docstrings contain images

torch_scatter/functions/add.py

@@ -3,11 +3,15 @@ from .utils import gen_output
 
 def scatter_add_(output, index, input, dim=0):
     r"""
+    |
+
     .. image:: https://raw.githubusercontent.com/rusty1s/pytorch_scatter/
             master/docs/source/_figures/add.svg?sanitize=true
         :align: center
         :width: 400px
 
+    |
+
     Sums all values from the :attr:`input` tensor into :attr:`output` at the
     indices specified in the :attr:`index` tensor along an given axis
     :attr:`dim`. For each value in :attr:`input`, its output index is specified

torch_scatter/functions/div.py

@@ -3,8 +3,18 @@ from .utils import gen_output
 
 
 def scatter_div_(output, index, input, dim=0):
-    r"""Divides all values from the :attr:`input` tensor into :attr:`output`
-    at the indices specified in the :attr:`index` tensor along an given axis
+    r"""
+    |
+
+    .. image:: https://raw.githubusercontent.com/rusty1s/pytorch_scatter/
+            master/docs/source/_figures/div.svg?sanitize=true
+        :align: center
+        :width: 400px
+
+    |
+
+    Divides all values from the :attr:`input` tensor into :attr:`output` at
+    the indices specified in the :attr:`index` tensor along an given axis
     :attr:`dim`. If multiple indices reference the same location, their
     **contributions divide** (`cf.` :meth:`~torch_scatter.scatter_add_`).
 

torch_scatter/functions/max.py

@@ -3,8 +3,18 @@ from .utils import gen_filled_tensor, gen_output
 
 
 def scatter_max_(output, index, input, dim=0):
-    r"""Maximizes all values from the :attr:`input` tensor into :attr:`output`
-    at the indices specified in the :attr:`index` tensor along an given axis
+    r"""
+    |
+
+    .. image:: https://raw.githubusercontent.com/rusty1s/pytorch_scatter/
+            master/docs/source/_figures/max.svg?sanitize=true
+        :align: center
+        :width: 400px
+
+    |
+
+    Maximizes all values from the :attr:`input` tensor into :attr:`output` at
+    the indices specified in the :attr:`index` tensor along an given axis
     :attr:`dim`. If multiple indices reference the same location, their
     **contributions maximize** (`cf.` :meth:`~torch_scatter.scatter_add_`).
     The second return value is the index location in :attr:`input` of each

torch_scatter/functions/mean.py

@@ -3,8 +3,18 @@ from .utils import gen_filled_tensor, gen_output
 
 
 def scatter_mean_(output, index, input, dim=0):
-    r"""Averages all values from the :attr:`input` tensor into :attr:`output`
-    at the indices specified in the :attr:`index` tensor along an given axis
+    r"""
+    |
+
+    .. image:: https://raw.githubusercontent.com/rusty1s/pytorch_scatter/
+            master/docs/source/_figures/mean.svg?sanitize=true
+        :align: center
+        :width: 400px
+
+    |
+
+    Averages all values from the :attr:`input` tensor into :attr:`output` at
+    the indices specified in the :attr:`index` tensor along an given axis
     :attr:`dim`. If multiple indices reference the same location, their
     **contributions average** (`cf.` :meth:`~torch_scatter.scatter_add_`).
 

torch_scatter/functions/min.py

@@ -3,8 +3,18 @@ from .utils import gen_filled_tensor, gen_output
 
 
 def scatter_min_(output, index, input, dim=0):
-    r"""Minimizes all values from the :attr:`input` tensor into :attr:`output`
-    at the indices specified in the :attr:`index` tensor along an given axis
+    r"""
+    |
+
+    .. image:: https://raw.githubusercontent.com/rusty1s/pytorch_scatter/
+            master/docs/source/_figures/min.svg?sanitize=true
+        :align: center
+        :width: 400px
+
+    |
+
+    Minimizes all values from the :attr:`input` tensor into :attr:`output` at
+    the indices specified in the :attr:`index` tensor along an given axis
     :attr:`dim`. If multiple indices reference the same location, their
     **contributions minimize** (`cf.` :meth:`~torch_scatter.scatter_add_`).
     The second return value is the index location in :attr:`input` of each

torch_scatter/functions/mul.py

@@ -3,8 +3,18 @@ from .utils import gen_output
 
 
 def scatter_mul_(output, index, input, dim=0):
-    r"""Multiplies all values from the :attr:`input` tensor into :attr:`output`
-    at the indices specified in the :attr:`index` tensor along an given axis
+    r"""
+    |
+
+    .. image:: https://raw.githubusercontent.com/rusty1s/pytorch_scatter/
+            master/docs/source/_figures/mul.svg?sanitize=true
+        :align: center
+        :width: 400px
+
+    |
+
+    Multiplies all values from the :attr:`input` tensor into :attr:`output` at
+    the indices specified in the :attr:`index` tensor along an given axis
     :attr:`dim`. If multiple indices reference the same location, their
     **contributions multiply** (`cf.` :meth:`~torch_scatter.scatter_add_`).
 

torch_scatter/functions/sub.py

@@ -2,8 +2,18 @@ from .utils import gen_output
 
 
 def scatter_sub_(output, index, input, dim=0):
-    r"""Subtracts all values from the :attr:`input` tensor into :attr:`output`
-    at the indices specified in the :attr:`index` tensor along an given axis
+    r"""
+    |
+
+    .. image:: https://raw.githubusercontent.com/rusty1s/pytorch_scatter/
+            master/docs/source/_figures/sub.svg?sanitize=true
+        :align: center
+        :width: 400px
+
+    |
+
+    Subtracts all values from the :attr:`input` tensor into :attr:`output` at
+    the indices specified in the :attr:`index` tensor along an given axis
     :attr:`dim`. If multiple indices reference the same location, their
     **negated contributions add** (`cf.` :meth:`~torch_scatter.scatter_add_`).