Upload InvDesMobility artifact release

README.md

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+---
+library_name: pytorch
+tags:
+- materials-science
+- crystal-generation
+- graph-ml
+- diffusion-model
+- diffcsp
+- inverse-design
+license: other
+---
+
+# InvDesMobility DiffCSP Generator Checkpoints
+
+This repository contains the DiffCSP generator checkpoints used by the
+InvDesMobility inverse-design workflow. The checkpoints are released as
+external artifacts for the code repositories:
+
+- https://github.com/DreamLufei/invDesMobility
+- https://github.com/DreamLufei/invdesmobility_loop
+- https://github.com/DreamLufei/2d-mobility
+
+## Files
+
+- `pretrained/PretrainGenerationModel.ckpt`: upstream DiffCSP warm-start checkpoint used by the pipeline.
+- `finetuned/mobility2d_highquality280_ft_v1/best.ckpt`: seed mobility-2D fine-tuned generator.
+- `finetuned/generator_round_XX/best.ckpt`: closed-loop feedback fine-tuned generators for rounds 01, 02, 03, 04, 06, 07, 08, and 09.
+- Each fine-tuned directory also includes `hparams.yaml`, `lattice_scaler.pt`, and `prop_scaler.pt`.
+
+The `epoch=...ckpt` files from local training logs are intentionally omitted because
+they are byte-identical to the retained `best.ckpt` files for the corresponding
+rounds. Run logs, W&B files, generated pools, and VASP outputs are not included.
+
+## Intended Use
+
+These checkpoints are intended for reproducing the candidate-generation stage of
+InvDesMobility and for research use in feedback-guided 2D crystal generation.
+
+## Training Data
+
+The seed model was fine-tuned on the mobility-2D high-quality seed dataset.
+Closed-loop checkpoints were fine-tuned on feedback-augmented DiffCSP datasets
+constructed from trusted first-principles mobility-validation records.
+
+The matching datasets are packaged separately in `DreamLufei/invDesMobility-data`.
+
+## Training Parameters
+
+The retained `hparams.yaml` files contain the exact DiffCSP/PyTorch Lightning
+configuration for each checkpoint, including model architecture, dataset path,
+batch size, optimization configuration, and diffusion scheduler settings.
+
+Key settings used by the feedback models include:
+
+- DiffCSP `CSPDiffusion` with `CSPNet` decoder.
+- `hidden_dim=512`, `num_layers=6`, `max_neighbors=20`, `radius=7.0`.
+- Fine-tuning via the project scripts under `05_steps/02_finetune_generator/` and
+  `05_steps/09_closed_loop_feedback/`.
+
+## Limitations
+
+The generator proposes candidate structures; it does not validate mobility,
+dynamic stability, synthesizability, or DFT-level electronic structure. Candidate
+structures require downstream deduplication, surrogate screening, and
+first-principles validation with the companion `2d-mobility` workflow.
+
+## Citation
+
+If you use these checkpoints, please cite the InvDesMobility manuscript and the
+associated GitHub repositories above.

finetuned/generator_round_01/best.ckpt

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finetuned/generator_round_01/hparams.yaml

