[Eager] dlpack (#40811)

* dlpack eager, test=develop

* eager test_base_layer, test=develop

* fix error report, test=develop

* eager _getitem_from_offset, test=develop

* refine, test=develop

* refine offset, test=develop

* add test_inner test_outer, test=develop

* refine, test=develop

* refine, test=develop

paddle/fluid/eager/utils.h

@@ -137,7 +137,10 @@ class EagerUtils {
 
   template <typename T, typename... Args>
   static bool ComputeRequireGrad(T trace_backward, Args&&... args) {
-    if (!trace_backward) return false;
+    if (!trace_backward) {
+      VLOG(6) << "Do not require grad because trace_backward = false";
+      return false;
+    }
 
     auto iter = ComputeRequireGradIter();
     iter.apply(std::forward<Args>(args)...);

paddle/fluid/pybind/eager_method.cc

@@ -25,7 +25,6 @@ limitations under the License. */
 #include "paddle/fluid/eager/hooks.h"
 #include "paddle/fluid/eager/utils.h"
 #include "paddle/fluid/framework/convert_utils.h"
-#include "paddle/fluid/framework/python_headers.h"
 #include "paddle/fluid/memory/allocation/allocator.h"
 #include "paddle/fluid/memory/memcpy.h"
 #include "paddle/fluid/platform/enforce.h"
@@ -33,7 +32,6 @@ limitations under the License. */
 #include "paddle/fluid/pybind/eager_utils.h"
 #include "paddle/fluid/pybind/exception.h"
 #include "paddle/fluid/pybind/slice_utils.h"
-#include "paddle/fluid/pybind/tensor_py.h"
 #include "paddle/phi/api/include/api.h"
 #include "paddle/phi/common/data_type.h"
 #include "paddle/phi/core/compat/convert_utils.h"
@@ -41,6 +39,9 @@ limitations under the License. */
 #include "paddle/phi/core/sparse_coo_tensor.h"
 #include "paddle/phi/core/sparse_csr_tensor.h"
 #include "pybind11/detail/internals.h"
+#pragma GCC diagnostic ignored "-Wmissing-field-initializers"
+#include "paddle/fluid/framework/python_headers.h"
+#include "paddle/fluid/pybind/tensor_py.h"
 
 namespace paddle {
 namespace pybind {
@@ -682,6 +683,103 @@ static PyObject* tensor__getitem_index_not_tensor(TensorObject* self,
   EAGER_CATCH_AND_THROW_RETURN_NULL
 }
 
