Support test basic of Var and Layer (#38426)

* Rearranged Eager AutoCodeGen directory structure

* Removed USE_OP in Eager AutoCodeGen

* Enabled generation for Operators without Grad/Inputs/Outputs

* Resolved operators without input

* Fixed merge conflicts

* Enabled Eager AutoCodeGen for 10+ more operators

* Refactored Eager AutoCodeGen with more organized helper objects

* Enabled Eager AutoCodeGen for operators with multiple OpBases

* Adjusted Eager AutoCodeGen to Enable Passing Output Tensor as Input Argument

* Handled Dispensable Inputs/Outputs in Eager AutoCodeGen

* Adjusted function generation/call between Python-C API & Dygraph API

* Synchronized auto-generated Python-C API with Dygraph Forward Functions

* support more eager tensor api

* fix merge compile error

* fix compile error and fit develop code

* support pure CPU

* fix some logic error in eager_mode

* support _varbase_creator in eager mode

* Added safe_initialized interface to EagerTensor for use in processing dispensable inputs

* for eager mode

* refine

* support multiple constructor for eager tensor

* add place related code

* polish code

* specific randint with dtype of int64

* Support pure cpu test

* eager logic

* refine test in pure cpu

* eager logic

* eager logic

* eager logic, test=develop

* skip core.eager when in inference, test=develop

* refine, test=develop

* refine, test=develop

* call RetainGrad after run forward kernel, test=develop

* refine, test=develop

* support dygraph util, meta, guard test

* support inference test

* refine test and fix initializer failed

* support create varbase and fix retain grad error

* fix windows error

* support test code coverage

* support test code coverage

* support test code coverage
Co-authored-by: Njim19930609 <jim19930609@gmail.com>
Co-authored-by: NWang Huan <wanghuan29@baidu.com>

paddle/fluid/eager/auto_code_generator/eager_generator.cc

@@ -1003,13 +1003,6 @@ static std::string GenerateGradNodeCreationContent(
       grad_node_creation_str +=
           paddle::string::Sprintf(ADD_EDGES_TEMPLATE, input_autograd_name,
                                   input_autograd_name, input_position);
-
-      VLOG(6) << "Generated Call RetainGradForTensor";
-      const char* RETAIN_GRAD_TEMPLATE =
-          "    egr::EagerUtils::CheckAndRetainGrad(%s);\n";
-      grad_node_creation_str +=
-          paddle::string::Sprintf(RETAIN_GRAD_TEMPLATE, input_name);
-
     } else {
       compute_require_grad_args += ", &" + input_autograd_name;
       size_t input_position = fwd_inputs_name_pos_map.at(input_name);
@@ -1023,6 +1016,11 @@ static std::string GenerateGradNodeCreationContent(
       grad_node_creation_str += paddle::string::Sprintf(
           ADD_EDGES_TEMPLATE, input_autograd_name, input_position);
     }
+    VLOG(6) << "Generated Call RetainGradForTensor";
+    const char* RETAIN_GRAD_TEMPLATE =
+        "    egr::EagerUtils::CheckAndRetainGrad(%s);\n";
+    grad_node_creation_str +=
+        paddle::string::Sprintf(RETAIN_GRAD_TEMPLATE, input_name);
   }
 
   // [GradOpNode] SetGradInMeta

paddle/fluid/pybind/eager.cc

@@ -42,6 +42,7 @@ namespace py = ::pybind11;
 
 PyTypeObject* p_eager_tensor_type;
 extern PyTypeObject* g_vartype_pytype;
+extern PyTypeObject* g_framework_tensor_pytype;
 
 PyObject* EagerTensorNew(PyTypeObject* type, PyObject* args, PyObject* kwargs) {
   PyObject* obj = type->tp_alloc(type, 0);
@@ -154,6 +155,37 @@ void InitEagerTensorWithEagerTensor(EagerTensorObject* self,
   }
 }
 
