Merge pull request #28 from jim19930609/merge

Fixed python-c api

paddle/fluid/pybind/CMakeLists.txt

@@ -208,7 +208,7 @@ if(WITH_PYTHON)
 
   cc_library(paddle_eager
     SRCS eager.cc eager_functions.cc eager_method.cc eager_properties.cc eager_utils.cc
-    DEPS eager_api autograd_meta backward grad_node_info pten)
+    DEPS eager_api accumulation_node autograd_meta backward grad_node_info pten)
   list(APPEND PYBIND_DEPS paddle_eager)
 
   cc_library(paddle_pybind SHARED

paddle/fluid/pybind/eager_functions.cc

@@ -21,6 +21,7 @@ limitations under the License. */
 #include <string>
 #include <vector>
 
+#include "paddle/fluid/eager/accumulation/accumulation_node.h"
 #include "paddle/fluid/eager/api/all.h"
 #include "paddle/fluid/eager/autograd_meta.h"
 #include "paddle/fluid/eager/backward.h"
@@ -30,6 +31,7 @@ limitations under the License. */
 #include "paddle/fluid/platform/enforce.h"
 #include "paddle/fluid/pybind/eager.h"
 #include "paddle/fluid/pybind/eager_utils.h"
+#include "paddle/pten/api/lib/utils/allocator.h"
 #include "paddle/pten/api/lib/utils/storage.h"
 #include "paddle/pten/api/lib/utils/tensor_utils.h"
 #include "paddle/pten/common/data_type.h"
@@ -155,6 +157,12 @@ static inline PyObject* eager_api_numpy_to_tensor(
     v->eagertensor.set_name(egr::Controller::Instance().GenerateUniqueName());
     auto meta = egr::EagerUtils::autograd_meta(&(v->eagertensor));
     meta->SetStopGradient(stop_gradient);
+
+    // Created tensor will be leaf tensor
+    // So we append AccumulationNode to it.
+    auto accumulation_node = std::make_shared<egr::GradNodeAccumulation>();
+    meta->SetGradNode(accumulation_node);
+
     // TODO(jiabin): Shall we increase ref cnt here to make python ref cnt num
     // correctly?
   } else {

paddle/fluid/pybind/eager_method.cc

@@ -77,6 +77,17 @@ static PyObject* eager_tensor_method_numpy(EagerTensorObject* self,
         place, reinterpret_cast<void*>(
                    (reinterpret_cast<PyArrayObject_fields*>(array))->data),
         place, dense_tensor->data(), sizeof_dtype * numel);
+#if defined(PADDLE_WITH_CUDA)
+  } else if (self->eagertensor.is_cuda()) {
+    auto dense_tensor =
+        std::dynamic_pointer_cast<pten::DenseTensor>(self->eagertensor.impl());
+
+    paddle::platform::GpuMemcpySync(
+        (reinterpret_cast<PyArrayObject_fields*>(array))->data,
+        dense_tensor->data(),
+        pten::DataTypeSize(dense_tensor->dtype()) * dense_tensor->numel(),
+        cudaMemcpyDeviceToHost);
+#endif
   } else {
     PADDLE_THROW(platform::errors::InvalidArgument(
         "Tensor.numpy() only support cpu tensor."));

paddle/fluid/pybind/eager_properties.cc

@@ -65,6 +65,12 @@ PyObject* eager_tensor_properties_get_stop_gradient(EagerTensorObject* self,
   return ToPyObject(meta->StopGradient());
 }
 
+PyObject* eager_tensor_properties_get_grad(EagerTensorObject* self,
+                                           void* closure) {
+  auto meta = egr::EagerUtils::unsafe_autograd_meta(self->eagertensor);
+  return ToPyObject(meta->Grad());
+}
+
 int eager_tensor_properties_set_stop_gradient(EagerTensorObject* self,
                                               PyObject* value, void* closure) {
   auto meta = egr::EagerUtils::unsafe_autograd_meta(self->eagertensor);
@@ -116,6 +122,8 @@ PyObject* eager_tensor_properties_get_dtype(EagerTensorObject* self,
 }
 
 struct PyGetSetDef variable_properties[] = {
+    {"grad", (getter)eager_tensor_properties_get_grad, nullptr, nullptr,
+     nullptr},
     {"name", (getter)eager_tensor_properties_get_name,
      (setter)eager_tensor_properties_set_name, nullptr, nullptr},
     {"stop_gradient", (getter)eager_tensor_properties_get_stop_gradient,