[Dy2stat]fix no_grad context error in dy2stat

paddle/fluid/pybind/pybind.cc

@@ -1241,6 +1241,17 @@ All parameter, weight, gradient are variables in Paddle.
              return self.GetMutable<framework::ReaderHolder>();
            },
            py::return_value_policy::reference)
+      .def("get_scope",
+           [](Variable &self) -> Scope * {
+             auto scope_vec =
+                 self.GetMutable<std::vector<framework::Scope *>>();
+             PADDLE_ENFORCE_GT(
+                 scope_vec->size(), 0,
+                 platform::errors::InvalidArgument(
+                     "The size of scope_vec should be greater than 0"));
+             return scope_vec->front();
+           },
+           py::return_value_policy::reference)
       .def("set_scope", [](Variable &self, Scope &scope) {
         auto scope_vec = self.GetMutable<std::vector<framework::Scope *>>();
         scope_vec->emplace_back(&scope);

python/paddle/fluid/dygraph/dygraph_to_static/partial_program.py

@@ -290,10 +290,15 @@ def __call__(self, inputs):
             self._valid_vars(self._params),
             self._valid_vars(out_vars), self._tmp_scope_vec, self._double_grads,
             *attrs)
-
+        self.drop_scope_if_no_grad()
         restored_nest_out = self._restore_out(out_vars)
         return self._remove_no_value(restored_nest_out)
 
+    def drop_scope_if_no_grad(self):
+        tracer = framework._dygraph_tracer()
+        if self.training and not tracer._has_grad:
+            self._tmp_scope_vec.value().get_scope().drop_kids()
+
     @property
     def program(self):
         if self.training:

python/paddle/fluid/tests/unittests/dygraph_to_static/test_partial_program.py

@@ -152,6 +152,21 @@ def test_switch_eval_and_train(self):
                              partial_layer._train_program)
 
 
+class TestWithNoGrad(unittest.TestCase):
+    def test_with_no_grad(self):
+        with fluid.dygraph.guard():
+            linear_net = Linear()
+            x_data = np.random.random((5, 10)).astype('float32')
+            x = fluid.dygraph.to_variable(x_data)
+
+            with paddle.no_grad():
+                linear_net.train()
+                linear_net(x)
+                _, partial_layer = linear_net.forward.program_cache.last()[-1]
+                self.assertEqual(partial_layer.program,
+                                 partial_layer._train_program)
+
+
 class GPT2LMHeadModel(fluid.dygraph.Layer):
     def __init__(self):
         super(GPT2LMHeadModel, self).__init__()