+  model_checkpoints:
+    save_top_k: 1
+    verbose: false
+    save_last: false
+  every_n_epochs_checkpoint:
+    every_n_epochs: 25
+    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
+partial_ckpt_load: true
+partial_ckpt_path: /mnt/ai4sci_develop_fast/songyouli/crystal-uniug/runs/trash/uniug_uni/bz256_mp20_mptsub_tclearn_freeze_epoch500/every_n_epochs/epoch=399-step=754800.ckpt
+data:
+  dataset_name: mp_20
+  dim_coords: 3
+  root_path: ${oc.env:DATA_DIR}/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: 500
+  early_stopping_patience: 100000
+  teacher_forcing_max_epoch: 500
+  md_dataset_name: mptsubmp20_v0
+  root_path_md: ${oc.env:DATA_DIR}/${data.md_dataset_name}
+  require_order: false
+  prop_md:
+  - energy
+  - forces
+  energy_only: true
+  t_mode: c_learn
+  t_constant: 1.0
+  datamodule:
+    _target_: uniug.datamodule_uni.CrystDataModule
+    task_mode: uni
+    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}
+      train_md:
+        _target_: diffcsp.pl_data.dataset.CrystDataset
+        name: Formation energy train
+        path: ${data.root_path_md}/train.csv
+        save_path: ${data.root_path_md}/train_ori.pt
+        require_order: ${data.require_order}
+        prop: ${data.prop_md}
+        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_md:
+      - _target_: diffcsp.pl_data.dataset.CrystDataset
+        name: Formation energy val
+        path: ${data.root_path_md}/val.csv
+        save_path: ${data.root_path_md}/val_ori.pt
+        require_order: ${data.require_order}
+        prop: ${data.prop_md}
+        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: 32
+      val: 32
+      test: 32
+      train_md: 32
+      val_md: 32
+    pin_memory: true
+    persistent_workers: false
+    prefetch_factor: 2
+model:
+  w_csp: 0.95
+  w_pflow: 0.2
+  w_time: 0.1
+  cost_coord: 400.0
+  cost_lattice: 1.0
+  cost_type: 0.0
+  cost_energy: 1.0
+  cost_forces: 1.0
+  cost_stress: 1.0
+  affine_combine_costs: true
+  target_distribution: conditional
+  self_cond: false
+  t_pflow_clip: false
+  use_tangent: false
+  tclearn_freeze_epoch: 250
+  use_uns_flow_task: true
+  w_uns_flow: 0.001
+  w_consist: 0.01
+  uns_flow_tscale: true
+  uns_flow_tlearn: true
+  uns_path_refine: true
+  uns_path_t_clip: 0.9
+  use_consist_flow: true
+  consist_freeze_epoch: 450
+  uns_flow_freeze_epoch: 400
+  manifold_getter:
+    atom_type_manifold: null_manifold
+    coord_manifold: flat_torus_01
+    lattice_manifold: lattice_params
+    length_inner_coef: 1.0
+vectorfield:
+  _target_: uniug.arch_uni.FlowmmUniModel
+  force_pred_way: direct
+  use_pflow_head: true
+  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}
+  t_mode: ${data.t_mode}
+  t_mask: -1.0
+  use_pflow_task: false
+  tlearn_clip: false
+  learnable_time_emb: false

ckpt/mp20_PathRefine/.hydra/overrides.yaml

@@ -0,0 +1,35 @@
+- data=mp20_mptsub
+- data.md_dataset_name=mptsubmp20_v0
+- model=null_params_uni
+- vectorfield=rfm_cspnet_uni
+- train.pl_trainer.num_nodes=1
+- train.pl_trainer.devices=8
+- data.datamodule.batch_size.train=32
+- data.datamodule.batch_size.train_md=32
+- data.datamodule.batch_size.val=32
+- data.datamodule.batch_size.val_md=32
+- data.datamodule.batch_size.test=32
+- logging.wandb.project=uniug_uni
+- logging.wandb.experiment_name=mp20_PathRefine_wuns0.001_wc0.01_e400_e450
+- data.energy_only=True
+- model.w_csp=0.95
+- optim.optimizer.lr=0.0005
+- train.pl_trainer.gradient_clip_val=10.0
+- train.pl_trainer.gradient_clip_algorithm=norm
+- data.t_mode=c_learn
+- model.tclearn_freeze_epoch=250
+- model.use_uns_flow_task=True
+- vectorfield.use_pflow_head=True
+- model.w_uns_flow=0.001
+- model.uns_flow_tscale=True
+- model.uns_flow_tlearn=True
+- data.train_max_epochs=500
+- logging.val_check_interval=25
+- train.every_n_epochs_checkpoint.every_n_epochs=25
+- model.uns_path_refine=True
+- model.uns_flow_freeze_epoch=400
+- model.use_consist_flow=True
+- model.consist_freeze_epoch=450
+- model.w_consist=0.01
+- partial_ckpt_load=True
+- partial_ckpt_path="/mnt/ai4sci_develop_fast/songyouli/crystal-uniug/runs/trash/uniug_uni/bz256_mp20_mptsub_tclearn_freeze_epoch500/every_n_epochs/epoch=399-step=754800.ckpt"

ckpt/mp20_PathRefine/every_n_epochs/epoch=499-step=190587.ckpt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9510fd7c337d86bfe94f27134bdca2a7cfa8be151a93b89919ef3c8bca0c78f5
+size 227511350