+static PyObject* tensor__getitem_from_offset(TensorObject* self, PyObject* args,
+                                             PyObject* kwargs) {
+  EAGER_TRY
+  auto ptr = static_cast<phi::DenseTensor*>(self->tensor.impl().get());
+  PADDLE_ENFORCE_NOT_NULL(
+      ptr, platform::errors::InvalidArgument("%s is not a DenseTensor.",
+                                             self->tensor.name()));
+  const auto& tensor = *ptr;
+  PADDLE_ENFORCE_EQ(
+      tensor.IsInitialized(), true,
+      platform::errors::InvalidArgument(
+          "Tensor of %s is Empty, please check if it has no data.",
+          self->tensor.name()));
+
+  const auto& tensor_dims = tensor.dims();
+
+  std::vector<size_t> dims(tensor_dims.size());
+  std::vector<size_t> strides(tensor_dims.size());
+
+  size_t numel = 1;
+  for (int i = tensor_dims.size() - 1; i >= 0; --i) {
+    strides[i] = numel;
+    dims[i] = static_cast<size_t>(tensor_dims[i]);
+    numel *= dims[i];
+  }
+  size_t offset = 0;
+  if (PyTuple_Size(args) == 0) {
+    PADDLE_ENFORCE_EQ(numel, 1,
+                      platform::errors::InvalidArgument(
+                          "only one element tensors can be converted to Python "
+                          "scalars when no input coordinates"));
+  } else if (PyTuple_Size(args) == 1) {
+    offset = CastPyArg2AttrLong(PyTuple_GET_ITEM(args, 0), 0);
+    PADDLE_ENFORCE_LT(
+        offset, numel,
+        platform::errors::InvalidArgument(
+            "index %d is out of bounds for size %d", offset, numel));
+  } else {
+    PADDLE_ENFORCE_EQ(PyTuple_Size(args), dims.size(),
+                      platform::errors::InvalidArgument(
+                          "incorrect number of indices for Tensor"));
+
+    for (Py_ssize_t i = 0; i < PyTuple_Size(args); ++i) {
+      size_t index = CastPyArg2AttrLong(PyTuple_GET_ITEM(args, i), i);
+      PADDLE_ENFORCE_LT(
+          index, dims[i],
+          platform::errors::InvalidArgument(
+              "index %d is out fo bounds for axis %d with size %d", index, i,
+              dims[i]));
+      offset += index * strides[i];
+    }
+  }
+#define PD_FOR_EACH_DENSE_TENSOR_DATA_TYPE(_) \
+  _(bool, DataType::BOOL)                     \
+  _(int8_t, DataType::INT8)                   \
+  _(uint8_t, DataType::UINT8)                 \
+  _(int16_t, DataType::INT16)                 \
+  _(uint16_t, DataType::UINT16)               \
+  _(int32_t, DataType::INT32)                 \
+  _(uint32_t, DataType::UINT32)               \
+  _(int64_t, DataType::INT64)                 \
+  _(uint64_t, DataType::UINT64)               \
+  _(bfloat16, DataType::BFLOAT16)             \
+  _(float16, DataType::FLOAT16)               \
+  _(float, DataType::FLOAT32)                 \
+  _(double, DataType::FLOAT64)                \
+  _(complex64, DataType::COMPLEX64)           \
+  _(complex128, DataType::COMPLEX128)
+
+#define TENSOR_TO_PY_SCALAR(T, proto_type)                                   \
+  if (tensor.dtype() == proto_type) {                                        \
+    auto numpy_dtype = TensorDtype2NumpyDtype(proto_type);                   \
+    T b = paddle::pybind::TensorGetElement<T>(tensor, offset);               \
+    Py_intptr_t py_dims[paddle::framework::DDim::kMaxRank];                  \
+    Py_intptr_t py_strides[paddle::framework::DDim::kMaxRank];               \
+    py_dims[0] = 1;                                                          \
+    py_strides[0] = 1;                                                       \
+    auto& api = pybind11::detail::npy_api::get();                            \
+    PyObject* array = api.PyArray_NewFromDescr_(                             \
+        api.PyArray_Type_, api.PyArray_DescrFromType_(numpy_dtype), 1,       \
+        py_dims, py_strides, nullptr,                                        \
+        pybind11::detail::npy_api::NPY_ARRAY_ALIGNED_ |                      \
+            pybind11::detail::npy_api::NPY_ARRAY_WRITEABLE_,                 \
+        nullptr);                                                            \
+    std::memcpy(                                                             \
+        reinterpret_cast<void*>(pybind11::detail::array_proxy(array)->data), \
+        static_cast<void*>(&b), sizeof(b));                                  \
+    return array;                                                            \
+  }
+
+  PD_FOR_EACH_DENSE_TENSOR_DATA_TYPE(TENSOR_TO_PY_SCALAR);
+#undef TENSOR_TO_PY_SCALAR
+  PADDLE_THROW(platform::errors::Unimplemented(
+      "Unsupported tensor data type: %s", tensor.dtype()));
+  EAGER_CATCH_AND_THROW_RETURN_NULL
+}
+
 static PyObject* tensor_method__setitem_eager_tensor(TensorObject* self,
                                                      PyObject* args,
                                                      PyObject* kwargs) {
@@ -1252,6 +1350,9 @@ PyMethodDef variable_methods[] = {
     {"_getitem_index_not_tensor",
      (PyCFunction)(void (*)(void))tensor__getitem_index_not_tensor,
      METH_VARARGS | METH_KEYWORDS, NULL},
+    {"_getitem_from_offset",
+     (PyCFunction)(void (*)(void))tensor__getitem_from_offset,
+     METH_VARARGS | METH_KEYWORDS, NULL},
     {"__setitem_eager_tensor__",
      (PyCFunction)(void (*)(void))tensor_method__setitem_eager_tensor,
      METH_VARARGS | METH_KEYWORDS, NULL},

paddle/fluid/pybind/eager_utils.cc

@@ -633,8 +633,15 @@ paddle::optional<const paddle::experimental::Tensor&> GetOptionalTensorFromArgs(
     return paddle::none;
   }
 
-  return paddle::make_optional<const paddle::experimental::Tensor&>(
-      reinterpret_cast<TensorObject*>(obj)->tensor);
+  if (PyObject_IsInstance(obj, reinterpret_cast<PyObject*>(p_tensor_type))) {
+    return paddle::make_optional<const paddle::experimental::Tensor&>(
+        reinterpret_cast<TensorObject*>(obj)->tensor);
+  } else {
+    PADDLE_THROW(platform::errors::InvalidArgument(
+        "%s(): argument '%s' (position %d) must be Tensor, but got %s", op_type,
+        arg_name, arg_idx,
+        reinterpret_cast<PyTypeObject*>(obj->ob_type)->tp_name));
+  }
 }
 
 static paddle::experimental::Tensor& GetTensorFromPyObject(
@@ -654,7 +661,14 @@ static paddle::experimental::Tensor& GetTensorFromPyObject(
     return emptytensor;
   }
 
-  return reinterpret_cast<TensorObject*>(obj)->tensor;
+  if (PyObject_IsInstance(obj, reinterpret_cast<PyObject*>(p_tensor_type))) {
+    return reinterpret_cast<TensorObject*>(obj)->tensor;
+  } else {
+    PADDLE_THROW(platform::errors::InvalidArgument(
+        "%s(): argument '%s' (position %d) must be Tensor, but got %s", op_type,
+        arg_name, arg_idx,
+        reinterpret_cast<PyTypeObject*>(obj->ob_type)->tp_name));
+  }
 }
 
 // For Intermediate State Dygraph,
@@ -744,7 +758,14 @@ paddle::experimental::Tensor* GetTensorPtrFromArgs(const std::string& op_type,
     return &emptytensor;
   }
 
