Permutation in analytical score

data/process_lammps_data.py

@@ -3,8 +3,8 @@
 import logging
 import tempfile
 
-from diffusion_for_multi_scale_molecular_dynamics.data.diffusion.data_loader import (
-    LammpsForDiffusionDataModule, LammpsLoaderParameters)
+from diffusion_for_multi_scale_molecular_dynamics.data.diffusion.lammps_for_diffusion_data_module import (
+    LammpsDataModuleParameters, LammpsForDiffusionDataModule)
 from diffusion_for_multi_scale_molecular_dynamics.utils.logging_utils import \
     setup_analysis_logger
 from diffusion_for_multi_scale_molecular_dynamics.utils.main_utils import \
@@ -31,7 +31,7 @@ def main():
     logger.info(f"   --processed_datadir : {args.processed_datadir}")
     logger.info(f"   --config: {args.config}")
 
-    data_params = LammpsLoaderParameters(**hyper_params)
+    data_params = LammpsDataModuleParameters(**hyper_params)
 
     with tempfile.TemporaryDirectory() as tmp_work_dir:
         data_module = LammpsForDiffusionDataModule(lammps_run_dir=lammps_run_dir,

examples/config_files/diffusion/config_diffusion_egnn_2_atoms_in_1D.yaml

@@ -0,0 +1,117 @@
+#================================================================================
+# Configuration file for a diffusion experiment for 2 pseudo-atoms in 1D.
+#
+# An 'on-the-fly' Gaussian dataset is created and used for training.
+#================================================================================
+exp_name: egnn_2_atoms_in_1D
+run_name: run1
+max_epoch: 1000
+log_every_n_steps: 1
+gradient_clipping: 0.0
+accumulate_grad_batches: 1  # make this number of forward passes before doing a backprop step
+
+elements: [A]
+
+# set to null to avoid setting a seed (can speed up GPU computation, but
+# results will not be reproducible)
+seed: 1234
+
+# On-the-fly Data Module that creates a Gaussian dataset.
+data:
+  data_source: gaussian
+  random_seed: 42
+  number_of_atoms: 2
+  sigma_d: 0.01
+  equilibrium_relative_coordinates: 
+    - [0.25]
+    - [0.75]
+
+  train_dataset_size: 8_192
+  valid_dataset_size: 1_024
+
+  batch_size:  64 
+  num_workers: 0
+  max_atom: 2
+  spatial_dimension: 1
+
+
+spatial_dimension: 1
+
+model:
+  loss:
+    coordinates_algorithm: mse
+    atom_types_ce_weight: 0.0
+    atom_types_lambda_weight: 0.0
+    relative_coordinates_lambda_weight: 1.0
+    lattice_lambda_weight: 0.0  
+  score_network:
+    architecture: egnn
+    spatial_dimension: 1
+    num_atom_types: 1
+    n_layers: 4
+    coordinate_hidden_dimensions_size: 128
+    coordinate_n_hidden_dimensions: 4
+    coords_agg: "mean"
+    message_hidden_dimensions_size: 128
+    message_n_hidden_dimensions: 4
+    node_hidden_dimensions_size: 128
+    node_n_hidden_dimensions: 4
+    attention: False
+    normalize: True
+    residual: True
+    tanh: False
+    edges: fully_connected
+  noise:
+    total_time_steps: 100
+    sigma_min: 0.001 
+    sigma_max: 0.2
+
+# optimizer and scheduler
+optimizer:
+  name: adamw
+  learning_rate: 0.001
+  weight_decay: 5.0e-8
+
+
+scheduler:
+  name: CosineAnnealingLR
+  T_max: 1000
+  eta_min: 0.0
+
+# early stopping
+early_stopping:
+  metric: validation_epoch_loss
+  mode: min
+  patience: 1000
+
+model_checkpoint:
+  monitor: validation_epoch_loss
+  mode: min
+
+score_viewer:
+  record_every_n_epochs: 1
+
+  score_viewer_parameters: 
+    sigma_min: 0.001 
+    sigma_max: 0.2
+    number_of_space_steps: 100
+    starting_relative_coordinates: 
+      - [0.0]
+      - [1.0]
+    ending_relative_coordinates: 
+      - [1.0]
+      - [0.0]
+  analytical_score_network:
+    architecture: "analytical"
+    spatial_dimension: 1
+    number_of_atoms: 2
+    num_atom_types: 1
+    kmax: 5
+    equilibrium_relative_coordinates: 
+      - [0.25]
+      - [0.75]
+    sigma_d: 0.01
+    use_permutation_invariance: True
+
+logging:
+  - tensorboard

experiments/atom_types_only_experiments/patches/fixed_position_data_loader.py

@@ -7,8 +7,8 @@
 from equilibrium_structure import create_equilibrium_sige_structure
 from torch_geometric.data import DataLoader
 