ckpt/mp20_PathRefine/hparams.yaml

@@ -0,0 +1,250 @@
+core:
+  version: ${get_flowmm_version:}
+  tags:
+  - ${now:%Y-%m-%d}
+  - ⚡️pytorch lightning
+logging:
+  val_check_interval: 25
+  wandb:
+    project: uniug_uni
+    entity: null
+    log_model: true
+    mode: cloud
+    experiment_name: mp20_PathRefine_wuns0.001_wc0.01_e400_e450
+  wandb_watch:
+    log: all
+    log_freq: 500
+  lr_monitor:
+    logging_interval: step
+    log_momentum: false
+optim:
+  optimizer:
+    _target_: torch.optim.AdamW
+    lr: 0.0005
+    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
+    strategy: ddp_find_unused_parameters_true
+    num_nodes: 1
+    devices: 8
+    accelerator: gpu
+    precision: 32
+    max_epochs: ${data.train_max_epochs}
+    accumulate_grad_batches: 1
+    num_sanity_val_steps: 1
+    gradient_clip_val: 10.0
+    gradient_clip_algorithm: norm
+    profiler: simple
+    log_every_n_steps: 500
+  monitor_metric: val/loss_csp
+  monitor_metric_mode: min
+  model_checkpoints:
+    save_top_k: 1
+    verbose: false
+    save_last: false
+  every_n_epochs_checkpoint:
+    every_n_epochs: 25
+    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
+partial_ckpt_load: true
+partial_ckpt_path: /mnt/ai4sci_develop_fast/songyouli/crystal-uniug/runs/trash/uniug_uni/bz256_mp20_mptsub_tclearn_freeze_epoch500/every_n_epochs/epoch=399-step=754800.ckpt
+data:
+  dataset_name: mp_20
+  dim_coords: 3
+  root_path: ${oc.env:DATA_DIR}/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: 500
+  early_stopping_patience: 100000
+  teacher_forcing_max_epoch: 500
+  md_dataset_name: mptsubmp20_v0
+  root_path_md: ${oc.env:DATA_DIR}/${data.md_dataset_name}
+  require_order: false
+  prop_md:
+  - energy
+  - forces
+  energy_only: true
+  t_mode: c_learn
+  t_constant: 1.0
+  datamodule:
+    _target_: uniug.datamodule_uni.CrystDataModule
+    task_mode: uni
+    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}
+      train_md:
+        _target_: diffcsp.pl_data.dataset.CrystDataset
+        name: Formation energy train
+        path: ${data.root_path_md}/train.csv
+        save_path: ${data.root_path_md}/train_ori.pt
+        require_order: ${data.require_order}
+        prop: ${data.prop_md}
+        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_md:
+      - _target_: diffcsp.pl_data.dataset.CrystDataset
+        name: Formation energy val
+        path: ${data.root_path_md}/val.csv
+        save_path: ${data.root_path_md}/val_ori.pt
+        require_order: ${data.require_order}
+        prop: ${data.prop_md}
+        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: 32
+      val: 32
+      test: 32
+      train_md: 32
+      val_md: 32
+    pin_memory: true
+    persistent_workers: false
+    prefetch_factor: 2
+model:
+  w_csp: 0.95
+  w_pflow: 0.2
+  w_time: 0.1
+  cost_coord: 400.0
+  cost_lattice: 1.0
+  cost_type: 0.0
+  cost_energy: 1.0
+  cost_forces: 1.0
+  cost_stress: 1.0
+  affine_combine_costs: true
+  target_distribution: conditional
+  self_cond: false
+  t_pflow_clip: false
+  use_tangent: false
+  tclearn_freeze_epoch: 250
+  use_uns_flow_task: true
+  w_uns_flow: 0.001
+  w_consist: 0.01
+  uns_flow_tscale: true
+  uns_flow_tlearn: true
+  uns_path_refine: true
+  uns_path_t_clip: 0.9
+  use_consist_flow: true
+  consist_freeze_epoch: 450
+  uns_flow_freeze_epoch: 400
+  manifold_getter:
+    atom_type_manifold: null_manifold
+    coord_manifold: flat_torus_01
+    lattice_manifold: lattice_params
+    length_inner_coef: 1.0
+vectorfield:
+  _target_: uniug.arch_uni.FlowmmUniModel
+  force_pred_way: direct
+  use_pflow_head: true
+  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}
+  t_mode: ${data.t_mode}
+  t_mask: -1.0
+  use_pflow_task: false
+  tlearn_clip: false
+  learnable_time_emb: false