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+data:
+  root_path: /home/wkli/invDesMobility/01_code/InvDesFlow/data/mobility2d_feedback_round_01
+  prop: formation_energy_per_atom
+  num_targets: 1
+  niggli: true
+  primitive: false
+  graph_method: crystalnn
+  lattice_scale_method: scale_length
+  preprocess_workers: 8
+  readout: mean
+  max_atoms: 36
+  otf_graph: false
+  eval_model_name: mp20
+  tolerance: 0.1
+  use_space_group: false
+  use_pos_index: false
+  train_max_epochs: 1000
+  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: 0
+      val: 0
+      test: 0
+    batch_size:
+      train: 256
+      val: 128
+      test: 128
+logging:
+  val_check_interval: 5
+  progress_bar_refresh_rate: 1
+  wandb:
+    name: ${expname}
+    project: diffcsp
+    entity: null
+    log_model: true
+    mode: offline
+    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
+    max_atoms: 100
+    num_layers: 6
+    act_fn: silu
+    dis_emb: sin
+    num_freqs: 128
+    edge_style: fc
+    max_neighbors: ${model.max_neighbors}
+    cutoff: ${model.radius}
+    ln: true
+    ip: true
+  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
+  _target_: diffcsp.pl_modules.diffusion_w_type.CSPDiffusion
+  time_dim: 256
+  latent_dim: 0
+  cost_coord: 1.0
+  cost_lattice: 1.0
+  cost_type: 20.0
+  max_neighbors: 20
+  radius: 7.0
+  timesteps: 1000
+optim:
+  optimizer:
+    _target_: torch.optim.Adam
+    lr: 5.0e-05
+    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
+  pl_trainer:
+    fast_dev_run: false
+    gpus: 1
+    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
+    profiler: simple
+  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
+  init_from_ckpt: /home/wkli/invDesMobility/04_models/01_diffcsp_generator/pretrained/PretrainGenerationModel.ckpt
+  init_strict: true
+expname: mobility2d_highquality280_ft_v1
+core:
+  version: 0.0.1
+  tags:
+  - ${now:%Y-%m-%d}

finetuned/generator_round_01/lattice_scaler.pt

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finetuned/generator_round_01/prop_scaler.pt

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finetuned/generator_round_02/best.ckpt

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finetuned/generator_round_02/hparams.yaml

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+data:
+  root_path: /home/wkli/invDesMobility/01_code/InvDesFlow/data/mobility2d_feedback_round_02
+  prop: formation_energy_per_atom
+  num_targets: 1
+  niggli: true
+  primitive: false
+  graph_method: crystalnn
+  lattice_scale_method: scale_length
+  preprocess_workers: 8
+  readout: mean
+  max_atoms: 36
+  otf_graph: false
+  eval_model_name: mp20
+  tolerance: 0.1
+  use_space_group: false
+  use_pos_index: false
+  train_max_epochs: 1000
+  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: 0
+      val: 0
+      test: 0
+    batch_size:
+      train: 256
+      val: 128
+      test: 128
+logging:
+  val_check_interval: 5
+  progress_bar_refresh_rate: 1
+  wandb:
+    name: ${expname}
+    project: diffcsp
+    entity: null
+    log_model: true
+    mode: offline
+    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
+    max_atoms: 100
+    num_layers: 6
+    act_fn: silu
+    dis_emb: sin
+    num_freqs: 128
+    edge_style: fc
+    max_neighbors: ${model.max_neighbors}
+    cutoff: ${model.radius}
+    ln: true
+    ip: true
+  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
+  _target_: diffcsp.pl_modules.diffusion_w_type.CSPDiffusion
+  time_dim: 256
+  latent_dim: 0
+  cost_coord: 1.0
+  cost_lattice: 1.0
+  cost_type: 20.0
+  max_neighbors: 20
+  radius: 7.0
+  timesteps: 1000
+optim:
+  optimizer:
+    _target_: torch.optim.Adam
+    lr: 5.0e-05
+    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
+  pl_trainer:
+    fast_dev_run: false
+    gpus: 1
+    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
+    profiler: simple
+  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
+  init_from_ckpt: /home/wkli/invDesMobility/04_models/01_diffcsp_generator/pretrained/PretrainGenerationModel.ckpt
+  init_strict: true
+expname: mobility2d_highquality280_ft_v1
+core:
+  version: 0.0.1
+  tags:
+  - ${now:%Y-%m-%d}

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finetuned/generator_round_03/hparams.yaml