+void InitEagerTensorWithFrameworkTensor(EagerTensorObject* self,
+                                        const framework::Tensor& src,
+                                        const paddle::platform::Place& place,
+                                        const std::string& name) {
+  self->eager_tensor.set_name(name);
+  if (place == src.place()) {
+    std::shared_ptr<pten::DenseTensor> dense_tensor =
+        std::make_shared<pten::DenseTensor>(
+            pten::make_intrusive<paddle::experimental::SharedStorage>(place),
+            pten::DenseTensorMeta(pten::TransToPtenDataType(src.type()),
+                                  src.dims()));
+    paddle::experimental::ReMakePtenDenseTensor(src, dense_tensor.get());
+    self->eager_tensor.set_impl(dense_tensor);
+    VLOG(4) << "Same place, do ShareDataWith";
+  } else {
+    std::shared_ptr<pten::DenseTensor> dense_tensor =
+        std::make_shared<pten::DenseTensor>(
+            pten::make_intrusive<paddle::experimental::SharedStorage>(
+                src.place()),
+            pten::DenseTensorMeta(pten::TransToPtenDataType(src.type()),
+                                  src.dims()));
+    paddle::experimental::ReMakePtenDenseTensor(src, dense_tensor.get());
+    auto temp = egr::EagerTensor(dense_tensor);
+    self->eager_tensor.set_impl(
+        temp.copy_to(pten::TransToPtenBackend(place), true).impl());
+    VLOG(4) << "Different place, do TensorCopy";
+  }
+  egr::EagerUtils::autograd_meta(&(self->eager_tensor))->SetStopGradient(true);
+  egr::EagerUtils::unsafe_autograd_meta(self->eager_tensor)
+      ->SetPersistable(false);
+}
 // TODO(jiabin): We have to do some ugly work, refactor this method using
 // PyArg_ParseTuple()，PyArg_ParseTupleAndKeywords() and PyArg_Parse() later to
 // support kwargs.
@@ -187,6 +219,11 @@ int EagerTensorInit(PyObject* self, PyObject* args, PyObject* kwds) {
    * ** tensor: EagerTensor,
    * ** place: paddle::platform::Place,
    * ** name: std::string)
+   * 7. (multi-place) (must have first 2 parameter)
+   * def __init__ (
+   * ** tensor: FrameworkTensor,
+   * ** place: paddle::platform::Place,
+   * ** name: std::string)
    *  **/
   PADDLE_ENFORCE_NOT_NULL(
       self, paddle::platform::errors::Fatal(
@@ -236,6 +273,15 @@ int EagerTensorInit(PyObject* self, PyObject* args, PyObject* kwds) {
             egr::Controller::Instance().GetExpectedPlace(),
             egr::Controller::Instance().GenerateUniqueName("generated_tensor"));
         return 0;
+      } else if (PyObject_IsInstance(
+                     arg0_ptr,
+                     reinterpret_cast<PyObject*>(g_framework_tensor_pytype))) {
+        VLOG(6) << "Calling case7's initializer.";
+        auto src_tensor = CastPyArg2FrameworkTensor(arg0_ptr, 0);
+        InitEagerTensorWithFrameworkTensor(
+            py_tensor_ptr, src_tensor, src_tensor.place(),
+            egr::Controller::Instance().GenerateUniqueName("generated_tensor"));
+        return 0;
       } else {
         PADDLE_THROW(platform::errors::InvalidArgument(
             "We only support construct tensor from numpy value or tensor with "
@@ -275,6 +321,17 @@ int EagerTensorInit(PyObject* self, PyObject* args, PyObject* kwds) {
             py_tensor_ptr, src_tensor, place,
             egr::Controller::Instance().GenerateUniqueName("generated_tensor"));
         return 0;
+      } else if (PyObject_IsInstance(
+                     arg0_ptr,
+                     reinterpret_cast<PyObject*>(g_framework_tensor_pytype))) {
+        VLOG(6) << "Calling case7's initializer.";
+        auto src_tensor = CastPyArg2FrameworkTensor(arg0_ptr, 0);
+        paddle::platform::Place place =
+            CastPyArg2Place(PyTuple_GET_ITEM(args, 1), 1);
+        InitEagerTensorWithFrameworkTensor(
+            py_tensor_ptr, src_tensor, place,
+            egr::Controller::Instance().GenerateUniqueName("generated_tensor"));
+        return 0;
       } else {
         PADDLE_THROW(platform::errors::InvalidArgument(
             "We only support construct tensor from numpy value or tensor with "
@@ -282,6 +339,7 @@ int EagerTensorInit(PyObject* self, PyObject* args, PyObject* kwds) {
             "please check your input first and make sure you are on the right "
             "way."));
       }
+      return 0;
     }
     case (Py_ssize_t)3: {
       PyObject* arg0_ptr = PyTuple_GET_ITEM(args, 0);
@@ -321,6 +379,24 @@ int EagerTensorInit(PyObject* self, PyObject* args, PyObject* kwds) {
         InitEagerTensorWithEagerTensor(py_tensor_ptr, src_tensor, place,
                                        act_name);
         return 0;
+      } else if (PyObject_IsInstance(
+                     arg0_ptr,
+                     reinterpret_cast<PyObject*>(g_framework_tensor_pytype))) {
+        VLOG(6) << "Calling case7's initializer.";
+        auto src_tensor = CastPyArg2FrameworkTensor(arg0_ptr, 0);
+        paddle::platform::Place place =
+            CastPyArg2Place(PyTuple_GET_ITEM(args, 1), 1);
+        std::string act_name = "";
+        PyObject* name_obj = PyTuple_GET_ITEM(args, 2);
+        if (name_obj == Py_None) {
+          act_name = egr::Controller::Instance().GenerateUniqueName(
+              "generated_tensor");
+        } else {
+          act_name = CastPyArg2AttrString(name_obj, 2);
+        }
+        InitEagerTensorWithFrameworkTensor(py_tensor_ptr, src_tensor, place,
+                                           act_name);
+        return 0;
       } else {
         PADDLE_THROW(platform::errors::InvalidArgument(
             "We only support construct tensor from numpy value or tensor with "
@@ -328,6 +404,7 @@ int EagerTensorInit(PyObject* self, PyObject* args, PyObject* kwds) {
             "please check your input first and make sure you are on the right "
             "way."));
       }
+      return 0;
     }
     case (Py_ssize_t)4: {
       VLOG(6) << "Calling case3's initializer.";