ckpt/mp20_uns_PathRefine/.hydra/config.yaml

@@ -0,0 +1,249 @@
+core:
+  version: ${get_flowmm_version:}
+  tags:
+  - ${now:%Y-%m-%d}
+logging:
+  val_check_interval: 10
+  wandb:
+    project: uniug_uni
+    entity: null
+    log_model: true
+    mode: cloud
+    experiment_name: mp20_uns_PathRefine_wuns0.02_wc0.5_e199_e249
+  wandb_watch:
+    log: all
+    log_freq: 500
+  lr_monitor:
+    logging_interval: step
+    log_momentum: false
+optim:
+  optimizer:
+    _target_: torch.optim.AdamW
+    lr: 0.0005
+    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
+    strategy: ddp_find_unused_parameters_true
+    num_nodes: 1
+    devices: 8
+    accelerator: gpu
+    precision: 32
+    max_epochs: ${data.train_max_epochs}
+    accumulate_grad_batches: 1
+    num_sanity_val_steps: 1
+    gradient_clip_val: 10.0
+    gradient_clip_algorithm: norm
+    profiler: simple
+    log_every_n_steps: 500
+  monitor_metric: val/loss_csp
+  monitor_metric_mode: min
+  model_checkpoints:
+    save_top_k: 1
+    verbose: false
+    save_last: false
+  every_n_epochs_checkpoint:
+    every_n_epochs: 10
+    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
+partial_ckpt_load: true
+partial_ckpt_path: /mnt/ai4sci_develop_fast/songyouli/crystal-uniug/runs/trash/uniug_uni/mp20_mptsub_uns_V0_tclearn_freeze_wcsp0.95/every_n_epochs/epoch=199-step=172600.ckpt
+data:
+  dataset_name: mp_20
+  dim_coords: 3
+  root_path: ${oc.env:DATA_DIR}/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: 300
+  early_stopping_patience: 100000
+  teacher_forcing_max_epoch: 500
+  md_dataset_name: mptsubmp20_uns_V0
+  root_path_md: ${oc.env:DATA_DIR}/${data.md_dataset_name}
+  require_order: false
+  prop_md:
+  - energy
+  - forces
+  energy_only: true
+  t_mode: c_learn
+  t_constant: 1.0
+  datamodule:
+    _target_: uniug.datamodule_uni.CrystDataModule
+    task_mode: uni
+    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}
+      train_md:
+        _target_: diffcsp.pl_data.dataset.CrystDataset
+        name: Formation energy train
+        path: ${data.root_path_md}/train.csv
+        save_path: ${data.root_path_md}/train_ori.pt
+        require_order: ${data.require_order}
+        prop: ${data.prop_md}
+        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_md:
+      - _target_: diffcsp.pl_data.dataset.CrystDataset
+        name: Formation energy val
+        path: ${data.root_path_md}/val.csv
+        save_path: ${data.root_path_md}/val_ori.pt
+        require_order: ${data.require_order}
+        prop: ${data.prop_md}
+        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: 64
+      val: 64
+      test: 64
+      train_md: 64
+      val_md: 64
+    pin_memory: true
+    persistent_workers: false
+    prefetch_factor: 2
+model:
+  w_csp: 0.95
+  w_pflow: 0.2
+  w_time: 0.1
+  cost_coord: 400.0
+  cost_lattice: 1.0
+  cost_type: 0.0
+  cost_energy: 1.0
+  cost_forces: 1.0
+  cost_stress: 1.0
+  affine_combine_costs: true
+  target_distribution: conditional
+  self_cond: false
+  t_pflow_clip: false
+  use_tangent: false
+  tclearn_freeze_epoch: 150
+  use_uns_flow_task: true
+  w_uns_flow: 0.02
+  w_consist: 0.5
+  uns_flow_tscale: true
+  uns_flow_tlearn: true
+  uns_path_refine: true
+  uns_path_t_clip: 0.9
+  use_consist_flow: true
+  consist_freeze_epoch: 249
+  uns_flow_freeze_epoch: 199
+  manifold_getter:
+    atom_type_manifold: null_manifold
+    coord_manifold: flat_torus_01
+    lattice_manifold: lattice_params
+    length_inner_coef: 1.0
+vectorfield:
+  _target_: uniug.arch_uni.FlowmmUniModel
+  force_pred_way: direct
+  use_pflow_head: true
+  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}
+  t_mode: ${data.t_mode}
+  t_mask: -1.0
+  use_pflow_task: false
+  tlearn_clip: false
+  learnable_time_emb: false

ckpt/mp20_uns_PathRefine/.hydra/overrides.yaml

@@ -0,0 +1,35 @@
+- data=mp20_mptsub
+- data.md_dataset_name=mptsubmp20_uns_V0
+- model=null_params_uni
+- vectorfield=rfm_cspnet_uni
+- train.pl_trainer.num_nodes=1
+- train.pl_trainer.devices=8
+- data.datamodule.batch_size.train=64
+- data.datamodule.batch_size.train_md=64
+- data.datamodule.batch_size.val=64
+- data.datamodule.batch_size.val_md=64
+- data.datamodule.batch_size.test=64
+- logging.wandb.project=uniug_uni
+- logging.wandb.experiment_name=mp20_uns_PathRefine_wuns0.02_wc0.5_e199_e249
+- data.energy_only=True
+- model.w_csp=0.95
+- optim.optimizer.lr=0.0005
+- train.pl_trainer.gradient_clip_val=10.0
+- train.pl_trainer.gradient_clip_algorithm=norm
+- data.t_mode=c_learn
+- model.tclearn_freeze_epoch=150
+- model.use_uns_flow_task=True
+- vectorfield.use_pflow_head=True
+- model.w_uns_flow=0.02
+- model.uns_flow_tscale=True
+- model.uns_flow_tlearn=True
+- data.train_max_epochs=300
+- logging.val_check_interval=10
+- train.every_n_epochs_checkpoint.every_n_epochs=10
+- model.uns_path_refine=True
+- model.uns_flow_freeze_epoch=199
+- model.use_consist_flow=True
+- model.consist_freeze_epoch=249
+- model.w_consist=0.5
+- partial_ckpt_load=True
+- partial_ckpt_path="/mnt/ai4sci_develop_fast/songyouli/crystal-uniug/runs/trash/uniug_uni/mp20_mptsub_uns_V0_tclearn_freeze_wcsp0.95/every_n_epochs/epoch=199-step=172600.ckpt"

ckpt/mp20_uns_PathRefine/every_n_epochs/epoch=299-step=87163.ckpt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d7fe702488b4f1ade82e7512afe9f1119678234444ec86f2c8e8e06c429458bc
+size 227511350