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+data:
+  root_path: /home/wkli/invDesMobility/01_code/InvDesFlow/data/mobility2d_feedback_round_03
+  prop: formation_energy_per_atom
+  num_targets: 1
+  niggli: true
+  primitive: false
+  graph_method: crystalnn
+  lattice_scale_method: scale_length
+  preprocess_workers: 8
+  readout: mean
+  max_atoms: 36
+  otf_graph: false
+  eval_model_name: mp20
+  tolerance: 0.1
+  use_space_group: false
+  use_pos_index: false
+  train_max_epochs: 1000
+  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: 0
+      val: 0
+      test: 0
+    batch_size:
+      train: 256
+      val: 128
+      test: 128
+logging:
+  val_check_interval: 5
+  progress_bar_refresh_rate: 1
+  wandb:
+    name: ${expname}
+    project: diffcsp
+    entity: null
+    log_model: true
+    mode: offline
+    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
+    max_atoms: 100
+    num_layers: 6
+    act_fn: silu
+    dis_emb: sin
+    num_freqs: 128
+    edge_style: fc
+    max_neighbors: ${model.max_neighbors}
+    cutoff: ${model.radius}
+    ln: true
+    ip: true
+  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
+  _target_: diffcsp.pl_modules.diffusion_w_type.CSPDiffusion
+  time_dim: 256
+  latent_dim: 0
+  cost_coord: 1.0
+  cost_lattice: 1.0
+  cost_type: 20.0
+  max_neighbors: 20
+  radius: 7.0
+  timesteps: 1000
+optim:
+  optimizer:
+    _target_: torch.optim.Adam
+    lr: 5.0e-05
+    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
+  pl_trainer:
+    fast_dev_run: false
+    gpus: 1
+    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
+    profiler: simple
+  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
+  init_from_ckpt: /home/wkli/invDesMobility/04_models/01_diffcsp_generator/pretrained/PretrainGenerationModel.ckpt
+  init_strict: true
+expname: mobility2d_highquality280_ft_v1
+core:
+  version: 0.0.1
+  tags:
+  - ${now:%Y-%m-%d}

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finetuned/generator_round_04/hparams.yaml

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+data:
+  root_path: /home/wkli/invDesMobility/01_code/InvDesFlow/data/mobility2d_feedback_round_04
+  prop: formation_energy_per_atom
+  num_targets: 1
+  niggli: true
+  primitive: false
+  graph_method: crystalnn
+  lattice_scale_method: scale_length
+  preprocess_workers: 8
+  readout: mean
+  max_atoms: 36
+  otf_graph: false
+  eval_model_name: mp20
+  tolerance: 0.1
+  use_space_group: false
+  use_pos_index: false
+  train_max_epochs: 1000
+  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: 0
+      val: 0
+      test: 0
+    batch_size:
+      train: 256
+      val: 128
+      test: 128
+logging:
+  val_check_interval: 5
+  progress_bar_refresh_rate: 1
+  wandb:
+    name: ${expname}
+    project: diffcsp
+    entity: null
+    log_model: true
+    mode: offline
+    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
+    max_atoms: 100
+    num_layers: 6
+    act_fn: silu
+    dis_emb: sin
+    num_freqs: 128
+    edge_style: fc
+    max_neighbors: ${model.max_neighbors}
+    cutoff: ${model.radius}
+    ln: true
+    ip: true
+  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
+  _target_: diffcsp.pl_modules.diffusion_w_type.CSPDiffusion
+  time_dim: 256
+  latent_dim: 0
+  cost_coord: 1.0
+  cost_lattice: 1.0
+  cost_type: 20.0
+  max_neighbors: 20
+  radius: 7.0
+  timesteps: 1000
+optim:
+  optimizer:
+    _target_: torch.optim.Adam
+    lr: 5.0e-05
+    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
+  pl_trainer:
+    fast_dev_run: false
+    gpus: 1
+    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
+    profiler: simple
+  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
+  init_from_ckpt: /home/wkli/invDesMobility/04_models/01_diffcsp_generator/pretrained/PretrainGenerationModel.ckpt
+  init_strict: true
+expname: mobility2d_highquality280_ft_v1
+core:
+  version: 0.0.1
+  tags:
+  - ${now:%Y-%m-%d}

finetuned/generator_round_04/lattice_scaler.pt

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finetuned/generator_round_04/prop_scaler.pt