-  return &(reinterpret_cast<TensorObject*>(obj)->tensor);
+  if (PyObject_IsInstance(obj, reinterpret_cast<PyObject*>(p_tensor_type))) {
+    return &(reinterpret_cast<TensorObject*>(obj)->tensor);
+  } else {
+    PADDLE_THROW(platform::errors::InvalidArgument(
+        "%s(): argument '%s' (position %d) must be Tensor, but got %s", op_type,
+        arg_name, arg_idx,
+        reinterpret_cast<PyTypeObject*>(obj->ob_type)->tp_name));
+  }
 }
 
 std::vector<paddle::experimental::Tensor*> GetTensorPtrListFromArgs(

python/paddle/fluid/dygraph/layers.py

@@ -764,7 +764,7 @@ class Layer(object):
         elif tensor is not None and not (type(tensor) == core.VarBase or
                                          type(tensor) == core.eager.Tensor):
             raise TypeError(
-                "The registered buffer should be a core.VarBase, but received {}.".
+                "The registered buffer should be a Paddle.Tensor, but received {}.".
                 format(type(tensor).__name__))
         else:
             self._buffers[name] = tensor
@@ -1158,8 +1158,7 @@ class Layer(object):
                 layers[name] = None
             else:
                 _buffers = self.__dict__.get('_buffers', None)
-                if type(value) == core.VarBase or \
-                    type(value) == core.eager.Tensor:
+                if isinstance(value, (core.VarBase, core.eager.Tensor)):
                     if _buffers is None:
                         raise ValueError(
                             "super(YourLayer, self).__init__() should be called first"

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

@@ -18,8 +18,9 @@ import numpy as np
 import paddle
 import paddle.fluid as fluid
 from paddle.fluid.dygraph import to_variable
-from paddle.fluid.framework import ParamBase
+from paddle.fluid.framework import ParamBase, EagerParamBase
 from paddle.jit import ProgramTranslator
+from paddle.fluid.framework import _test_eager_guard, in_dygraph_mode
 
 
 class L1(fluid.Layer):
@@ -57,7 +58,7 @@ class L3(fluid.Layer):
 
 
 class TestBaseLayer(unittest.TestCase):
-    def test_one_level(self):
+    def func_test_one_level(self):
         with fluid.dygraph.guard():
             l = L1()
             ret = l()
@@ -68,7 +69,12 @@ class TestBaseLayer(unittest.TestCase):
                 idx += 1
             self.assertTrue(np.allclose(ret.numpy(), 0.2 * np.ones([2, 2])))
 
-    def test_three_level(self):
+    def test_one_level(self):
+        with _test_eager_guard():
+            self.func_test_one_level()
+        self.func_test_one_level()
+
+    def func_test_three_level(self):
         with fluid.dygraph.guard():
             l = L3()
             expected_names = [
@@ -88,7 +94,12 @@ class TestBaseLayer(unittest.TestCase):
             ret = l()
             self.assertTrue(np.allclose(ret.numpy(), 0.8 * np.ones([2, 2])))
 
-    def test_add_parameter_with_error(self):
+    def test_three_level(self):
+        with _test_eager_guard():
+            self.func_test_three_level()
+        self.func_test_three_level()
+
+    def func_test_add_parameter_with_error(self):
         with fluid.dygraph.guard():
             net = fluid.Layer()
             param = net.create_parameter(shape=[1])
@@ -113,6 +124,11 @@ class TestBaseLayer(unittest.TestCase):
             net._loaddict_holder[load_param.name] = load_param
             net.add_parameter("load_param", load_param)
 
+    def test_add_parameter_with_error(self):
+        with _test_eager_guard():
+            self.func_test_add_parameter_with_error()
+        self.func_test_add_parameter_with_error()
+
 
 class BufferLayer(fluid.Layer):
     def __init__(self):
@@ -140,7 +156,7 @@ class BufferNet(fluid.Layer):
 
 
 class TestBuffer(unittest.TestCase):
-    def test_buffers_and_named_buffers(self):
+    def func_test_buffers_and_named_buffers(self):
         def names(named_buffers):
             return [name for name, _ in named_buffers]
 
@@ -161,7 +177,12 @@ class TestBuffer(unittest.TestCase):
                 names(net.named_buffers(include_sublayers=False)),
                 ['net_buffer', 'new_buffer'])
 
-    def test_register_buffer_with_error(self):
+    def test_buffers_and_named_buffers(self):
+        with _test_eager_guard():
+            self.func_test_buffers_and_named_buffers()
+        self.func_test_buffers_and_named_buffers()
+
+    def func_test_register_buffer_with_error(self):
         with fluid.dygraph.guard():
             net = fluid.Layer()
             var = to_variable(np.zeros([1]))
@@ -171,8 +192,13 @@ class TestBuffer(unittest.TestCase):
                 net.register_buffer(12, var)
 
             with self.assertRaisesRegexp(TypeError,
-                                         "buffer should be a core.VarBase"):
-                net.register_buffer("buffer_name", ParamBase([2, 2], 'float32'))
+                                         "buffer should be a Paddle.Tensor"):
+                if in_dygraph_mode():
+                    net.register_buffer("buffer_name",
+                                        EagerParamBase([2, 2], 'float32'))
+                else:
+                    net.register_buffer("buffer_name",
+                                        ParamBase([2, 2], 'float32'))
 
             with self.assertRaisesRegexp(KeyError,
                                          "name of buffer can not contain"):
@@ -187,11 +213,19 @@ class TestBuffer(unittest.TestCase):
                 net.register_buffer("attr_name", var)
 
             del net.attr_name
-            net.attr_name = ParamBase([2, 2], 'float32')
+            if in_dygraph_mode():
+                net.attr_name = EagerParamBase([2, 2], 'float32')
+            else:
+                net.attr_name = ParamBase([2, 2], 'float32')
             with self.assertRaisesRegexp(KeyError, "already exists"):
                 net.register_buffer("attr_name", var)
 