ckpt/mp20_uns_PathRefine/hparams.yaml

@@ -0,0 +1,250 @@
+core:
+  version: ${get_flowmm_version:}
+  tags:
+  - ${now:%Y-%m-%d}
+  - ⚡️pytorch lightning
+logging:
+  val_check_interval: 10
+  wandb:
+    project: uniug_uni
+    entity: null
+    log_model: true
+    mode: cloud
+    experiment_name: mp20_uns_PathRefine_wuns0.02_wc0.5_e199_e249
+  wandb_watch:
+    log: all
+    log_freq: 500
+  lr_monitor:
+    logging_interval: step
+    log_momentum: false
+optim:
+  optimizer:
+    _target_: torch.optim.AdamW
+    lr: 0.0005
+    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
+    strategy: ddp_find_unused_parameters_true
+    num_nodes: 1
+    devices: 8
+    accelerator: gpu
+    precision: 32
+    max_epochs: ${data.train_max_epochs}
+    accumulate_grad_batches: 1
+    num_sanity_val_steps: 1
+    gradient_clip_val: 10.0
+    gradient_clip_algorithm: norm
+    profiler: simple
+    log_every_n_steps: 500
+  monitor_metric: val/loss_csp
+  monitor_metric_mode: min
+  model_checkpoints:
+    save_top_k: 1
+    verbose: false
+    save_last: false
+  every_n_epochs_checkpoint:
+    every_n_epochs: 10
+    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
+partial_ckpt_load: true
+partial_ckpt_path: /mnt/ai4sci_develop_fast/songyouli/crystal-uniug/runs/trash/uniug_uni/mp20_mptsub_uns_V0_tclearn_freeze_wcsp0.95/every_n_epochs/epoch=199-step=172600.ckpt
+data:
+  dataset_name: mp_20
+  dim_coords: 3
+  root_path: ${oc.env:DATA_DIR}/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: 300
+  early_stopping_patience: 100000
+  teacher_forcing_max_epoch: 500
+  md_dataset_name: mptsubmp20_uns_V0
+  root_path_md: ${oc.env:DATA_DIR}/${data.md_dataset_name}
+  require_order: false
+  prop_md:
+  - energy
+  - forces
+  energy_only: true
+  t_mode: c_learn
+  t_constant: 1.0
+  datamodule:
+    _target_: uniug.datamodule_uni.CrystDataModule
+    task_mode: uni
+    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}
+      train_md:
+        _target_: diffcsp.pl_data.dataset.CrystDataset
+        name: Formation energy train
+        path: ${data.root_path_md}/train.csv
+        save_path: ${data.root_path_md}/train_ori.pt
+        require_order: ${data.require_order}
+        prop: ${data.prop_md}
+        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_md:
+      - _target_: diffcsp.pl_data.dataset.CrystDataset
+        name: Formation energy val
+        path: ${data.root_path_md}/val.csv
+        save_path: ${data.root_path_md}/val_ori.pt
+        require_order: ${data.require_order}
+        prop: ${data.prop_md}
+        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: 64
+      val: 64
+      test: 64
+      train_md: 64
+      val_md: 64
+    pin_memory: true
+    persistent_workers: false
+    prefetch_factor: 2
+model:
+  w_csp: 0.95
+  w_pflow: 0.2
+  w_time: 0.1
+  cost_coord: 400.0
+  cost_lattice: 1.0
+  cost_type: 0.0
+  cost_energy: 1.0
+  cost_forces: 1.0
+  cost_stress: 1.0
+  affine_combine_costs: true
+  target_distribution: conditional
+  self_cond: false
+  t_pflow_clip: false
+  use_tangent: false
+  tclearn_freeze_epoch: 150
+  use_uns_flow_task: true
+  w_uns_flow: 0.02
+  w_consist: 0.5
+  uns_flow_tscale: true
+  uns_flow_tlearn: true
+  uns_path_refine: true
+  uns_path_t_clip: 0.9
+  use_consist_flow: true
+  consist_freeze_epoch: 249
+  uns_flow_freeze_epoch: 199
+  manifold_getter:
+    atom_type_manifold: null_manifold
+    coord_manifold: flat_torus_01
+    lattice_manifold: lattice_params
+    length_inner_coef: 1.0
+vectorfield:
+  _target_: uniug.arch_uni.FlowmmUniModel
+  force_pred_way: direct
+  use_pflow_head: true
+  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}
+  t_mode: ${data.t_mode}
+  t_mask: -1.0
+  use_pflow_task: false
+  tlearn_clip: false
+  learnable_time_emb: false