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finetuned/generator_round_06/best.ckpt

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finetuned/generator_round_06/hparams.yaml

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+data:
+  root_path: /home/wkli/invDesMobility/01_code/InvDesFlow/data/mobility2d_feedback_round_06
+  prop: formation_energy_per_atom
+  num_targets: 1
+  niggli: true
+  primitive: false
+  graph_method: crystalnn
+  lattice_scale_method: scale_length
+  preprocess_workers: 8
+  readout: mean
+  max_atoms: 36
+  otf_graph: false
+  eval_model_name: mp20
+  tolerance: 0.1
+  use_space_group: false
+  use_pos_index: false
+  train_max_epochs: 1000
+  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: 0
+      val: 0
+      test: 0
+    batch_size:
+      train: 256
+      val: 128
+      test: 128
+logging:
+  val_check_interval: 5
+  progress_bar_refresh_rate: 1
+  wandb:
+    name: ${expname}
+    project: diffcsp
+    entity: null
+    log_model: true
+    mode: offline
+    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
+    max_atoms: 100
+    num_layers: 6
+    act_fn: silu
+    dis_emb: sin
+    num_freqs: 128
+    edge_style: fc
+    max_neighbors: ${model.max_neighbors}
+    cutoff: ${model.radius}
+    ln: true
+    ip: true
+  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
+  _target_: diffcsp.pl_modules.diffusion_w_type.CSPDiffusion
+  time_dim: 256
+  latent_dim: 0
+  cost_coord: 1.0
+  cost_lattice: 1.0
+  cost_type: 20.0
+  max_neighbors: 20
+  radius: 7.0
+  timesteps: 1000
+optim:
+  optimizer:
+    _target_: torch.optim.Adam
+    lr: 5.0e-05
+    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
+  pl_trainer:
+    fast_dev_run: false
+    gpus: 1
+    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
+    profiler: simple
+  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
+  init_from_ckpt: /home/wkli/invDesMobility/04_models/01_diffcsp_generator/pretrained/PretrainGenerationModel.ckpt
+  init_strict: true
+expname: mobility2d_highquality280_ft_v1
+core:
+  version: 0.0.1
+  tags:
+  - ${now:%Y-%m-%d}

finetuned/generator_round_06/lattice_scaler.pt

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+size 1063

finetuned/generator_round_06/prop_scaler.pt

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finetuned/generator_round_07/best.ckpt

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finetuned/generator_round_07/hparams.yaml

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+data:
+  root_path: /home/wkli/invDesMobility/01_code/InvDesFlow/data/mobility2d_feedback_round_07
+  prop: formation_energy_per_atom
+  num_targets: 1
+  niggli: true
+  primitive: false
+  graph_method: crystalnn
+  lattice_scale_method: scale_length
+  preprocess_workers: 8
+  readout: mean
+  max_atoms: 36
+  otf_graph: false
+  eval_model_name: mp20
+  tolerance: 0.1
+  use_space_group: false
+  use_pos_index: false
+  train_max_epochs: 1000
+  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: 0
+      val: 0
+      test: 0
+    batch_size:
+      train: 256
+      val: 128
+      test: 128
+logging:
+  val_check_interval: 5
+  progress_bar_refresh_rate: 1
+  wandb:
+    name: ${expname}
+    project: diffcsp
+    entity: null
+    log_model: true
+    mode: offline
+    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
+    max_atoms: 100
+    num_layers: 6
+    act_fn: silu
+    dis_emb: sin
+    num_freqs: 128
+    edge_style: fc
+    max_neighbors: ${model.max_neighbors}
+    cutoff: ${model.radius}
+    ln: true
+    ip: true
+  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
+  _target_: diffcsp.pl_modules.diffusion_w_type.CSPDiffusion
+  time_dim: 256
+  latent_dim: 0
+  cost_coord: 1.0
+  cost_lattice: 1.0
+  cost_type: 20.0
+  max_neighbors: 20
+  radius: 7.0
+  timesteps: 1000
+optim:
+  optimizer:
+    _target_: torch.optim.Adam
+    lr: 5.0e-05
+    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
+  pl_trainer:
+    fast_dev_run: false
+    gpus: 1
+    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
+    profiler: simple
+  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
+  init_from_ckpt: /home/wkli/invDesMobility/04_models/01_diffcsp_generator/pretrained/PretrainGenerationModel.ckpt
+  init_strict: true
+expname: mobility2d_highquality280_ft_v1
+core:
+  version: 0.0.1
+  tags:
+  - ${now:%Y-%m-%d}