paddle/fluid/pybind/eager_method.cc

@@ -140,6 +140,7 @@ static PyObject* eager_tensor_method_copy_(EagerTensorObject* self,
 static PyObject* eager_tensor_retain_grads(EagerTensorObject* self,
                                            PyObject* args, PyObject* kwargs) {
   EAGER_TRY
+  if (egr::Controller::Instance().HasGrad()) {
     auto meta = egr::EagerUtils::autograd_meta(&(self->eager_tensor));
     if (!meta->GetMutableGradNode()) {
       VLOG(6) << "Make grad node of tensor: " << self->eager_tensor.name()
@@ -147,6 +148,7 @@ static PyObject* eager_tensor_retain_grads(EagerTensorObject* self,
       meta->SetGradNode(std::make_shared<egr::GradNodeAccumulation>());
     }
     egr::egr_utils_api::RetainGradForTensor(self->eager_tensor);
+  }
   Py_INCREF(Py_None);
   return Py_None;
   EAGER_CATCH_AND_THROW_RETURN_NULL

paddle/fluid/pybind/eager_utils.cc

@@ -40,6 +40,7 @@ extern PyTypeObject* g_cpuplace_pytype;
 extern PyTypeObject* g_xpuplace_pytype;
 extern PyTypeObject* g_npuplace_pytype;
 extern PyTypeObject* g_cudapinnedplace_pytype;
+extern PyTypeObject* g_framework_tensor_pytype;
 
 int TensorDtype2NumpyDtype(pten::DataType dtype) {
   switch (dtype) {
@@ -300,6 +301,18 @@ platform::Place CastPyArg2Place(PyObject* obj, ssize_t arg_pos) {
   return place;
 }
 
+framework::Tensor CastPyArg2FrameworkTensor(PyObject* obj, ssize_t arg_pos) {
+  if (PyObject_IsInstance(
+          obj, reinterpret_cast<PyObject*>(g_framework_tensor_pytype))) {
+    return ::pybind11::handle(obj).cast<framework::Tensor>();
+  } else {
+    PADDLE_THROW(platform::errors::InvalidArgument(
+        "argument (position %d) must be "
+        "EagerTensor, but got %s",
+        arg_pos + 1, reinterpret_cast<PyTypeObject*>(obj->ob_type)->tp_name));
+  }
+}
+
 paddle::framework::proto::VarType::Type CastPyArg2ProtoType(PyObject* obj,
                                                             ssize_t arg_pos) {
   paddle::framework::proto::VarType::Type dtype;

paddle/fluid/pybind/eager_utils.h

@@ -35,6 +35,7 @@ egr::EagerTensor CastPyArg2EagerTensor(PyObject* obj, ssize_t arg_pos);
 std::vector<egr::EagerTensor> CastPyArg2VectorOfEagerTensor(PyObject* obj,
                                                             ssize_t arg_pos);
 platform::Place CastPyArg2Place(PyObject* obj, ssize_t arg_pos);
+framework::Tensor CastPyArg2FrameworkTensor(PyObject* obj, ssize_t arg_pos);
 std::vector<int> CastPyArg2VectorOfInt(PyObject* obj, size_t arg_pos);
 framework::proto::VarType::Type CastPyArg2ProtoType(PyObject* obj,
                                                     ssize_t arg_pos);