ckpt/mpts52_PathRefine/.hydra/config.yaml

@@ -0,0 +1,249 @@
+core:
+  version: ${get_flowmm_version:}
+  tags:
+  - ${now:%Y-%m-%d}
+logging:
+  val_check_interval: 5
+  wandb:
+    project: uniug_uni
+    entity: null
+    log_model: true
+    mode: cloud
+    experiment_name: mpts52_PathRefine_wuns0.1_wc0.05_e109_e129
+  wandb_watch:
+    log: all
+    log_freq: 500
+  lr_monitor:
+    logging_interval: step
+    log_momentum: false
+optim:
+  optimizer:
+    _target_: torch.optim.AdamW
+    lr: 0.0005
+    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
+    strategy: ddp_find_unused_parameters_true
+    num_nodes: 1
+    devices: 4
+    accelerator: gpu
+    precision: 32
+    max_epochs: ${data.train_max_epochs}
+    accumulate_grad_batches: 1
+    num_sanity_val_steps: 1
+    gradient_clip_val: 10.0
+    gradient_clip_algorithm: norm
+    profiler: simple
+    log_every_n_steps: 500
+  monitor_metric: val/loss_csp
+  monitor_metric_mode: min
+  model_checkpoints:
+    save_top_k: 1
+    verbose: false
+    save_last: false
+  every_n_epochs_checkpoint:
+    every_n_epochs: 5
+    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
+partial_ckpt_load: true
+partial_ckpt_path: /mnt/ai4sci_develop_fast/songyouli/crystal-uniug/runs/trash/uniug_uni/mpts52_PathRefine_wuns0.1_e109/every_n_epochs/epoch=129-step=80976.ckpt
+data:
+  dataset_name: mpts_52
+  dim_coords: 3
+  root_path: ${oc.env:DATA_DIR}/mpts_52
+  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: 52
+  otf_graph: false
+  eval_model_name: mp20
+  tolerance: 0.1
+  use_space_group: false
+  use_pos_index: false
+  train_max_epochs: 150
+  early_stopping_patience: 100000
+  teacher_forcing_max_epoch: 300
+  md_dataset_name: mptsubmpts52
+  root_path_md: ${oc.env:DATA_DIR}/${data.md_dataset_name}
+  require_order: false
+  prop_md:
+  - energy
+  - forces
+  energy_only: true
+  t_mode: c_learn
+  t_constant: 1.0
+  datamodule:
+    _target_: uniug.datamodule_uni.CrystDataModule
+    task_mode: uni
+    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}
+      train_md:
+        _target_: diffcsp.pl_data.dataset.CrystDataset
+        name: Formation energy train
+        path: ${data.root_path_md}/train.csv
+        save_path: ${data.root_path_md}/train_ori.pt
+        require_order: ${data.require_order}
+        prop: ${data.prop_md}
+        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_md:
+      - _target_: diffcsp.pl_data.dataset.CrystDataset
+        name: Formation energy val
+        path: ${data.root_path_md}/val.csv
+        save_path: ${data.root_path_md}/val_ori.pt
+        require_order: ${data.require_order}
+        prop: ${data.prop_md}
+        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: 32
+      val: 32
+      test: 32
+      train_md: 32
+      val_md: 32
+    pin_memory: true
+    persistent_workers: false
+    prefetch_factor: 2
+model:
+  w_csp: 0.95
+  w_pflow: 0.2
+  w_time: 0.1
+  cost_coord: 400.0
+  cost_lattice: 1.0
+  cost_type: 0.0
+  cost_energy: 1.0
+  cost_forces: 1.0
+  cost_stress: 1.0
+  affine_combine_costs: true
+  target_distribution: conditional
+  self_cond: false
+  t_pflow_clip: false
+  use_tangent: false
+  tclearn_freeze_epoch: 75
+  use_uns_flow_task: true
+  w_uns_flow: 0.1
+  w_consist: 0.05
+  uns_flow_tscale: true
+  uns_flow_tlearn: true
+  uns_path_refine: true
+  uns_path_t_clip: 0.9
+  use_consist_flow: true
+  consist_freeze_epoch: 129
+  uns_flow_freeze_epoch: 109
+  manifold_getter:
+    atom_type_manifold: null_manifold
+    coord_manifold: flat_torus_01
+    lattice_manifold: lattice_params
+    length_inner_coef: 1.0
+vectorfield:
+  _target_: uniug.arch_uni.FlowmmUniModel
+  force_pred_way: direct
+  use_pflow_head: true
+  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}
+  t_mode: ${data.t_mode}
+  t_mask: -1.0
+  use_pflow_task: false
+  tlearn_clip: false
+  learnable_time_emb: false

ckpt/mpts52_PathRefine/.hydra/overrides.yaml

@@ -0,0 +1,34 @@
+- data=mpts52_mptsub
+- model=null_params_uni
+- vectorfield=rfm_cspnet_uni
+- train.pl_trainer.num_nodes=1
+- train.pl_trainer.devices=4
+- data.datamodule.batch_size.train=32
+- data.datamodule.batch_size.train_md=32
+- data.datamodule.batch_size.val=32
+- data.datamodule.batch_size.val_md=32
+- data.datamodule.batch_size.test=32
+- logging.wandb.project=uniug_uni
+- logging.wandb.experiment_name=mpts52_PathRefine_wuns0.1_wc0.05_e109_e129
+- data.energy_only=True
+- model.w_csp=0.95
+- optim.optimizer.lr=0.0005
+- train.pl_trainer.gradient_clip_val=10.0
+- train.pl_trainer.gradient_clip_algorithm=norm
+- data.t_mode=c_learn
+- model.tclearn_freeze_epoch=75
+- model.use_uns_flow_task=True
+- vectorfield.use_pflow_head=True
+- model.w_uns_flow=0.1
+- model.uns_flow_tscale=True
+- model.uns_flow_tlearn=True
+- data.train_max_epochs=150
+- logging.val_check_interval=5
+- train.every_n_epochs_checkpoint.every_n_epochs=5
+- model.uns_path_refine=True
+- model.uns_flow_freeze_epoch=109
+- model.use_consist_flow=True
+- model.consist_freeze_epoch=129
+- model.w_consist=0.05
+- partial_ckpt_load=True
+- partial_ckpt_path="/mnt/ai4sci_develop_fast/songyouli/crystal-uniug/runs/trash/uniug_uni/mpts52_PathRefine_wuns0.1_e109/every_n_epochs/epoch=129-step=80976.ckpt"