-    def test_register_buffer_same_name(self):
+    def test_register_buffer_with_error(self):
+        with _test_eager_guard():
+            self.func_test_register_buffer_with_error()
+        self.func_test_register_buffer_with_error()
+
+    def func_test_register_buffer_same_name(self):
         with fluid.dygraph.guard():
             net = fluid.Layer()
             var1 = to_variable(np.zeros([1]))
@@ -205,7 +239,12 @@ class TestBuffer(unittest.TestCase):
             net.register_buffer("buffer_name", var3)
             self.assert_var_base_equal(net.buffer_name, var3)
 
-    def test_buffer_not_persistable(self):
+    def test_register_buffer_same_name(self):
+        with _test_eager_guard():
+            self.func_test_register_buffer_same_name()
+        self.func_test_register_buffer_same_name()
+
+    def func_test_buffer_not_persistable(self):
         with fluid.dygraph.guard():
             net = fluid.Layer()
             var1 = to_variable(np.zeros([1]))
@@ -214,7 +253,12 @@ class TestBuffer(unittest.TestCase):
             self.assertEqual(len(net.buffers()), 1)
             self.assertEqual(len(net.state_dict()), 0)
 
-    def test_buffer_not_persistable_del(self):
+    def test_buffer_not_persistable(self):
+        with _test_eager_guard():
+            self.func_test_buffer_not_persistable()
+        self.func_test_buffer_not_persistable()
+
+    def func_test_buffer_not_persistable_del(self):
         with fluid.dygraph.guard():
             net = fluid.Layer()
             var1 = to_variable(np.zeros([1]))
@@ -222,7 +266,12 @@ class TestBuffer(unittest.TestCase):
             del net.buffer_name
             self.assertEqual(len(net.buffers()), 0)
 
-    def test_buffer_not_persistable_overwrite(self):
+    def test_buffer_not_persistable_del(self):
+        with _test_eager_guard():
+            self.func_test_buffer_not_persistable_del()
+        self.func_test_buffer_not_persistable_del()
+
+    def func_test_buffer_not_persistable_overwrite(self):
         with fluid.dygraph.guard():
             net = fluid.Layer()
             var1 = to_variable(np.zeros([1]))
@@ -238,7 +287,12 @@ class TestBuffer(unittest.TestCase):
             self.assertEqual(len(net.buffers()), 1)
             self.assertEqual(len(net.state_dict()), 0)
 
-    def test_buffer_not_persistable_assign(self):
+    def test_buffer_not_persistable_overwrite(self):
+        with _test_eager_guard():
+            self.func_test_buffer_not_persistable_overwrite()
+        self.func_test_buffer_not_persistable_overwrite()
+
+    def func_test_buffer_not_persistable_assign(self):
         with fluid.dygraph.guard():
             net = fluid.Layer()
             var1 = to_variable(np.zeros([1]))
@@ -255,18 +309,31 @@ class TestBuffer(unittest.TestCase):
             self.assertEqual(len(net.state_dict()), 0)
 
             # Re-assign a ParamBase will remove the buffer.
-            net.buffer_name = ParamBase([2, 2], 'float32')
+            if in_dygraph_mode():
+                net.buffer_name = EagerParamBase([2, 2], 'float32')
+            else:
+                net.buffer_name = ParamBase([2, 2], 'float32')
             self.assertEqual(len(net.buffers()), 0)
             self.assertEqual(len(net.state_dict()), 1)
 
-    def test_buffer_not_persistable_load(self):
+    def test_buffer_not_persistable_assign(self):
+        with _test_eager_guard():
+            self.func_test_buffer_not_persistable_assign()
+        self.func_test_buffer_not_persistable_assign()
+
+    def func_test_buffer_not_persistable_load(self):
         with fluid.dygraph.guard():
             net = fluid.Layer()
             var1 = to_variable(np.zeros([1]))
             net.register_buffer("buffer_name", var1, persistable=False)
             net.load_dict({})
 
-    def test_buffer_state_dict(self):
+    def test_buffer_not_persistable_load(self):
+        with _test_eager_guard():
+            self.func_test_buffer_not_persistable_load()
+        self.func_test_buffer_not_persistable_load()
+
+    def func_test_buffer_state_dict(self):
         with fluid.dygraph.guard():
             net = fluid.Layer()
             var1 = to_variable(np.zeros([2, 3]))
@@ -286,6 +353,11 @@ class TestBuffer(unittest.TestCase):
 
             self.assert_var_base_equal(net_load.buffer_var1, var1)
 
+    def test_buffer_state_dict(self):
+        with _test_eager_guard():
+            self.func_test_buffer_state_dict()
+        self.func_test_buffer_state_dict()
+
     def assert_var_base_equal(self, var1, var2):
         self.assertTrue(np.array_equal(var1.numpy(), var2.numpy()))
 
