Check for Constants in OpFromGraph constructor

aesara/compile/builders.py

@@ -11,6 +11,7 @@ from aesara.configdefaults import config
 from aesara.gradient import DisconnectedType, Rop, grad
 from aesara.graph.basic import (
     Apply,
+    Constant,
     Variable,
     clone_replace,
     graph_inputs,
@@ -331,13 +332,21 @@ class OpFromGraph(Op, HasInnerGraph):
         name=None,
         **kwargs,
     ):
-        if not isinstance(outputs, list):
-            raise TypeError(f"outputs must be list, got {type(outputs)}")
+
+        if not (isinstance(inputs, list) and isinstance(outputs, list)):
+            raise TypeError("Inputs and outputs must be lists")
+
         for i in inputs + outputs:
             if not isinstance(i, Variable):
-                raise TypeError("inputs and outputs must be Variable instances", i)
+                raise TypeError(
+                    f"Inputs and outputs must be Variable instances; got {i}"
+                )
+            if i in inputs and isinstance(i, Constant):
+                raise TypeError(f"Constants not allowed as inputs; {i}")
+
         if "updates" in kwargs or "givens" in kwargs:
-            raise TypeError("updates and givens are not allowed here")
+            raise NotImplementedError("Updates and givens are not allowed here")
+
         self.is_inline = inline
         # To correctly support shared variables the inner fct should
         # not see them. Otherwise there is a problem with the gradient.

tests/compile/test_builders.py

@@ -19,12 +19,28 @@ from aesara.tensor.math import round as aet_round
 from aesara.tensor.math import sigmoid
 from aesara.tensor.math import sum as aet_sum
 from aesara.tensor.random.utils import RandomStream
+from aesara.tensor.shape import specify_shape
 from aesara.tensor.type import TensorType, matrices, matrix, scalar, vector, vectors
 from tests import unittest_tools
 from tests.graph.utils import MyVariable
 
 
 class TestOpFromGraph(unittest_tools.InferShapeTester):
+    def test_valid_input(self):
+        x, y, z = matrices("xyz")
+
+        with pytest.raises(TypeError):
+            OpFromGraph((x,), (x,))
+
+        with pytest.raises(TypeError):
+            OpFromGraph([1], [1])
+
+        with pytest.raises(TypeError):
+            OpFromGraph([x, as_tensor(1)], [x])
+
+        with pytest.raises(NotImplementedError):
+            OpFromGraph([x], [x], updates={})
+
     @pytest.mark.parametrize(
         "cls_ofg", [OpFromGraph, partial(OpFromGraph, inline=True)]
     )
@@ -39,9 +55,6 @@ class TestOpFromGraph(unittest_tools.InferShapeTester):
         xv = np.ones((2, 2), dtype=config.floatX)
         yv = np.ones((2, 2), dtype=config.floatX) * 3
         zv = np.ones((2, 2), dtype=config.floatX) * 5
-        # print function, function.__module__
-        # print fn.maker.fgraph.toposort()
-        fn(xv, yv, zv)
         assert np.all(8.0 == fn(xv, yv, zv))
         assert np.all(8.0 == fn(xv, yv, zv))
 
@@ -412,7 +425,7 @@ class TestOpFromGraph(unittest_tools.InferShapeTester):
         # shape
         x = MyVariable("x")
         y = matrix("y")
-        z = as_tensor([1, 2])
+        z = specify_shape(vector("z"), (2,))
 
         op_graph = OpFromGraph([x, y, z], [x, y])