finetuned/generator_round_07/lattice_scaler.pt

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finetuned/generator_round_07/prop_scaler.pt

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finetuned/generator_round_08/best.ckpt

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finetuned/generator_round_08/hparams.yaml

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+data:
+  root_path: /home/wkli/invDesMobility/01_code/InvDesFlow/data/mobility2d_feedback_round_08
+  prop: formation_energy_per_atom
+  num_targets: 1
+  niggli: true
+  primitive: false
+  graph_method: crystalnn
+  lattice_scale_method: scale_length
+  preprocess_workers: 8
+  readout: mean
+  max_atoms: 36
+  otf_graph: false
+  eval_model_name: mp20
+  tolerance: 0.1
+  use_space_group: false
+  use_pos_index: false
+  train_max_epochs: 1000
+  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: 0
+      val: 0
+      test: 0
+    batch_size:
+      train: 256
+      val: 128
+      test: 128
+logging:
+  val_check_interval: 5
+  progress_bar_refresh_rate: 1
+  wandb:
+    name: ${expname}
+    project: diffcsp
+    entity: null
+    log_model: true
+    mode: offline
+    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
+    max_atoms: 100
+    num_layers: 6
+    act_fn: silu
+    dis_emb: sin
+    num_freqs: 128
+    edge_style: fc
+    max_neighbors: ${model.max_neighbors}
+    cutoff: ${model.radius}
+    ln: true
+    ip: true
+  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
+  _target_: diffcsp.pl_modules.diffusion_w_type.CSPDiffusion
+  time_dim: 256
+  latent_dim: 0
+  cost_coord: 1.0
+  cost_lattice: 1.0
+  cost_type: 20.0
+  max_neighbors: 20
+  radius: 7.0
+  timesteps: 1000
+optim:
+  optimizer:
+    _target_: torch.optim.Adam
+    lr: 5.0e-05
+    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
+  pl_trainer:
+    fast_dev_run: false
+    gpus: 1
+    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
+    profiler: simple
+  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
+  init_from_ckpt: /home/wkli/invDesMobility/04_models/01_diffcsp_generator/pretrained/PretrainGenerationModel.ckpt
+  init_strict: true
+expname: mobility2d_highquality280_ft_v1
+core:
+  version: 0.0.1
+  tags:
+  - ${now:%Y-%m-%d}

finetuned/generator_round_08/lattice_scaler.pt

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finetuned/generator_round_08/prop_scaler.pt

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finetuned/generator_round_09/best.ckpt

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finetuned/generator_round_09/hparams.yaml