-from diffusion_for_multi_scale_molecular_dynamics.data.diffusion.data_loader import \
-    LammpsLoaderParameters
+from diffusion_for_multi_scale_molecular_dynamics.data.diffusion.lammps_for_diffusion_data_module import \
+    LammpsDataModuleParameters
 from diffusion_for_multi_scale_molecular_dynamics.data.element_types import \
     ElementTypes
 from diffusion_for_multi_scale_molecular_dynamics.namespace import (
@@ -24,7 +24,7 @@ def __init__(
         self,
         lammps_run_dir: str,  # dummy
         processed_dataset_dir: str,
-        hyper_params: LammpsLoaderParameters,
+        hyper_params: LammpsDataModuleParameters,
         working_cache_dir: Optional[str] = None,  # dummy
     ):
         """Init method."""
@@ -99,7 +99,7 @@ def clean_up(self):
     elements = ["Si", "Ge"]
     processed_dataset_dir = Path("/experiments/atom_types_only_experiments")
 
-    hyper_params = LammpsLoaderParameters(
+    hyper_params = LammpsDataModuleParameters(
         batch_size=64,
         train_batch_size=1024,
         valid_batch_size=1024,

experiments/dataset_analysis/dataset_covariance.py

@@ -13,8 +13,8 @@
 
 from diffusion_for_multi_scale_molecular_dynamics import (ANALYSIS_RESULTS_DIR,
                                                           DATA_DIR)
-from diffusion_for_multi_scale_molecular_dynamics.data.diffusion.data_loader import (
-    LammpsForDiffusionDataModule, LammpsLoaderParameters)
+from diffusion_for_multi_scale_molecular_dynamics.data.diffusion.lammps_for_diffusion_data_module import (
+    LammpsDataModuleParameters, LammpsForDiffusionDataModule)
 from diffusion_for_multi_scale_molecular_dynamics.utils.basis_transformations import \
     map_relative_coordinates_to_unit_cell
 from diffusion_for_multi_scale_molecular_dynamics.utils.logging_utils import \
@@ -40,7 +40,7 @@
 
 cache_dir = lammps_run_dir / "cache"
 
-data_params = LammpsLoaderParameters(batch_size=2048, max_atom=max_atom)
+data_params = LammpsDataModuleParameters(batch_size=2048, max_atom=max_atom)
 
 if __name__ == "__main__":
     setup_analysis_logger()

experiments/dataset_analysis/energy_consistency_analysis.py

@@ -19,8 +19,8 @@
     PLEASANT_FIG_SIZE, PLOT_STYLE_PATH)
 from diffusion_for_multi_scale_molecular_dynamics.callbacks.sampling_visualization_callback import \
     SamplingVisualizationCallback
-from diffusion_for_multi_scale_molecular_dynamics.data.diffusion.data_loader import (
-    LammpsForDiffusionDataModule, LammpsLoaderParameters)
+from diffusion_for_multi_scale_molecular_dynamics.data.diffusion.lammps_for_diffusion_data_module import (
+    LammpsDataModuleParameters, LammpsForDiffusionDataModule)
 from diffusion_for_multi_scale_molecular_dynamics.oracle.lammps import \
     get_energy_and_forces_from_lammps
 from diffusion_for_multi_scale_molecular_dynamics.utils.logging_utils import \
@@ -38,7 +38,7 @@
 
 cache_dir = str(EXPERIMENT_ANALYSIS_DIR / "cache" / dataset_name)
 
-data_params = LammpsLoaderParameters(batch_size=64, max_atom=8)
+data_params = LammpsDataModuleParameters(batch_size=64, max_atom=8)
 
 sample_size = 1000