paddle/fluid/pybind/imperative.cc

@@ -763,7 +763,6 @@ void BindImperative(py::module *m_ptr) {
         []() { imperative::SetLoadProcessSignalHandler(); });
   m.def("_throw_error_if_process_failed",
         []() { imperative::ThrowErrorIfLoadProcessFailed(); });
-
   // Dygraph DataLoader reader process & thread related functions
   m.def(
       "_convert_to_tensor_list",
@@ -866,7 +865,10 @@ void BindImperative(py::module *m_ptr) {
 
   m.def("start_imperative_gperf_profiler",
         []() { imperative::StartProfile(); });
-
+  m.def("_set_eager_tracer",
+        [](const std::shared_ptr<imperative::Tracer> &tracer) {
+          egr::Controller::Instance().SetCurrentTracer(tracer);
+        });
   m.def("stop_imperative_gperf_profiler", []() { imperative::StopProfile(); });
 
   m.def("_is_dygraph_debug_enabled",

paddle/fluid/pybind/pybind.cc

@@ -164,6 +164,7 @@ PyTypeObject *g_cpuplace_pytype = nullptr;
 PyTypeObject *g_xpuplace_pytype = nullptr;
 PyTypeObject *g_npuplace_pytype = nullptr;
 PyTypeObject *g_cudapinnedplace_pytype = nullptr;
+PyTypeObject *g_framework_tensor_pytype = nullptr;
 
 bool IsCompiledWithCUDA() {
 #if !defined(PADDLE_WITH_CUDA) && !defined(PADDLE_WITH_HIP)
@@ -733,7 +734,11 @@ PYBIND11_MODULE(core_noavx, m) {
 
   BindImperative(&m);
 
-  py::class_<framework::Tensor>(m, "Tensor", py::buffer_protocol())
+  py::class_<framework::Tensor> framework_tensor(m, "Tensor",
+                                                 py::buffer_protocol());
+  g_framework_tensor_pytype =
+      reinterpret_cast<PyTypeObject *>(framework_tensor.ptr());
+  framework_tensor
       .def("__array__",
            [](framework::Tensor &self) { return TensorToPyArray(self); })
       .def("_is_initialized",

paddle/pten/api/lib/utils/tensor_utils.cc

@@ -411,6 +411,28 @@ void ReMakePtenDenseTensor(const paddle::framework::LoDTensor& src,
   }
 }
 
+void ReMakePtenDenseTensor(const paddle::framework::Tensor& src,
+                           pten::DenseTensor* dst) {
+  auto* meta = pten::CompatibleDenseTensorUtils::GetMutableMeta(dst);
+  meta->dims = src.dims();
+  // Since the type of DenseTensorMeta is const, const_cast must be used
+  const_cast<DataType&>(meta->dtype) = pten::TransToPtenDataType(src.type());
+  // Since the type of DenseTensorMeta is const, const_cast must be used
+  const_cast<DataLayout&>(meta->layout) =
+      pten::TransToPtenDataLayout(src.layout());
+
+  auto* shared_storage = static_cast<SharedStorage*>(
+      pten::CompatibleDenseTensorUtils::UnsafeGetMutableStorage(dst));
+  PADDLE_ENFORCE_NOT_NULL(
+      shared_storage,
+      platform::errors::NotFound(
+          "Target DenseTensor's shared storage is nullptr."));
+
+  if (src.IsInitialized()) {
+    shared_storage->ResetAllocation(src.Holder(), src.offset());
+  }
+}
+
 void ReMakePtenDenseTensor(const paddle::framework::LoDTensor& src,
                            const pten::TensorArgDef& arg_def,
                            pten::DenseTensor* dst) {

paddle/pten/api/lib/utils/tensor_utils.h

@@ -75,6 +75,9 @@ void MovesSharedStorage(pten::DenseTensor* src,
 void ReMakePtenDenseTensor(const paddle::framework::LoDTensor& src,
                            pten::DenseTensor* dst);
 
