fix unittests

test/dygraph_to_static/test_resnet.py

@@ -19,6 +19,7 @@
 import unittest
 
 import numpy as np
+from dygraph_to_static_util import ast_only_test
 from predictor_utils import PredictorTools
 
 import paddle
@@ -413,6 +414,7 @@ def verify_predict(self):
             ),
         )
 
+    @ast_only_test
     def test_resnet(self):
         static_loss = self.train(to_static=True)
         dygraph_loss = self.train(to_static=False)
@@ -426,6 +428,7 @@ def test_resnet(self):
         )
         self.verify_predict()
 
+    @ast_only_test
     def test_resnet_composite_backward(self):
         core._set_prim_backward_enabled(True)
         static_loss = self.train(to_static=True)
@@ -440,6 +443,7 @@ def test_resnet_composite_backward(self):
             ),
         )
 
+    @ast_only_test
     def test_resnet_composite_forward_backward(self):
         core._set_prim_all_enabled(True)
         static_loss = self.train(to_static=True)
@@ -454,6 +458,7 @@ def test_resnet_composite_forward_backward(self):
             ),
         )
 
+    @ast_only_test
     def test_in_static_mode_mkldnn(self):
         fluid.set_flags({'FLAGS_use_mkldnn': True})
         try:

test/dygraph_to_static/test_resnet_v2.py

@@ -19,6 +19,7 @@
 import unittest
 
 import numpy as np
+from dygraph_to_static_util import ast_only_test
 from predictor_utils import PredictorTools
 
 import paddle
@@ -412,6 +413,7 @@ def verify_predict(self):
             ),
         )
 
+    @ast_only_test
     def test_resnet(self):
         static_loss = self.train(to_static=True)
         dygraph_loss = self.train(to_static=False)
@@ -425,6 +427,7 @@ def test_resnet(self):
         )
         self.verify_predict()
 
+    @ast_only_test
     def test_resnet_composite(self):
         core._set_prim_backward_enabled(True)
         core._add_skip_comp_ops("batch_norm")
@@ -440,6 +443,7 @@ def test_resnet_composite(self):
             ),
         )
 
+    @ast_only_test
     def test_in_static_mode_mkldnn(self):
         paddle.fluid.set_flags({'FLAGS_use_mkldnn': True})
         try:

test/dygraph_to_static/test_rollback.py

@@ -15,6 +15,7 @@
 import unittest
 
 import numpy as np
+from dygraph_to_static_util import ast_only_test
 
 import paddle
 from paddle.jit.dy2static.program_translator import StaticFunction
@@ -88,6 +89,7 @@ class TestRollBackNet(unittest.TestCase):
     def setUp(self):
         paddle.set_device("cpu")
 
+    @ast_only_test
     def test_net(self):
         net = paddle.jit.to_static(Net())
         x = paddle.randn([3, 4])

test/dygraph_to_static/test_save_inference_model.py

@@ -17,6 +17,7 @@
 import unittest
 
 import numpy as np
+from dygraph_to_static_util import ast_only_test
 
 import paddle
 from paddle import fluid
@@ -53,6 +54,7 @@ def setUp(self):
     def tearDown(self):
         self.temp_dir.cleanup()
 
+    @ast_only_test
     def test_save_inference_model(self):
         fc_size = 20
         x_data = np.random.random((fc_size, fc_size)).astype('float32')
@@ -145,6 +147,7 @@ def load_and_run_inference(
 
 
 class TestPartialProgramRaiseError(unittest.TestCase):
+    @ast_only_test
     def test_param_type(self):
         paddle.jit.enable_to_static(True)
         x_data = np.random.random((20, 20)).astype('float32')

test/dygraph_to_static/test_save_load.py

@@ -17,6 +17,7 @@
 import unittest
 
 import numpy as np
+from dygraph_to_static_util import ast_only_test
 from test_fetch_feed import Linear
 
 import paddle
@@ -115,6 +116,7 @@ def test_save_load_same_result(self):
             dygraph_loss.numpy(), static_loss.numpy(), rtol=1e-05
         )
 
+    @ast_only_test
     def test_save_load_prim(self):
         with fluid.dygraph.guard(place):
             self.x = paddle.randn([4, 2, 6, 6], dtype="float32")
@@ -155,6 +157,7 @@ def test_save_load_prim(self):
             self.assertIn("pool2d", load_op_type_list)
             np.testing.assert_allclose(res.numpy(), new_res.numpy(), rtol=1e-05)
 
+    @ast_only_test
     def test_save_load_prim_with_hook(self):
         with fluid.dygraph.guard(place):
             self.x = paddle.randn([4, 2, 6, 6], dtype="float32")