@@ -308,7 +380,7 @@ class BufferNetWithModification(paddle.nn.Layer):
 
 
 class TestModifiedBuffer(unittest.TestCase):
-    def setUp(self):
+    def funcsetUp(self):
         paddle.disable_static()
         self.prog_trans = ProgramTranslator()
         self.shape = [10, 16]
@@ -322,7 +394,8 @@ class TestModifiedBuffer(unittest.TestCase):
 
         return out, net.buffer1, net.buffer2
 
-    def test_modified(self):
+    def func_test_modified(self):
+        self.funcsetUp()
         dy_outs = self._run(False)
         st_outs = self._run(True)
 
@@ -330,9 +403,14 @@ class TestModifiedBuffer(unittest.TestCase):
             self.assertTrue(
                 np.array_equal(dy_outs[i].numpy(), st_outs[i].numpy()))
 
+    def test_modified(self):
+        with _test_eager_guard():
+            self.func_test_modified()
+        self.func_test_modified()
+
 
 class TestLayerTo(unittest.TestCase):
-    def setUp(self):
+    def funcsetUp(self):
         paddle.disable_static()
         self.linear = paddle.nn.Linear(2, 2)
         self.new_grad = np.random.random([2, 2])
@@ -343,7 +421,7 @@ class TestLayerTo(unittest.TestCase):
         sublayer = paddle.nn.Conv1D(3, 2, 3)
         self.linear.add_sublayer("1", sublayer)
 
-    def test_to_api(self):
+    def func_test_to_api(self):
         self.linear.to(dtype='double')
         self.assertEqual(self.linear.weight.dtype,
                          paddle.fluid.core.VarDesc.VarType.FP64)
@@ -364,7 +442,11 @@ class TestLayerTo(unittest.TestCase):
         self.assertEqual(self.linear.weight._grad_ivar().dtype,
                          paddle.fluid.core.VarDesc.VarType.FP64)
         for p in self.linear.parameters():
-            self.assertTrue(isinstance(p, paddle.fluid.framework.ParamBase))
+            if in_dygraph_mode():
+                self.assertTrue(
+                    isinstance(p, paddle.fluid.framework.EagerParamBase))
+            else:
+                self.assertTrue(isinstance(p, paddle.fluid.framework.ParamBase))
 
         if paddle.fluid.is_compiled_with_cuda():
             self.linear.to(device=paddle.CUDAPlace(0))
@@ -387,7 +469,12 @@ class TestLayerTo(unittest.TestCase):
             self.assertEqual(
                 self.linear.weight._grad_ivar().place.gpu_device_id(), 0)
             for p in self.linear.parameters():
-                self.assertTrue(isinstance(p, paddle.fluid.framework.ParamBase))
+                if in_dygraph_mode():
+                    self.assertTrue(
+                        isinstance(p, paddle.fluid.framework.EagerParamBase))
+                else:
+                    self.assertTrue(
+                        isinstance(p, paddle.fluid.framework.ParamBase))
 
         self.linear.to(device=paddle.CPUPlace())
         self.assertTrue(self.linear.weight.place.is_cpu_place())
@@ -403,7 +490,7 @@ class TestLayerTo(unittest.TestCase):
 
         self.assertRaises(AssertionError, self.linear.to, blocking=1)
 
-    def test_to_api_paddle_dtype(self):
+    def func_test_to_api_paddle_dtype(self):
         self.linear.to(dtype=paddle.float64)
         self.assertEqual(self.linear.weight.dtype,
                          paddle.fluid.core.VarDesc.VarType.FP64)
@@ -424,9 +511,13 @@ class TestLayerTo(unittest.TestCase):
         self.assertEqual(self.linear.weight._grad_ivar().dtype,
                          paddle.fluid.core.VarDesc.VarType.FP64)
         for p in self.linear.parameters():
-            self.assertTrue(isinstance(p, paddle.fluid.framework.ParamBase))
+            if in_dygraph_mode():
+                self.assertTrue(
+                    isinstance(p, paddle.fluid.framework.EagerParamBase))
+            else:
+                self.assertTrue(isinstance(p, paddle.fluid.framework.ParamBase))
 
-    def test_to_api_numpy_dtype(self):
+    def func_test_to_api_numpy_dtype(self):
         self.linear.to(dtype=np.float64)
         self.assertEqual(self.linear.weight.dtype,
                          paddle.fluid.core.VarDesc.VarType.FP64)
@@ -447,7 +538,22 @@ class TestLayerTo(unittest.TestCase):
         self.assertEqual(self.linear.weight._grad_ivar().dtype,
                          paddle.fluid.core.VarDesc.VarType.FP64)
         for p in self.linear.parameters():
-            self.assertTrue(isinstance(p, paddle.fluid.framework.ParamBase))
+            if in_dygraph_mode():
+                self.assertTrue(
+                    isinstance(p, paddle.fluid.framework.EagerParamBase))
+            else:
+                self.assertTrue(isinstance(p, paddle.fluid.framework.ParamBase))
+
+    def test_main(self):
+        with _test_eager_guard():
+            self.funcsetUp()
+            self.func_test_to_api()
+            self.func_test_to_api_paddle_dtype()
+            self.func_test_to_api_numpy_dtype()
+        self.funcsetUp()
+        self.func_test_to_api()
+        self.func_test_to_api_paddle_dtype()
+        self.func_test_to_api_numpy_dtype()
 
 
 if __name__ == '__main__':

