Add test for Blockwise of COp with params

tests/tensor/test_blockwise.py

@@ -9,10 +9,10 @@ from pytensor import config, function
 from pytensor.gradient import grad
 from pytensor.graph import Apply, Op
 from pytensor.graph.replace import vectorize_node
+from pytensor.raise_op import assert_op
 from pytensor.tensor import diagonal, log, tensor
 from pytensor.tensor.blockwise import Blockwise
 from pytensor.tensor.nlinalg import MatrixInverse
-from pytensor.tensor.shape import Shape
 from pytensor.tensor.slinalg import Cholesky, Solve, cholesky, solve_triangular
 from pytensor.tensor.utils import _parse_gufunc_signature
 
@@ -362,11 +362,20 @@ def test_batched_mvnormal_logp_and_dlogp(mu_batch_shape, cov_batch_shape, benchm
     benchmark(fn, *test_values)
 
 
-def test_op_with_params():
-    matrix_shape_blockwise = Blockwise(core_op=Shape(), signature="(x1,x2)->(s)")
+def test_cop_with_params():
+    matrix_assert = Blockwise(core_op=assert_op, signature="(x1,x2),()->(x1,x2)")
+
     x = tensor("x", shape=(5, None, None), dtype="float64")
-    x_shape = matrix_shape_blockwise(x)
+    x_shape = matrix_assert(x, (x >= 0).all())
+
     fn = pytensor.function([x], x_shape)
-    pytensor.dprint(fn)
-    # Assert blockwise
-    print(fn(np.zeros((5, 3, 2))))
+    [fn_out] = fn.maker.fgraph.outputs
+    assert fn_out.owner.op == matrix_assert, "Blockwise should be in final graph"
+
+    np.testing.assert_allclose(
+        fn(np.zeros((5, 3, 2))),
+        np.zeros((5, 3, 2)),
+    )
+
+    with pytest.raises(AssertionError):
+        fn(np.zeros((5, 3, 2)) - 1)