+void ReMakePtenDenseTensor(const paddle::framework::Tensor& src,
+                           pten::DenseTensor* dst);
+
 void ReMakePtenDenseTensor(const paddle::framework::Tensor& src,
                            const pten::TensorArgDef& arg_def,
                            pten::DenseTensor* dst);

python/paddle/fluid/core.py

@@ -268,6 +268,7 @@ if avx_supported():
         from .core_avx import _is_dygraph_debug_enabled
         from .core_avx import _dygraph_debug_level
         from .core_avx import _switch_tracer
+        from .core_avx import _set_eager_tracer
         from .core_avx import _disable_eager_mode
         from .core_avx import _enable_eager_mode
         from .core_avx import _in_eager_mode
@@ -324,6 +325,7 @@ if load_noavx:
         from .core_noavx import _is_dygraph_debug_enabled
         from .core_noavx import _dygraph_debug_level
         from .core_noavx import _switch_tracer
+        from .core_noavx import _set_eager_tracer
         from .core_noavx import _disable_eager_mode
         from .core_noavx import _enable_eager_mode
         from .core_noavx import _in_eager_mode

python/paddle/fluid/framework.py

@@ -81,10 +81,13 @@ core._disable_eager_mode()
 
 
 @signature_safe_contextmanager
-def _test_eager_guard():
+def _test_eager_guard(tracer=None):
     core._enable_eager_mode()
     _C_ops.switch_to_eager_ops()
-    core._switch_tracer(_dygraph_tracer_)
+    if tracer is None:
+        core._set_eager_tracer(_dygraph_tracer_)
+    else:
+        core._set_eager_tracer(tracer)
     try:
         yield
     finally:

python/paddle/fluid/tests/unittests/test_egr_python_api.py

@@ -16,7 +16,7 @@ import paddle.fluid.core as core
 import paddle.fluid.eager.eager_tensor_patch_methods as eager_tensor_patch_methods
 import paddle
 import numpy as np
-from paddle.fluid.framework import _test_eager_guard, EagerParamBase
+from paddle.fluid.framework import _test_eager_guard, EagerParamBase, _in_eager_mode
 from paddle.fluid.data_feeder import convert_dtype
 import unittest
 import copy
@@ -221,6 +221,36 @@ class EagerTensorPropertiesTestCase(unittest.TestCase):
         self.assertTrue(egr_tensor9.place._equals(place))
         self.assertTrue(np.array_equal(egr_tensor9.numpy(), arr4))
 
+        x = np.random.rand(3, 3).astype('float32')
+        t = paddle.fluid.Tensor()
+        t.set(x, paddle.fluid.CPUPlace())
+        egr_tensor10 = core.eager.EagerTensor(t, place)
+        self.assertEqual(egr_tensor10.persistable, False)
+        self.assertTrue("generated_tensor" in egr_tensor10.name)
+        self.assertEqual(egr_tensor10.shape, [3, 3])
+        self.assertEqual(egr_tensor10.dtype, core.VarDesc.VarType.FP32)
+        self.assertEqual(egr_tensor10.stop_gradient, True)
+        self.assertTrue(egr_tensor10.place._equals(place))
+        self.assertTrue(np.array_equal(egr_tensor10.numpy(), x))
+
+        egr_tensor11 = core.eager.EagerTensor(t, place, "framework_constructed")
+        self.assertEqual(egr_tensor11.persistable, False)
+        self.assertTrue("framework_constructed" in egr_tensor11.name)
+        self.assertEqual(egr_tensor11.shape, [3, 3])
+        self.assertEqual(egr_tensor11.dtype, core.VarDesc.VarType.FP32)
+        self.assertEqual(egr_tensor11.stop_gradient, True)
+        self.assertTrue(egr_tensor11.place._equals(place))
+        self.assertTrue(np.array_equal(egr_tensor11.numpy(), x))
+
+        egr_tensor12 = core.eager.EagerTensor(t)
+        self.assertEqual(egr_tensor12.persistable, False)
+        self.assertTrue("generated_tensor" in egr_tensor12.name)
+        self.assertEqual(egr_tensor12.shape, [3, 3])
+        self.assertEqual(egr_tensor12.dtype, core.VarDesc.VarType.FP32)
+        self.assertEqual(egr_tensor12.stop_gradient, True)
+        self.assertTrue(egr_tensor12.place._equals(paddle.fluid.CPUPlace()))
+        self.assertTrue(np.array_equal(egr_tensor12.numpy(), x))
+
         with self.assertRaisesRegexp(
                 ValueError, "The shape of Parameter should not be None"):
             eager_param = EagerParamBase(shape=None, dtype="float32")
@@ -423,5 +453,12 @@ class EagerParamBaseUsageTestCase(unittest.TestCase):
         self.assertTrue(np.array_equal(res3, res4))
 