ckpt/mpts52_PathRefine/every_n_epochs/epoch=149-step=80976.ckpt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:36b9a9c16997f269b118d13e32160a5247c7824d3cff6eabf1990144401076d0
+size 227511350

ckpt/mpts52_PathRefine/hparams.yaml

@@ -0,0 +1,250 @@
+core:
+  version: ${get_flowmm_version:}
+  tags:
+  - ${now:%Y-%m-%d}
+  - ⚡️pytorch lightning
+logging:
+  val_check_interval: 5
+  wandb:
+    project: uniug_uni
+    entity: null
+    log_model: true
+    mode: cloud
+    experiment_name: mpts52_PathRefine_wuns0.1_wc0.05_e109_e129
+  wandb_watch:
+    log: all
+    log_freq: 500
+  lr_monitor:
+    logging_interval: step
+    log_momentum: false
+optim:
+  optimizer:
+    _target_: torch.optim.AdamW
+    lr: 0.0005
+    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
+    strategy: ddp_find_unused_parameters_true
+    num_nodes: 1
+    devices: 4
+    accelerator: gpu
+    precision: 32
+    max_epochs: ${data.train_max_epochs}
+    accumulate_grad_batches: 1
+    num_sanity_val_steps: 1
+    gradient_clip_val: 10.0
+    gradient_clip_algorithm: norm
+    profiler: simple
+    log_every_n_steps: 500
+  monitor_metric: val/loss_csp
+  monitor_metric_mode: min
+  model_checkpoints:
+    save_top_k: 1
+    verbose: false
+    save_last: false
+  every_n_epochs_checkpoint:
+    every_n_epochs: 5
+    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
+partial_ckpt_load: true
+partial_ckpt_path: /mnt/ai4sci_develop_fast/songyouli/crystal-uniug/runs/trash/uniug_uni/mpts52_PathRefine_wuns0.1_e109/every_n_epochs/epoch=129-step=80976.ckpt
+data:
+  dataset_name: mpts_52
+  dim_coords: 3
+  root_path: ${oc.env:DATA_DIR}/mpts_52
+  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: 52
+  otf_graph: false
+  eval_model_name: mp20
+  tolerance: 0.1
+  use_space_group: false
+  use_pos_index: false
+  train_max_epochs: 150
+  early_stopping_patience: 100000
+  teacher_forcing_max_epoch: 300
+  md_dataset_name: mptsubmpts52
+  root_path_md: ${oc.env:DATA_DIR}/${data.md_dataset_name}
+  require_order: false
+  prop_md:
+  - energy
+  - forces
+  energy_only: true
+  t_mode: c_learn
+  t_constant: 1.0
+  datamodule:
+    _target_: uniug.datamodule_uni.CrystDataModule
+    task_mode: uni
+    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}
+      train_md:
+        _target_: diffcsp.pl_data.dataset.CrystDataset
+        name: Formation energy train
+        path: ${data.root_path_md}/train.csv
+        save_path: ${data.root_path_md}/train_ori.pt
+        require_order: ${data.require_order}
+        prop: ${data.prop_md}
+        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_md:
+      - _target_: diffcsp.pl_data.dataset.CrystDataset
+        name: Formation energy val
+        path: ${data.root_path_md}/val.csv
+        save_path: ${data.root_path_md}/val_ori.pt
+        require_order: ${data.require_order}
+        prop: ${data.prop_md}
+        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: 32
+      val: 32
+      test: 32
+      train_md: 32
+      val_md: 32
+    pin_memory: true
+    persistent_workers: false
+    prefetch_factor: 2
+model:
+  w_csp: 0.95
+  w_pflow: 0.2
+  w_time: 0.1
+  cost_coord: 400.0
+  cost_lattice: 1.0
+  cost_type: 0.0
+  cost_energy: 1.0
+  cost_forces: 1.0
+  cost_stress: 1.0
+  affine_combine_costs: true
+  target_distribution: conditional
+  self_cond: false
+  t_pflow_clip: false
+  use_tangent: false
+  tclearn_freeze_epoch: 75
+  use_uns_flow_task: true
+  w_uns_flow: 0.1
+  w_consist: 0.05
+  uns_flow_tscale: true
+  uns_flow_tlearn: true
+  uns_path_refine: true
+  uns_path_t_clip: 0.9
+  use_consist_flow: true
+  consist_freeze_epoch: 129
+  uns_flow_freeze_epoch: 109
+  manifold_getter:
+    atom_type_manifold: null_manifold
+    coord_manifold: flat_torus_01
+    lattice_manifold: lattice_params
+    length_inner_coef: 1.0
+vectorfield:
+  _target_: uniug.arch_uni.FlowmmUniModel
+  force_pred_way: direct
+  use_pflow_head: true
+  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}
+  t_mode: ${data.t_mode}
+  t_mask: -1.0
+  use_pflow_task: false
+  tlearn_clip: false
+  learnable_time_emb: false

