Fix AdvancedIncSubtensor1 C-compilation with empty indices

Author: ricardoV94

pytensor/tensor/subtensor.py

@@ -2561,7 +2561,11 @@ def c_code(self, node, name, input_names, output_names, sub):
             and y_.type.dtype not in complex_dtypes
         ):
             # Simple implementation for vector x, y cases
-            idx_may_be_neg = not (isinstance(idx_, Constant) and idx_.data.min() >= 0)
+            idx_may_be_neg = not (
+                # Empty idx needs no negative checks
+                idx_.type.shape[0] == 0
+                or (isinstance(idx_, Constant) and idx_.data.min() >= 0)
+            )
             idx_may_be_invalid = AdvancedSubtensor1._idx_may_be_invalid(x_, idx_)
             shape0 = x_.type.shape[0]
             # This is used to make sure that when we trust the indices to be valid
@@ -2680,7 +2684,7 @@ def c_code(self, node, name, input_names, output_names, sub):
         """
 
     def c_code_cache_version(self):
-        return (9,)
+        return (10,)
 
     def _check_runtime_broadcasting(
         self, node: Apply, x: np.ndarray, y: np.ndarray, idx: np.ndarray

tests/tensor/test_subtensor.py

@@ -22,7 +22,7 @@
 from pytensor.graph.rewriting.utils import is_same_graph
 from pytensor.printing import pprint
 from pytensor.scalar.basic import as_scalar, int16
-from pytensor.tensor import as_tensor, get_vector_length, vectorize
+from pytensor.tensor import as_tensor, constant, get_vector_length, vectorize
 from pytensor.tensor.blockwise import Blockwise
 from pytensor.tensor.elemwise import DimShuffle
 from pytensor.tensor.math import exp, isinf, lt, switch
@@ -1730,7 +1730,7 @@ def test_grad_broadcastable_specialization(self):
         )
 
 
-class TestIncSubtensor1:
+class TestAdvancedIncSubtensor1:
     def setup_method(self):
         self.rng = np.random.default_rng(seed=utt.fetch_seed())
 
@@ -1817,6 +1817,16 @@ def test_inc_bcastableidx(self):
         out1val, out2val = f(mval, incval, incval)
         utt.assert_allclose(out1val, out2val)
 
+    def test_empty_index(self):
+        x = fvector()
+        idx = constant([], dtype="int64")
+        y = idx.astype("float32")
+        out = advanced_inc_subtensor1(x, y, idx)
+
+        test_x = np.array([1, 2, 3], dtype="float32")
+        res = out.eval({x: test_x}, mode=Mode(optimizer=None))
+        np.testing.assert_array_equal(res, test_x)
+
 
 class TestAdvancedSubtensor:
     """Test inc_subtensor and set_subtensor."""