fix searchsorted output type (#42933)

Summary:
Fixes https://github.com/pytorch/pytorch/issues/41389
Make sure searchsorted that returns integer type does not make them require gradients.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/42933

Reviewed By: gchanan

Differential Revision: D23109583

Pulled By: albanD

fbshipit-source-id: 5af300b2f7f3c140d39fd7f7d87799f7b93a79c1

test/test_autograd.py

@@ -4434,6 +4434,20 @@ for shape in [(1,), ()]:
         self.assertFalse(out.dtype.is_floating_point)
         self.assertFalse(out.requires_grad)
 
+        out = inp.argmin()
+        self.assertFalse(out.dtype.is_floating_point)
+        self.assertFalse(out.requires_grad)
+
+        out = inp.argsort()
+        self.assertFalse(out.dtype.is_floating_point)
+        self.assertFalse(out.requires_grad)
+
+        val = torch.rand((), requires_grad=True)
+
+        out = torch.searchsorted(inp, val)
+        self.assertFalse(out.dtype.is_floating_point)
+        self.assertFalse(out.requires_grad)
+
 
 def index_variable(shape, max_indices):
     if not isinstance(shape, tuple):

tools/autograd/gen_variable_type.py

@@ -138,7 +138,7 @@ DONT_REQUIRE_DERIVATIVE = {
     # Quantize functions should not record gradients
     'quantize_per_tensor', 'quantize_per_channel',
     # Functions that return integers should not have output that require gradients
-    'argmax', 'argmin', 'argsort',
+    'argmax', 'argmin', 'argsort', 'searchsorted'
 }
 
 # Some operators invalidate the grad_accumulator. Let's reset it.