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

@@ -17,6 +17,7 @@ import unittest
 import numpy as np
 import six
 import paddle
+from paddle.fluid.framework import _test_eager_guard, in_dygraph_mode
 
 
 def numpy_cov(np_arr, rowvar=True, ddof=1, fweights=None, aweights=None):
@@ -32,7 +33,7 @@ class Cov_Test(unittest.TestCase):
         self.shape = [20, 10]
         self.weightshape = [10]
 
-    def test_tensor_cov_default(self):
+    def func_test_tensor_cov_default(self):
         typelist = ['float64']
         places = [fluid.CPUPlace()]
         if fluid.core.is_compiled_with_cuda():
@@ -56,7 +57,12 @@ class Cov_Test(unittest.TestCase):
                     np_arr, rowvar=True, ddof=1, fweights=None, aweights=None)
                 self.assertTrue(np.allclose(np_cov, cov.numpy()))
 
-    def test_tensor_cov_rowvar(self):
+    def test_tensor_cov_default(self):
+        with _test_eager_guard():
+            self.func_test_tensor_cov_default()
+        self.func_test_tensor_cov_default()
+
+    def func_test_tensor_cov_rowvar(self):
         typelist = ['float64']
         places = [fluid.CPUPlace()]
         if fluid.core.is_compiled_with_cuda():
@@ -80,7 +86,12 @@ class Cov_Test(unittest.TestCase):
                     np_arr, rowvar=False, ddof=1, fweights=None, aweights=None)
                 self.assertTrue(np.allclose(np_cov, cov.numpy()))
 
-    def test_tensor_cov_ddof(self):
+    def test_tensor_cov_rowvar(self):
+        with _test_eager_guard():
+            self.func_test_tensor_cov_rowvar()
+        self.func_test_tensor_cov_rowvar()
+
+    def func_test_tensor_cov_ddof(self):
         typelist = ['float64']
         places = [fluid.CPUPlace()]
         if fluid.core.is_compiled_with_cuda():
@@ -104,7 +115,12 @@ class Cov_Test(unittest.TestCase):
                     np_arr, rowvar=True, ddof=0, fweights=None, aweights=None)
                 self.assertTrue(np.allclose(np_cov, cov.numpy()))
 
-    def test_tensor_cov_fweights(self):
+    def test_tensor_cov_ddof(self):
+        with _test_eager_guard():
+            self.func_test_tensor_cov_ddof()
+        self.func_test_tensor_cov_ddof()
+
+    def func_test_tensor_cov_fweights(self):
         typelist = ['float64']
         places = [fluid.CPUPlace()]
         if fluid.core.is_compiled_with_cuda():
@@ -131,7 +147,12 @@ class Cov_Test(unittest.TestCase):
                     np_arr, rowvar=True, ddof=1, fweights=np_fw, aweights=None)
                 self.assertTrue(np.allclose(np_cov, cov.numpy()))
 
-    def test_tensor_cov_aweights(self):
+    def test_tensor_cov_fweights(self):
+        with _test_eager_guard():
+            self.func_test_tensor_cov_fweights()
+        self.func_test_tensor_cov_fweights()
+
+    def func_test_tensor_cov_aweights(self):
         typelist = ['float64']
         places = [fluid.CPUPlace()]
         if fluid.core.is_compiled_with_cuda():
@@ -158,7 +179,12 @@ class Cov_Test(unittest.TestCase):
                     np_arr, rowvar=True, ddof=1, fweights=None, aweights=np_aw)
                 self.assertTrue(np.allclose(np_cov, cov.numpy()))
 
-    def test_tensor_cov_weights(self):
+    def test_tensor_cov_aweights(self):
+        with _test_eager_guard():
+            self.func_test_tensor_cov_aweights()
+        self.func_test_tensor_cov_aweights()
+
+    def func_test_tensor_cov_weights(self):
         typelist = ['float64']
         places = [fluid.CPUPlace()]
         if fluid.core.is_compiled_with_cuda():
@@ -187,6 +213,11 @@ class Cov_Test(unittest.TestCase):
                     np_arr, rowvar=True, ddof=1, fweights=np_fw, aweights=np_aw)
                 self.assertTrue(np.allclose(np_cov, cov.numpy()))
 
+    def test_tensor_cov_weights(self):
+        with _test_eager_guard():
+            self.func_test_tensor_cov_weights()
+        self.func_test_tensor_cov_weights()
+
 
 class Cov_Test2(Cov_Test):
     def setUp(self):
@@ -203,7 +234,7 @@ class Cov_Test3(unittest.TestCase):
         self.fw_s = 1.
         self.aw_s = 1.
 
