Merge pull request #99 from usnistgov/develop

Fix atomwise default settings.

alignn/__init__.py

@@ -1,2 +1,2 @@
 """Version number."""
-__version__ = "2023.04.27"
+__version__ = "2023.04.30"

alignn/ff/config.json

@@ -14,7 +14,7 @@
     "val_ratio": 0.05,
     "test_ratio": 0.05,
     "target_multiplication_factor": null,
-    "epochs": 500,
+    "epochs": 100,
     "batch_size": 16,
     "weight_decay": 1e-05,
     "learning_rate": 0.001,
@@ -52,7 +52,7 @@
         "output_features": 1,
         "grad_multiplier": -1,
         "calculate_gradient": true,
-        "atomwise_output_features": 3,
+        "atomwise_output_features": 0,
         "graphwise_weight": 1.0,
         "gradwise_weight": 10.0,
         "stresswise_weight": 0.0,
@@ -61,4 +61,4 @@
         "zero_inflated": false,
         "classification": false
     }
-}
+}

alignn/models/alignn_atomwise.py

@@ -34,7 +34,7 @@ class ALIGNNAtomWiseConfig(BaseSettings):
     output_features: int = 1
     grad_multiplier: int = -1
     calculate_gradient: bool = True
-    atomwise_output_features: int = 3
+    atomwise_output_features: int = 0
     graphwise_weight: float = 1.0
     gradwise_weight: float = 0.0
     stresswise_weight: float = 0.0

alignn/train.py

@@ -395,7 +395,8 @@ def get_batch_errors(dat=[]):
                     # )
 
                 if (
-                    config.model.atomwise_output_features is not None
+                    config.model.atomwise_output_features > 0
+                    # config.model.atomwise_output_features is not None
                     and config.model.atomwise_weight != 0
                 ):
                     loss2 = config.model.atomwise_weight * criterion(
@@ -514,7 +515,7 @@ def get_batch_errors(dat=[]):
                         result["out"].cpu().detach().numpy().tolist()
                     )
                 if (
-                    config.model.atomwise_output_features is not None
+                    config.model.atomwise_output_features > 0
                     and config.model.atomwise_weight != 0
                 ):
                     loss2 = config.model.atomwise_weight * criterion(
@@ -622,7 +623,7 @@ def get_batch_errors(dat=[]):
                     result["out"].cpu().detach().numpy().tolist()
                 )
 
-            if config.model.atomwise_output_features is not None:
+            if config.model.atomwise_output_features > 0:
                 loss2 = config.model.atomwise_weight * criterion(
                     result["atomwise_pred"].to(device),
                     dats[0].ndata["atomwise_target"].to(device),

setup.py

@@ -10,7 +10,7 @@
 
 setuptools.setup(
     name="alignn",
-    version="2023.04.27",
+    version="2023.04.30",
     author="Kamal Choudhary, Brian DeCost",
     author_email="kamal.choudhary@nist.gov",
     description="alignn",