ckpt/mpts52_uns_PathRefine/.hydra/config.yaml

@@ -0,0 +1,249 @@
+core:
+  version: ${get_flowmm_version:}
+  tags:
+  - ${now:%Y-%m-%d}
+logging:
+  val_check_interval: 5
+  wandb:
+    project: uniug_uni
+    entity: null
+    log_model: true
+    mode: cloud
+    experiment_name: mpts52_uns_PathRefine_wuns0.02_wc0.02_e109_e129
+  wandb_watch:
+    log: all
+    log_freq: 500
+  lr_monitor:
+    logging_interval: step
+    log_momentum: false
+optim:
+  optimizer:
+    _target_: torch.optim.AdamW
+    lr: 0.0005
+    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
+    strategy: ddp_find_unused_parameters_true
+    num_nodes: 1
+    devices: 4
+    accelerator: gpu
+    precision: 32
+    max_epochs: ${data.train_max_epochs}
+    accumulate_grad_batches: 1
+    num_sanity_val_steps: 1
+    gradient_clip_val: 10.0
+    gradient_clip_algorithm: norm
+    profiler: simple
+    log_every_n_steps: 500
+  monitor_metric: val/loss_csp
+  monitor_metric_mode: min
+  model_checkpoints:
+    save_top_k: 1
+    verbose: false
+    save_last: false
+  every_n_epochs_checkpoint:
+    every_n_epochs: 5
+    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
+partial_ckpt_load: true
+partial_ckpt_path: /mnt/ai4sci_develop_fast/songyouli/crystal-uniug/runs/trash/uniug_uni/mpts52_uns_PathRefine_wuns0.02_e109/every_n_epochs/epoch=129-step=36225.ckpt
+data:
+  dataset_name: mpts_52
+  dim_coords: 3
+  root_path: ${oc.env:DATA_DIR}/mpts_52
+  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: 52
+  otf_graph: false
+  eval_model_name: mp20
+  tolerance: 0.1
+  use_space_group: false
+  use_pos_index: false
+  train_max_epochs: 150
+  early_stopping_patience: 100000
+  teacher_forcing_max_epoch: 300
+  md_dataset_name: mptsubmpts52_uns_V0
+  root_path_md: ${oc.env:DATA_DIR}/${data.md_dataset_name}
+  require_order: false
+  prop_md:
+  - energy
+  - forces
+  energy_only: true
+  t_mode: c_learn
+  t_constant: 1.0
+  datamodule:
+    _target_: uniug.datamodule_uni.CrystDataModule
+    task_mode: uni
+    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}
+      train_md:
+        _target_: diffcsp.pl_data.dataset.CrystDataset
+        name: Formation energy train
+        path: ${data.root_path_md}/train.csv
+        save_path: ${data.root_path_md}/train_ori.pt
+        require_order: ${data.require_order}
+        prop: ${data.prop_md}
+        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_md:
+      - _target_: diffcsp.pl_data.dataset.CrystDataset
+        name: Formation energy val
+        path: ${data.root_path_md}/val.csv
+        save_path: ${data.root_path_md}/val_ori.pt
+        require_order: ${data.require_order}
+        prop: ${data.prop_md}
+        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: 64
+      val: 64
+      test: 64
+      train_md: 64
+      val_md: 64
+    pin_memory: true
+    persistent_workers: false
+    prefetch_factor: 2
+model:
+  w_csp: 0.95
+  w_pflow: 0.2
+  w_time: 0.1
+  cost_coord: 400.0
+  cost_lattice: 1.0
+  cost_type: 0.0
+  cost_energy: 1.0
+  cost_forces: 1.0
+  cost_stress: 1.0
+  affine_combine_costs: true
+  target_distribution: conditional
+  self_cond: false
+  t_pflow_clip: false
+  use_tangent: false
+  tclearn_freeze_epoch: 75
+  use_uns_flow_task: true
+  w_uns_flow: 0.02
+  w_consist: 0.02
+  uns_flow_tscale: true
+  uns_flow_tlearn: true
+  uns_path_refine: true
+  uns_path_t_clip: 0.9
+  use_consist_flow: true
+  consist_freeze_epoch: 129
+  uns_flow_freeze_epoch: 109
+  manifold_getter:
+    atom_type_manifold: null_manifold
+    coord_manifold: flat_torus_01
+    lattice_manifold: lattice_params
+    length_inner_coef: 1.0
+vectorfield:
+  _target_: uniug.arch_uni.FlowmmUniModel
+  force_pred_way: direct
+  use_pflow_head: true
+  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}
+  t_mode: ${data.t_mode}
+  t_mask: -1.0
+  use_pflow_task: false
+  tlearn_clip: false
+  learnable_time_emb: false

ckpt/mpts52_uns_PathRefine/.hydra/overrides.yaml

@@ -0,0 +1,35 @@
+- data=mpts52_mptsub
+- data.md_dataset_name=mptsubmpts52_uns_V0
+- model=null_params_uni
+- vectorfield=rfm_cspnet_uni
+- train.pl_trainer.num_nodes=1
+- train.pl_trainer.devices=4
+- data.datamodule.batch_size.train=64
+- data.datamodule.batch_size.train_md=64
+- data.datamodule.batch_size.val=64
+- data.datamodule.batch_size.val_md=64
+- data.datamodule.batch_size.test=64
+- logging.wandb.project=uniug_uni
+- logging.wandb.experiment_name=mpts52_uns_PathRefine_wuns0.02_wc0.02_e109_e129
+- data.energy_only=True
+- model.w_csp=0.95
+- optim.optimizer.lr=0.0005
+- train.pl_trainer.gradient_clip_val=10.0
+- train.pl_trainer.gradient_clip_algorithm=norm
+- data.t_mode=c_learn
+- model.tclearn_freeze_epoch=75
+- model.use_uns_flow_task=True
+- vectorfield.use_pflow_head=True
+- model.w_uns_flow=0.02
+- model.uns_flow_tscale=True
+- model.uns_flow_tlearn=True
+- data.train_max_epochs=150
+- logging.val_check_interval=5
+- train.every_n_epochs_checkpoint.every_n_epochs=5
+- model.uns_path_refine=True
+- model.uns_flow_freeze_epoch=109
+- model.use_consist_flow=True
+- model.consist_freeze_epoch=129
+- model.w_consist=0.02
+- partial_ckpt_load=True
+- partial_ckpt_path="/mnt/ai4sci_develop_fast/songyouli/crystal-uniug/runs/trash/uniug_uni/mpts52_uns_PathRefine_wuns0.02_e109/every_n_epochs/epoch=129-step=36225.ckpt"