-    def test_errors(self):
+    def func_test_errors(self):
         def test_err():
             np_arr = np.random.rand(*self.shape).astype('float64')
             np_fw = self.fw_s * np.random.rand(
@@ -221,6 +252,11 @@ class Cov_Test3(unittest.TestCase):
 
         self.assertRaises(ValueError, test_err)
 
+    def test_errors(self):
+        with _test_eager_guard():
+            self.func_test_errors()
+        self.func_test_errors()
+
 
 #Input(fweights) only support N-D (N<=1) tensor
 class Cov_Test4(Cov_Test3):

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

@@ -19,6 +19,7 @@ import numpy as np
 
 import paddle
 from paddle.static import Program, program_guard
+from paddle.fluid.framework import _test_eager_guard, in_dygraph_mode
 
 
 class TestMultiplyApi(unittest.TestCase):
@@ -48,7 +49,7 @@ class TestMultiplyApi(unittest.TestCase):
         res = paddle.inner(x, y)
         return res.numpy()
 
-    def test_multiply(self):
+    def func_test_multiply(self):
         np.random.seed(7)
 
         # test static computation graph: 3-d array
@@ -105,9 +106,14 @@ class TestMultiplyApi(unittest.TestCase):
         res = self._run_dynamic_graph_case(x_data, y_data)
         self.assertTrue(np.allclose(res, np.inner(x_data, y_data)))
 
+    def test_multiply(self):
+        with _test_eager_guard():
+            self.func_test_multiply()
+        self.func_test_multiply()
+
 
 class TestMultiplyError(unittest.TestCase):
-    def test_errors(self):
+    def func_test_errors(self):
         # test static computation graph: dtype can not be int8
         paddle.enable_static()
         with program_guard(Program(), Program()):
@@ -161,6 +167,11 @@ class TestMultiplyError(unittest.TestCase):
         y_data = np.random.randn(200).astype(np.float32)
         self.assertRaises(ValueError, paddle.inner, x_data, y_data)
 
+    def test_errors(self):
+        with _test_eager_guard():
+            self.func_test_errors()
+        self.func_test_errors()
+
 
 if __name__ == '__main__':
     paddle.enable_static()

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

@@ -20,6 +20,7 @@ import numpy as np
 import paddle
 import paddle.tensor as tensor
 from paddle.static import Program, program_guard
+from paddle.fluid.framework import _test_eager_guard, in_dygraph_mode
 
 
 class TestMultiplyApi(unittest.TestCase):
@@ -49,7 +50,7 @@ class TestMultiplyApi(unittest.TestCase):
         res = paddle.multiply(x, y)
         return res.numpy()
 
-    def test_multiply(self):
+    def func_test_multiply(self):
         np.random.seed(7)
 
         # test static computation graph: 1-d array
@@ -100,9 +101,14 @@ class TestMultiplyApi(unittest.TestCase):
         res = self._run_dynamic_graph_case(x_data, y_data)
         self.assertTrue(np.allclose(res, np.multiply(x_data, y_data)))
 
+    def test_multiply(self):
+        with _test_eager_guard():
+            self.func_test_multiply()
+        self.func_test_multiply()
+
 
 class TestMultiplyError(unittest.TestCase):
-    def test_errors(self):
+    def func_test_errors(self):
         # test static computation graph: dtype can not be int8
         paddle.enable_static()
         with program_guard(Program(), Program()):
@@ -175,6 +181,11 @@ class TestMultiplyError(unittest.TestCase):
         y_data = np.random.randn(200).astype(np.float32)
         self.assertRaises(ValueError, paddle.multiply, x_data, y_data)
 
+    def test_errors(self):
+        with _test_eager_guard():
+            self.func_test_errors()
+        self.func_test_errors()
+
 
 if __name__ == '__main__':
     unittest.main()

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

@@ -19,6 +19,7 @@ import numpy as np
 
 import paddle
 from paddle.static import Program, program_guard
+from paddle.fluid.framework import _test_eager_guard, in_dygraph_mode
 
 
 class TestMultiplyApi(unittest.TestCase):
@@ -48,7 +49,7 @@ class TestMultiplyApi(unittest.TestCase):
         res = paddle.outer(x, y)
         return res.numpy()
 
-    def test_multiply(self):
+    def func_test_multiply(self):
         np.random.seed(7)
 
         # test static computation graph: 3-d array
@@ -105,9 +106,14 @@ class TestMultiplyApi(unittest.TestCase):
         res = self._run_dynamic_graph_case(x_data, y_data)
         self.assertTrue(np.allclose(res, np.outer(x_data, y_data)))
 
+    def test_multiply(self):
+        with _test_eager_guard():
+            self.func_test_multiply()
+        self.func_test_multiply()
+
 
 class TestMultiplyError(unittest.TestCase):
-    def test_errors(self):
+    def func_test_errors(self):
         # test static computation graph: dtype can not be int8
         paddle.enable_static()
         with program_guard(Program(), Program()):
@@ -148,6 +154,11 @@ class TestMultiplyError(unittest.TestCase):
         y_data = np.random.randn(200).astype(np.float32)
         self.assertRaises(ValueError, paddle.outer, x_data, y_data)
 
