Eager check for invalid ndim in TensorType

pytensor/tensor/type.py

@@ -120,7 +120,12 @@ class TensorType(CType[np.ndarray], HasDataType, HasShape):
 
         self.shape = _shape = tuple(parse_bcast_and_shape(s) for s in shape)
         self.broadcastable = tuple(s == 1 for s in _shape)
-        self.ndim = len(_shape)
+        self.ndim = _ndim = len(_shape)
+        if _ndim > 64:
+            # Message mimicks that of numpy
+            raise ValueError(
+                f"maximum supported dimension for a TensorType is currently 64, found {_ndim}"
+            )
         self.dtype_specs()  # error checking is done there
         self.name = name
         self.numpy_dtype = np.dtype(self.dtype)

tests/tensor/test_elemwise.py

@@ -181,12 +181,12 @@ class TestDimShuffle(unittest_tools.InferShapeTester):
             )
 
     def test_too_big_rank(self):
-        numpy_maxdims = 64
         x = self.type(self.dtype, shape=())()
-        y = x.dimshuffle(("x",) * (numpy_maxdims + 1))
-
-        with pytest.raises((ValueError, SystemError)):
-            y.eval({x: 0})
+        with pytest.raises(
+            ValueError,
+            match="maximum supported dimension for a TensorType is currently 64, found 65",
+        ):
+            x.dimshuffle(("x",) * 65)
 
     def test_c_views(self):
         x_pt = vector()