update formatting

CHANGELOG.md

@@ -23,7 +23,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added the `use_pcst` option to `WebQSPDataset` ([#9722](https://github.com/pyg-team/pytorch_geometric/pull/9722))
 - Allowed users to pass `edge_weight` to `GraphUNet` models ([#9737](https://github.com/pyg-team/pytorch_geometric/pull/9737))
 - Consolidated `examples/ogbn_{papers_100m,products_gat,products_sage}.py` into `examples/ogbn_train.py` ([#9467](https://github.com/pyg-team/pytorch_geometric/pull/9467))
-- Added the `TransF` KGE model ([#9858](https://github.com/pyg-team/pytorch_geometric/pull/9858))
+- Added the `TransF` KGE model ([#9880](https://github.com/pyg-team/pytorch_geometric/pull/9880))
 
 ### Changed
 

torch_geometric/nn/kge/transf.py

@@ -14,17 +14,23 @@ class TransF(KGEModel):
     scaling the relation vector based on head and tail entity embeddings, resulting in:
 
     .. math::
-        \mathbf{e}_h + f(\mathbf{e}_h, \mathbf{e}_t, \mathbf{e}_r) \cdot \mathbf{e}_r \approx \mathbf{e}_t
+        \mathbf{e}_h + f(\mathbf{e}_h, \mathbf{e}_t, \mathbf{e}_r)
+    .. math::
+        \cdot \mathbf{e}_r \approx \mathbf{e}_t
 
     where :math:`f` is a dynamic scaling function:
 
     .. math::
-        f(\mathbf{e}_h, \mathbf{e}_t, \mathbf{e}_r) = \sigma((\mathbf{e}_h \odot \mathbf{e}_t) \cdot \mathbf{e}_r)
+        f(\mathbf{e}_h, \mathbf{e}_t, \mathbf{e}_r) =
+    .. math::
+        \sigma((\mathbf{e}_h \odot \mathbf{e}_t) \cdot \mathbf{e}_r)
 
     This results in the scoring function:
 
     .. math::
-        d(h, r, t) = - \| \mathbf{e}_h + f(\mathbf{e}_h, \mathbf{e}_t, \mathbf{e}_r) \cdot \mathbf{e}_r - \mathbf{e}_t \|_p
+        d(h, r, t) = - \| \mathbf{e}_h +
+    .. math::
+        f(\mathbf{e}_h, \mathbf{e}_t, \mathbf{e}_r) \cdot \mathbf{e}_r - \mathbf{e}_t \|_p
 
     .. note::
         For an example of using the :class:`TransF` model, see