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+data:
+  root_path: /home/wkli/invDesMobility/01_code/InvDesFlow/data/mobility2d_feedback_round_09
+  prop: formation_energy_per_atom
+  num_targets: 1
+  niggli: true
+  primitive: false
+  graph_method: crystalnn
+  lattice_scale_method: scale_length
+  preprocess_workers: 8
+  readout: mean
+  max_atoms: 36
+  otf_graph: false
+  eval_model_name: mp20
+  tolerance: 0.1
+  use_space_group: false
+  use_pos_index: false
+  train_max_epochs: 1000
+  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: 0
+      val: 0
+      test: 0
+    batch_size:
+      train: 256
+      val: 128
+      test: 128
+logging:
+  val_check_interval: 5
+  progress_bar_refresh_rate: 1
+  wandb:
+    name: ${expname}
+    project: diffcsp
+    entity: null
+    log_model: true
+    mode: offline
+    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
+    max_atoms: 100
+    num_layers: 6
+    act_fn: silu
+    dis_emb: sin
+    num_freqs: 128
+    edge_style: fc
+    max_neighbors: ${model.max_neighbors}
+    cutoff: ${model.radius}
+    ln: true
+    ip: true
+  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
+  _target_: diffcsp.pl_modules.diffusion_w_type.CSPDiffusion
+  time_dim: 256
+  latent_dim: 0
+  cost_coord: 1.0
+  cost_lattice: 1.0
+  cost_type: 20.0
+  max_neighbors: 20
+  radius: 7.0
+  timesteps: 1000
+optim:
+  optimizer:
+    _target_: torch.optim.Adam
+    lr: 5.0e-05
+    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
+  pl_trainer:
+    fast_dev_run: false
+    gpus: 1
+    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
+    profiler: simple
+  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
+  init_from_ckpt: /home/wkli/invDesMobility/04_models/01_diffcsp_generator/pretrained/PretrainGenerationModel.ckpt
+  init_strict: true
+expname: mobility2d_highquality280_ft_v1
+core:
+  version: 0.0.1
+  tags:
+  - ${now:%Y-%m-%d}

finetuned/generator_round_09/lattice_scaler.pt

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finetuned/generator_round_09/prop_scaler.pt

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finetuned/mobility2d_highquality280_ft_v1/hparams.yaml

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+data:
+  root_path: /home/wkli/invDesMobility/InvDesFlow/data/mobility2d_highquality280
+  prop: formation_energy_per_atom
+  num_targets: 1
+  niggli: true
+  primitive: false
+  graph_method: crystalnn
+  lattice_scale_method: scale_length
+  preprocess_workers: 8
+  readout: mean
+  max_atoms: 36
+  otf_graph: false
+  eval_model_name: mp20
+  tolerance: 0.1
+  use_space_group: false
+  use_pos_index: false
+  train_max_epochs: 1000
+  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: 0
+      val: 0
+      test: 0
+    batch_size:
+      train: 256
+      val: 128
+      test: 128
+logging:
+  val_check_interval: 5
+  progress_bar_refresh_rate: 1
+  wandb:
+    name: ${expname}
+    project: diffcsp
+    entity: null
+    log_model: true
+    mode: offline
+    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
+    max_atoms: 100
+    num_layers: 6
+    act_fn: silu
+    dis_emb: sin
+    num_freqs: 128
+    edge_style: fc
+    max_neighbors: ${model.max_neighbors}
+    cutoff: ${model.radius}
+    ln: true
+    ip: true
+  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
+  _target_: diffcsp.pl_modules.diffusion_w_type.CSPDiffusion
+  time_dim: 256
+  latent_dim: 0
+  cost_coord: 1.0
+  cost_lattice: 1.0
+  cost_type: 20.0
+  max_neighbors: 20
+  radius: 7.0
+  timesteps: 1000
+optim:
+  optimizer:
+    _target_: torch.optim.Adam
+    lr: 5.0e-05
+    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
+  pl_trainer:
+    fast_dev_run: false
+    gpus: 1
+    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
+    profiler: simple
+  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
+  init_from_ckpt: /home/wkli/invDesMobility/PretrainGenerationModel.ckpt
+  init_strict: true
+expname: mobility2d_highquality280_ft_v1
+core:
+  version: 0.0.1
+  tags:
+  - ${now:%Y-%m-%d}

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