Restrict diag input ndim to 1 and 2 like numpy

pytensor/tensor/basic.py

@@ -3630,7 +3630,7 @@ def diag(v, k=0):
     A helper function for two ops: `ExtractDiag` and
     `AllocDiag`. The name `diag` is meant to keep it consistent
     with numpy. It both accepts tensor vector and tensor matrix.
-    While the passed tensor variable `v` has `v.ndim>=2`, it builds a
+    While the passed tensor variable `v` has `v.ndim==2`, it builds a
     `ExtractDiag` instance, and returns a vector with its entries equal to
     `v`'s main diagonal; otherwise if `v.ndim` is `1`, it builds an `AllocDiag`
     instance, and returns a matrix with `v` at its k-th diaogonal.
@@ -3651,10 +3651,10 @@ def diag(v, k=0):
 
     if _v.ndim == 1:
         return AllocDiag(k)(_v)
-    elif _v.ndim >= 2:
+    elif _v.ndim == 2:
         return diagonal(_v, offset=k)
     else:
-        raise ValueError("Number of dimensions of `v` must be greater than one.")
+        raise ValueError("Input must be 1- or 2-d.")
 
 
 def stacklists(arg):

tests/tensor/test_basic.py

@@ -3593,17 +3593,18 @@ class TestDiag:
             # The right matrix is created
             assert (r == v).all()
 
-        # Test scalar input
-        xx = scalar()
-        with pytest.raises(ValueError):
-            diag(xx)
-
         # Test passing a list
         xx = [[1, 2], [3, 4]]
         g = diag(xx)
         f = function([], g)
         assert np.array_equal(f(), np.diag(xx))
 
+    @pytest.mark.parametrize("inp", (scalar, tensor3))
+    def test_diag_invalid_input_ndim(self, inp):
+        x = inp()
+        with pytest.raises(ValueError, match="Input must be 1- or 2-d."):
+            diag(x)
+
 
 class TestExtractDiag:
     @pytest.mark.parametrize("axis1, axis2", [(0, 1), (1, 0)])