 
+class EagerGuardTestCase(unittest.TestCase):
+    def test__test_eager_guard(self):
+        tracer = paddle.fluid.dygraph.tracer.Tracer()
+        with _test_eager_guard(tracer):
+            self.assertTrue(_in_eager_mode())
+
+
 if __name__ == "__main__":
     unittest.main()

python/paddle/fluid/tests/unittests/test_imperative_basic.py

@@ -24,7 +24,7 @@ from test_imperative_base import new_program_scope
 import paddle.fluid.dygraph_utils as dygraph_utils
 from paddle.fluid.dygraph.layer_object_helper import LayerObjectHelper
 import paddle
-from paddle.fluid.framework import _test_eager_guard
+from paddle.fluid.framework import _test_eager_guard, _in_eager_mode
 
 
 class MyLayer(fluid.Layer):
@@ -259,12 +259,28 @@ class TestImperative(unittest.TestCase):
             self.func_isinstance()
         self.func_isinstance()
 
-    def test_create_VarBase(self):
+    def func_create_varbase(self):
         x = np.ones([2, 2], np.float32)
         y = np.zeros([3, 3], np.float32)
         t = fluid.Tensor()
         t.set(x, fluid.CPUPlace())
-        with fluid.dygraph.guard():
+        if _in_eager_mode():
+            # TODO(jiabin): Support Kwargs and uncomment these tests
+            # egr_tmp = fluid.core.eager.EagerTensor(value=x, place=fluid.core.CPUPlace())
+            egr_tmp2 = fluid.core.eager.EagerTensor(y, fluid.core.CPUPlace())
+            egr_tmp3 = paddle.to_tensor(x)
+            egr_tmp4 = fluid.core.eager.EagerTensor(y)
+            # egr_tmp5 = fluid.core.eager.EagerTensor(value=x)
+            # TODO(jiabin): Support it when we merge LoDTensor with DenseTensor
+            egr_tmp6 = fluid.core.eager.EagerTensor(t)
+
+            # self.assertTrue(np.array_equal(x, egr_tmp.numpy()))
+            self.assertTrue(np.array_equal(y, egr_tmp2.numpy()))
+            self.assertTrue(np.array_equal(x, egr_tmp3.numpy()))
+            self.assertTrue(np.array_equal(y, egr_tmp4.numpy()))
+            # self.assertTrue(np.array_equal(x, egr_tmp5.numpy()))
+            self.assertTrue(np.array_equal(x, egr_tmp6.numpy()))
+        else:
             tmp = fluid.core.VarBase(value=x, place=fluid.core.CPUPlace())
             tmp2 = fluid.core.VarBase(y, fluid.core.CPUPlace())
             tmp3 = paddle.to_tensor(x)
@@ -279,6 +295,12 @@ class TestImperative(unittest.TestCase):
             self.assertTrue(np.array_equal(x, tmp5.numpy()))
             self.assertTrue(np.array_equal(x, tmp6.numpy()))
 
+    def test_create_varbase(self):
+        with fluid.dygraph.guard():
+            with _test_eager_guard():
+                self.func_create_varbase()
+            self.func_create_varbase()
+
     def test_no_grad_guard(self):
         data = np.array([[2, 3], [4, 5]]).astype('float32')
         with fluid.dygraph.guard():
@@ -758,7 +780,7 @@ class TestImperative(unittest.TestCase):
         self.assertTrue(np.allclose(dy_grad_h2h2, static_grad_h2h))
         self.assertTrue(np.allclose(dy_grad_i2h2, static_grad_i2h))
 
-    def test_layer_attrs(self):
+    def func_layer_attrs(self):
         layer = fluid.dygraph.Layer("test")
         layer.test_attr = 1
         self.assertFalse(hasattr(layer, "whatever"))
@@ -778,6 +800,11 @@ class TestImperative(unittest.TestCase):
         my_layer.l1 = None
         self.assertEqual(len(my_layer.sublayers()), 0)
 
+    def test_layer_attrs(self):
+        with _test_eager_guard():
+            self.func_layer_attrs()
+        self.func_layer_attrs()
+
 
 class TestDygraphUtils(unittest.TestCase):
     def func_append_activation_in_dygraph_exception(self):