Refine PyBind

paddle/fluid/pybind/tensor_py.h

@@ -14,6 +14,7 @@ limitations under the License. */
 
 #pragma once
 #include <Python.h>
+#include <cmake-build-release/third_party/pybind/src/extern_pybind/include/pybind11/common.h>
 #include <string>
 #include <tuple>
 #include <vector>
@@ -57,7 +58,8 @@ struct CastToPyBufferImpl<true, I, ARGS...> {
         prod *= dims_outside[i - 1];
       }
       framework::Tensor dst_tensor;
-      if (paddle::platform::is_gpu_place(tensor.place())) {
+      bool is_gpu = paddle::platform::is_gpu_place(tensor.place());
+      if (is_gpu) {
 #ifdef PADDLE_WITH_CUDA
         auto *src_ptr = static_cast<const void *>(tensor.data<CUR_TYPE>());
         auto *dst_ptr = static_cast<void *>(dst_tensor.mutable_data<CUR_TYPE>(
@@ -74,16 +76,44 @@ struct CastToPyBufferImpl<true, I, ARGS...> {
         dst_tensor = tensor;
       }
 
-      if (std::type_index(typeid(CUR_TYPE)) ==
-          std::type_index(typeid(platform::float16))) {
-        return pybind11::buffer_info(
-            dst_tensor.data<CUR_TYPE>(), sizeof(CUR_TYPE),
-            "e", /* np.dtype('e') == np.float16 */
-            (size_t)framework::arity(dst_tensor.dims()), dims_outside, strides);
+      std::string dtype = std::type_index(typeid(CUR_TYPE)) ==
+                                  std::type_index(typeid(platform::float16))
+                              ? std::string("e")  // np.dtype('e') == np.float16
+                              : pybind11::format_descriptor<CUR_TYPE>::format();
+
+      if (is_gpu) {
+        // manually construct a py_buffer if is_gpu since gpu data is copied
+        // into CPU.
+        // TODO(yy): Is these following code memleak?
+        Py_buffer *py_buffer =
+            reinterpret_cast<Py_buffer *>(malloc(sizeof(Py_buffer)));
+        py_buffer->format = strdup(dtype.c_str());
+        py_buffer->itemsize = sizeof(CUR_TYPE);
+        py_buffer->ndim = framework::arity(dst_tensor.dims());
+        py_buffer->len = tensor.numel();
+        py_buffer->strides = reinterpret_cast<Py_ssize_t *>(
+            malloc(sizeof(Py_ssize_t) * strides.size()));
+        for (size_t i = 0; i < strides.size(); ++i) {
+          py_buffer->strides[i] = strides[i];
+        }
+
+        py_buffer->shape = reinterpret_cast<Py_ssize_t *>(
+            malloc(sizeof(Py_ssize_t) * tensor.dims().size()));
+        for (size_t i = 0; i < tensor.dims().size(); ++i) {
+          py_buffer->shape[i] = tensor.dims()[i];
+        }
+
+        py_buffer->readonly = false;
+        py_buffer->suboffsets = nullptr;
+        py_buffer->obj = nullptr;
+        py_buffer->buf =
+            malloc(static_cast<size_t>(py_buffer->len * py_buffer->itemsize));
+        memcpy(py_buffer->buf, dst_tensor.data<CUR_TYPE>(),
+               static_cast<size_t>(py_buffer->len * py_buffer->itemsize));
+        return pybind11::buffer_info(py_buffer, true);
       } else {
         return pybind11::buffer_info(
-            dst_tensor.data<CUR_TYPE>(), sizeof(CUR_TYPE),
-            pybind11::format_descriptor<CUR_TYPE>::format(),
+            dst_tensor.data<CUR_TYPE>(), sizeof(CUR_TYPE), dtype,
             (size_t)framework::arity(dst_tensor.dims()), dims_outside, strides);
       }
     } else {

python/paddle/fluid/tests/unittests/test_conv2d_op.py

@@ -289,9 +289,9 @@ class TestFP16CUDNNWithGroup(TestWithGroup):
                 self.check_output_with_place(place, atol=2e-2)
 
 
-# class TestCUDNNWith1x1(TestWith1x1):
-#     def init_kernel_type(self):
-#         self.use_cudnn = True
+class TestCUDNNWith1x1(TestWith1x1):
+    def init_kernel_type(self):
+        self.use_cudnn = True
 
 
 class TestFP16CUDNNWith1x1(TestWith1x1):