+    def test_errors(self):
+        with _test_eager_guard():
+            self.func_test_errors()
+        self.func_test_errors()
+
 
 if __name__ == '__main__':
     unittest.main()

python/paddle/tensor/creation.py

@@ -127,7 +127,12 @@ def to_tensor(data, dtype=None, place=None, stop_gradient=True):
                     "\n\tFaild to convert input data to a regular ndarray :\n\t - Usually "
                     "this means the input data contains nested lists with different lengths. "
                 )
-        elif isinstance(data, (paddle.Tensor, core.eager.Tensor)):
+        elif isinstance(data, paddle.Tensor) and not in_dygraph_mode():
+            data = data._copy_to(place, False)
+            data = _handle_dtype(data, dtype)
+            data.stop_gradient = stop_gradient
+            return data
+        elif isinstance(data, core.eager.Tensor) and in_dygraph_mode():
             data = data._copy_to(place, False)
             data = _handle_dtype(data, dtype)
             data.stop_gradient = stop_gradient
@@ -136,7 +141,10 @@ def to_tensor(data, dtype=None, place=None, stop_gradient=True):
             # should't expose it to users, just for internal use.
             # convert core.Tensor/core.LoDTensor to VarBase first
             # Currenly, there is no copy when places are same
-            data = paddle.Tensor(data)
+            if in_dygraph_mode():
+                data = core.eager.Tensor(data)
+            else:
+                data = paddle.Tensor(data)
             if not data.place._equals(place):
                 data = data._copy_to(place, False)
             data = _handle_dtype(data, dtype)

python/paddle/tests/test_dlpack.py

@@ -18,21 +18,31 @@ import numpy as np
 import paddle
 import paddle.fluid as fluid
 import paddle.fluid.core as core
+from paddle.fluid.framework import _test_eager_guard, in_dygraph_mode
 
 
 class TestDLPack(unittest.TestCase):
-    def test_dlpack_dygraph(self):
+    def func_test_dlpack_dygraph(self):
         paddle.disable_static()
         tensor = paddle.to_tensor(np.array([1, 2, 3, 4]).astype('int'))
         dlpack = paddle.utils.dlpack.to_dlpack(tensor)
         out_from_dlpack = paddle.utils.dlpack.from_dlpack(dlpack)
-        self.assertTrue(isinstance(out_from_dlpack, paddle.Tensor))
+        if paddle.fluid.framework.in_dygraph_mode():
+            self.assertTrue(
+                isinstance(out_from_dlpack, paddle.fluid.core.eager.Tensor))
+        else:
+            self.assertTrue(isinstance(out_from_dlpack, paddle.Tensor))
         self.assertTrue(
             np.array_equal(
                 np.array(out_from_dlpack), np.array([1, 2, 3, 4]).astype(
                     'int')))
 
-    def test_dlpack_tensor_larger_than_2dim(self):
+    def test_dlpack_dygraph(self):
+        with _test_eager_guard():
+            self.func_test_dlpack_dygraph()
+        self.func_test_dlpack_dygraph()
+
+    def func_test_dlpack_tensor_larger_than_2dim(self):
         paddle.disable_static()
         numpy_data = np.random.randn(4, 5, 6)
         t = paddle.to_tensor(numpy_data)
@@ -41,6 +51,11 @@ class TestDLPack(unittest.TestCase):
         out = paddle.utils.dlpack.from_dlpack(dlpack)
         self.assertTrue(np.allclose(numpy_data, out.numpy()))
 
+    def test_dlpack_tensor_larger_than_2dim(self):
+        with _test_eager_guard():
+            self.func_test_dlpack_tensor_larger_than_2dim()
+        self.func_test_dlpack_tensor_larger_than_2dim()
+
     def test_dlpack_static(self):
         paddle.enable_static()
         tensor = fluid.create_lod_tensor(
@@ -67,7 +82,7 @@ class TestDLPack(unittest.TestCase):
                     np.array(gout_from_dlpack),
                     np.array([[1], [2], [3], [4]]).astype('int')))
 
-    def test_dlpack_dtype_conversion(self):
+    def func_test_dlpack_dtype_conversion(self):
         paddle.disable_static()
         # DLpack does not explicitly support bool data type.
         dtypes = [
@@ -98,15 +113,30 @@ class TestDLPack(unittest.TestCase):
             self.assertEqual(x.dtype, o.dtype)
             self.assertTrue(np.allclose(x.numpy(), o.numpy()))
 
+    def test_dlpack_dtype_conversion(self):
+        with _test_eager_guard():
+            self.func_test_dlpack_dtype_conversion()
+        self.func_test_dlpack_dtype_conversion()
+
 
 class TestRaiseError(unittest.TestCase):
-    def test_from_dlpack_raise_type_error(self):
+    def func_test_from_dlpack_raise_type_error(self):
         self.assertRaises(TypeError, paddle.utils.dlpack.from_dlpack,
                           np.zeros(5))
 
-    def test_to_dlpack_raise_type_error(self):
+    def test_from_dlpack_raise_type_error(self):
+        with _test_eager_guard():
+            self.func_test_from_dlpack_raise_type_error()
+        self.func_test_from_dlpack_raise_type_error()
+
+    def func_test_to_dlpack_raise_type_error(self):
         self.assertRaises(TypeError, paddle.utils.dlpack.to_dlpack, np.zeros(5))
 
+    def test_to_dlpack_raise_type_error(self):
+        with _test_eager_guard():
+            self.func_test_to_dlpack_raise_type_error()
+        self.func_test_to_dlpack_raise_type_error()
+
 
 if __name__ == '__main__':
     unittest.main()

python/paddle/utils/dlpack.py

@@ -48,7 +48,7 @@ def to_dlpack(x):
     """
 
     if _non_static_mode():
-        if not isinstance(x, paddle.Tensor):
+        if not isinstance(x, (paddle.Tensor, paddle.fluid.core.eager.Tensor)):
             raise TypeError(
                 "The type of 'x' in to_dlpack must be paddle.Tensor,"
                 " but received {}.".format(type(x)))