Small fix to uncertainty computation and added docs/requirements.

muammar · Feb 15, 2020 · 641e4eb · 641e4eb
1 parent 2c30d53
commit 641e4eb
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diff --git a/docs/requirements.txt b/docs/requirements.txt
@@ -0,0 +1,15 @@
+joblib
+seaborn
+dask_ml
+ase
+scipy
+numpy
+pip
+pandas
+plotly
+pytest
+msgpack_numpy
+matplotlib
+dscribe
+msgpack_python
+scikit_learn
diff --git a/docs/source/ml4chem.atomistic.models.rst b/docs/source/ml4chem.atomistic.models.rst
@@ -60,6 +60,14 @@ ml4chem.atomistic.models.neuralnetwork module
     :undoc-members:
     :show-inheritance:
 
+ml4chem.atomistic.models.rt module
+----------------------------------
+
+.. automodule:: ml4chem.atomistic.models.rt
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
 ml4chem.atomistic.models.se3net module
 --------------------------------------
 

diff --git a/ml4chem/atomistic/models/loss.py b/ml4chem/atomistic/models/loss.py
@@ -38,7 +38,7 @@ def AtomicMSELoss(outputs, targets, atoms_per_image, uncertainty=None):
         outputs_atom = torch.div(outputs, atoms_per_image)
         targets_atom = torch.div(targets, atoms_per_image)
         loss = (
-            criterion(outputs_atom, targets_atom) / (2 * torch.pow(uncertainty, 1))
+            criterion(outputs_atom, targets_atom) / (2 * torch.pow(uncertainty, 2))
         ).sum() * 0.5
     return loss