Merge pull request #2 from shenoynikhil/so3-variants

[Do not Merge] Different SO3 Variant

.gitignore

@@ -9,6 +9,7 @@ wandb/
 logs/
 output/
 results/
+notebooks/
 
 # cache
 .pytest_cache/

configs/drugs-base.yaml

@@ -63,7 +63,7 @@ model_args:
     lr_scheduler_type: CosineAnnealingWarmupRestarts
     first_cycle_steps: 500_000
     cycle_mult: 1.0
-    max_lr: 8.e-4
+    max_lr: 5.e-4
     min_lr: 1.e-8
     warmup_steps: 0
     gamma: 0.05
@@ -98,8 +98,8 @@ logger_args:
 # trainer
 trainer: Trainer
 trainer_args:
-    max_epochs: 100
+    max_epochs: 200
     devices: 8
     limit_train_batches: 5000
-    strategy: ddp_find_unused_parameters_true
+    strategy: ddp
     accelerator: auto

configs/qm9-base.yaml

@@ -38,7 +38,7 @@ model_args:
     cutoff_lower: 0.0
     cutoff_upper: 10.0
     max_z: 100
-    node_attr_dim: 8
+    node_attr_dim: 10
     edge_attr_dim: 1
     attn_activation: silu
     num_heads: 8
@@ -47,12 +47,12 @@ model_args:
     qk_norm: true
     clip_during_norm: true
     so3_equivariant: true
-    output_layer_norm: false
+    output_layer_norm: true
 
     # flow matching specific
     normalize_node_invariants: false
     sigma: 0.1
-    prior_type: harmonic
+    prior_type: gaussian
     interpolation_type: linear
 
     # optimizer args
@@ -99,8 +99,8 @@ logger_args:
 # trainer
 trainer: Trainer
 trainer_args:
-    max_epochs: 250
+    max_epochs: 500
     devices: 4
     limit_train_batches: 1500
-    strategy: ddp_find_unused_parameters_true
+    strategy: ddp
     accelerator: auto

etflow/commons/__init__.py

@@ -1,14 +1,5 @@
 from .covmat import build_conformer
-from .featurization import (
-    MoleculeFeaturizer,
-    atom_to_feature_vector,
-    bond_to_feature_vector,
-    compute_edge_index,
-    extend_graph_order_radius,
-    get_atomic_number_and_charge,
-    get_chiral_tensors,
-    signed_volume,
-)
+from .featurization import MoleculeFeaturizer
 from .io import (
     get_local_cache,
     load_hdf5,
@@ -20,11 +11,14 @@
     save_pkl,
 )
 from .sample import batched_sampling
-from .utils import Queue
+from .utils import (
+    Queue,
+    extend_graph_order_radius,
+    get_atomic_number_and_charge,
+    signed_volume,
+)
 
 __all__ = [
-    "atom_to_feature_vector",
-    "bond_to_feature_vector",
     "MoleculeFeaturizer",
     "Queue",
     "load_json",
@@ -34,10 +28,8 @@
     "load_memmap",
     "load_hdf5",
     "save_memmap",
-    "get_chiral_tensors",
     "get_local_cache",
     "get_atomic_number_and_charge",
-    "compute_edge_index",
     "build_conformer",
     "extend_graph_order_radius",
     "batched_sampling",