ckpt/mpts52_uns_PathRefine/every_n_epochs/epoch=149-step=36225.ckpt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:90605d9e8308da574b5d2fd815371dfec7de74b976dd967b6993e702c3b4e86d
+size 227511286

ckpt/mpts52_uns_PathRefine/hparams.yaml

@@ -0,0 +1,250 @@
+core:
+  version: ${get_flowmm_version:}
+  tags:
+  - ${now:%Y-%m-%d}
+  - ⚡️pytorch lightning
+logging:
+  val_check_interval: 5
+  wandb:
+    project: uniug_uni
+    entity: null
+    log_model: true
+    mode: cloud
+    experiment_name: mpts52_uns_PathRefine_wuns0.02_wc0.02_e109_e129
+  wandb_watch:
+    log: all
+    log_freq: 500
+  lr_monitor:
+    logging_interval: step
+    log_momentum: false
+optim:
+  optimizer:
+    _target_: torch.optim.AdamW
+    lr: 0.0005
+    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
+    strategy: ddp_find_unused_parameters_true
+    num_nodes: 1
+    devices: 4
+    accelerator: gpu
+    precision: 32
+    max_epochs: ${data.train_max_epochs}
+    accumulate_grad_batches: 1
+    num_sanity_val_steps: 1
+    gradient_clip_val: 10.0
+    gradient_clip_algorithm: norm
+    profiler: simple
+    log_every_n_steps: 500
+  monitor_metric: val/loss_csp
+  monitor_metric_mode: min
+  model_checkpoints:
+    save_top_k: 1
+    verbose: false
+    save_last: false
+  every_n_epochs_checkpoint:
+    every_n_epochs: 5
+    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
+partial_ckpt_load: true
+partial_ckpt_path: /mnt/ai4sci_develop_fast/songyouli/crystal-uniug/runs/trash/uniug_uni/mpts52_uns_PathRefine_wuns0.02_e109/every_n_epochs/epoch=129-step=36225.ckpt
+data:
+  dataset_name: mpts_52
+  dim_coords: 3
+  root_path: ${oc.env:DATA_DIR}/mpts_52
+  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: 52
+  otf_graph: false
+  eval_model_name: mp20
+  tolerance: 0.1
+  use_space_group: false
+  use_pos_index: false
+  train_max_epochs: 150
+  early_stopping_patience: 100000
+  teacher_forcing_max_epoch: 300
+  md_dataset_name: mptsubmpts52_uns_V0
+  root_path_md: ${oc.env:DATA_DIR}/${data.md_dataset_name}
+  require_order: false
+  prop_md:
+  - energy
+  - forces
+  energy_only: true
+  t_mode: c_learn
+  t_constant: 1.0
+  datamodule:
+    _target_: uniug.datamodule_uni.CrystDataModule
+    task_mode: uni
+    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}
+      train_md:
+        _target_: diffcsp.pl_data.dataset.CrystDataset
+        name: Formation energy train
+        path: ${data.root_path_md}/train.csv
+        save_path: ${data.root_path_md}/train_ori.pt
+        require_order: ${data.require_order}
+        prop: ${data.prop_md}
+        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_md:
+      - _target_: diffcsp.pl_data.dataset.CrystDataset
+        name: Formation energy val
+        path: ${data.root_path_md}/val.csv
+        save_path: ${data.root_path_md}/val_ori.pt
+        require_order: ${data.require_order}
+        prop: ${data.prop_md}
+        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: 64
+      val: 64
+      test: 64
+      train_md: 64
+      val_md: 64
+    pin_memory: true
+    persistent_workers: false
+    prefetch_factor: 2
+model:
+  w_csp: 0.95
+  w_pflow: 0.2
+  w_time: 0.1
+  cost_coord: 400.0
+  cost_lattice: 1.0
+  cost_type: 0.0
+  cost_energy: 1.0
+  cost_forces: 1.0
+  cost_stress: 1.0
+  affine_combine_costs: true
+  target_distribution: conditional
+  self_cond: false
+  t_pflow_clip: false
+  use_tangent: false
+  tclearn_freeze_epoch: 75
+  use_uns_flow_task: true
+  w_uns_flow: 0.02
+  w_consist: 0.02
+  uns_flow_tscale: true
+  uns_flow_tlearn: true
+  uns_path_refine: true
+  uns_path_t_clip: 0.9
+  use_consist_flow: true
+  consist_freeze_epoch: 129
+  uns_flow_freeze_epoch: 109
+  manifold_getter:
+    atom_type_manifold: null_manifold
+    coord_manifold: flat_torus_01
+    lattice_manifold: lattice_params
+    length_inner_coef: 1.0
+vectorfield:
+  _target_: uniug.arch_uni.FlowmmUniModel
+  force_pred_way: direct
+  use_pflow_head: true
+  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}
+  t_mode: ${data.t_mode}
+  t_mask: -1.0
+  use_pflow_task: false
+  tlearn_clip: false
+  learnable_time_emb: false