[Dy2St][CINN] Explicit use phi backend in more CINN uts

Author: SigureMo

test/ir/pir/cinn/sub_graphs/base.py

@@ -61,7 +61,10 @@ def train(self, net, to_static, with_prim=False, with_cinn=False):
                 )
             else:
                 net = paddle.jit.to_static(
-                    net(), full_graph=True, input_spec=self.input_specs
+                    net(),
+                    backend=None,
+                    full_graph=True,
+                    input_spec=self.input_specs,
                 )
         if self.with_train:
             net.train()

test/ir/pir/cinn/symbolic/test_decomp_inference_predictor_run.py

@@ -58,6 +58,7 @@ def setUp(self):
                 ),
             ],
             full_graph=True,
+            backend=None,
         )
         paddle.jit.save(
             model,

test/ir/pir/cinn/symbolic/test_reshape_dyshape2stshape.py

@@ -54,7 +54,11 @@ def train(self, net, to_static, with_cinn=False):
                     full_graph=True,
                 )
             else:
-                net = paddle.jit.to_static(net, full_graph=True)
+                net = paddle.jit.to_static(
+                    net,
+                    backend=None,
+                    full_graph=True,
+                )
         paddle.seed(123)
         outs = net(*self.inputs)
         return outs

test/ir/pir/cinn/symbolic/test_sub_graph_flatten.py

@@ -51,7 +51,11 @@ def train(self, net, to_static, with_prim=False, with_cinn=False):
                     full_graph=True,
                 )
             else:
-                net = paddle.jit.to_static(net, full_graph=True)
+                net = paddle.jit.to_static(
+                    net,
+                    backend=None,
+                    full_graph=True,
+                )
         paddle.seed(123)
         outs = net(*self.inputs)
         return outs

test/legacy_test/test_stack_op.py

@@ -396,7 +396,11 @@ def setUp(self):
     def test_list_single_tensor(self):
         expect = paddle.stack(self.x)
         paddle.base.core._set_prim_all_enabled(True)
-        st_model = paddle.jit.to_static(paddle.stack, full_graph=True)
+        st_model = paddle.jit.to_static(
+            paddle.stack,
+            backend=None,
+            full_graph=True,
+        )
         actual = st_model(self.x)
         np.testing.assert_allclose(expect, actual)
         paddle.enable_static()