diff --git a/pytensor/tensor/nlinalg.py b/pytensor/tensor/nlinalg.py
index d46f576a71..30a3c8d5c8 100644
--- a/pytensor/tensor/nlinalg.py
+++ b/pytensor/tensor/nlinalg.py
@@ -246,7 +246,7 @@ def perform(self, node, inputs, outputs):
         (x,) = inputs
         (sign, det) = outputs
         try:
-            sign[0], det[0] = (z.astype(x.dtype) for z in np.linalg.slogdet(x))
+            sign[0], det[0] = (np.array(z, dtype=x.dtype) for z in np.linalg.slogdet(x))
         except Exception:
             print("Failed to compute determinant", x)
             raise
@@ -1186,6 +1186,7 @@ def kron(a, b):
     "lstsq",
     "matrix_power",
     "norm",
+    "slogdet",
     "tensorinv",
     "tensorsolve",
     "kron",
diff --git a/tests/tensor/test_nlinalg.py b/tests/tensor/test_nlinalg.py
index bf4bb1a904..8a0c6c6596 100644
--- a/tests/tensor/test_nlinalg.py
+++ b/tests/tensor/test_nlinalg.py
@@ -387,6 +387,11 @@ def test_slogdet():
     sign, det = np.linalg.slogdet(r)
     assert np.equal(sign, f_sign)
     assert np.allclose(det, f_det)
+    # check numpy array types is returned
+    # see https://github.com/pymc-devs/pytensor/issues/799
+    sign, logdet = slogdet(x)
+    det = sign * pytensor.tensor.exp(logdet)
+    assert_array_almost_equal(det.eval({x: [[1]]}), np.array(1.0))
 
 
 def test_trace():