Try to implement gradient.

src/torch_stablesort/setup.py

@@ -2,6 +2,7 @@ from setuptools import setup, Extension
 from torch.utils import cpp_extension
 
 setup(name='torch_stablesort',
+    py_modules=['torch_stablesort'],
     ext_modules=[cpp_extension.CppExtension('torch_stablesort_cpp',
         ['torch_stablesort.cpp'],
         extra_compile_args=['-fopenmp', '-ggdb'])],

src/torch_stablesort/torch_stablesort.py

@@ -0,0 +1,18 @@
+import torch
+import torch_stablesort_cpp
+
+
+class StableSort(torch.autograd.Function):
+    @staticmethod
+    def forward(ctx, input, dim=-1, descending=False, out=None):
+        values, indices = \
+            torch_stablesort_cpp.stable_sort(input, dim, descending, out)
+        ctx.save_for_backward(input, indices)
+        return values, indices
+
+    @staticmethod
+    def backward(ctx, grad_values, grad_indices):
+        input, indices = ctx.saved_variables
+        res = torch.empty_like(grad_values)
+        res[indices] = grad_values + grad_indices
+        return res