提交 333fd152 编写于 作者: Q Qiao Longfei

add gpu test for mrege add

上级 ab3e36da
......@@ -323,7 +323,7 @@ struct MergeAdd<platform::CUDADeviceContext, T> {
{static_cast<int64_t>(merge_rows.size()), input_width}),
context.GetPlace());
math::SetConstant<platform::CPUDeviceContext, T> constant_functor;
math::SetConstant<platform::CUDADeviceContext, T> constant_functor;
constant_functor(context, out.mutable_value(), 0.0);
auto* out_data = out.mutable_value()->data<T>();
......
......@@ -241,3 +241,69 @@ TEST(selected_rows_functor, gpu_add_to) {
// row9: 2.0 + 3.0
EXPECT_EQ(tensor1_cpu_data[9 * row_numel + 6], 5.0);
}
TEST(selected_rows_functor, cpu_merge_add) {
paddle::platform::CUDAPlace gpu_place(0);
paddle::platform::CPUPlace cpu_place;
paddle::platform::CUDADeviceContext& ctx =
*reinterpret_cast<paddle::platform::CUDADeviceContext*>(
paddle::platform::DeviceContextPool::Instance().Get(gpu_place));
paddle::operators::math::SetConstant<paddle::platform::CUDADeviceContext,
float>
functor;
int64_t height = 10;
int64_t row_numel = 8;
std::vector<int64_t> rows1{5, 2, 5, 3, 5};
std::unique_ptr<paddle::framework::SelectedRows> selected_rows1{
new paddle::framework::SelectedRows(rows1, height)};
auto* in1_value = selected_rows1->mutable_value();
in1_value->mutable_data<float>(
paddle::framework::make_ddim(
{static_cast<int64_t>(rows1.size()), row_numel}),
cpu_place);
set_const(ctx, in1_value, 1.0);
std::vector<int64_t> rows2{2, 5, 3, 5, 3};
std::unique_ptr<paddle::framework::SelectedRows> selected_rows2{
new paddle::framework::SelectedRows(rows2, height)};
auto* in2_value = selected_rows2->mutable_value();
in2_value->mutable_data<float>(
paddle::framework::make_ddim(
{static_cast<int64_t>(rows2.size()), row_numel}),
cpu_place);
set_const(ctx, in2_value, 1.0);
std::unique_ptr<paddle::framework::SelectedRows> output{
new paddle::framework::SelectedRows()};
output->set_height(height);
paddle::operators::math::scatter::MergeAdd<
paddle::platform::CUDADeviceContext, float>
merge_add_functor;
std::vector<const paddle::framework::SelectedRows*> inputs;
inputs.push_back(selected_rows1.get());
inputs.push_back(selected_rows2.get());
merge_add_functor(ctx, inputs, output.get());
paddle::framework::Tensor output_cpu;
paddle::framework::TensorCopy(*output, cpu_place, ctx, &output_cpu);
ctx.Wait();
EXPECT_EQ(output->height(), height);
EXPECT_EQ(output->value().dims(),
paddle::framework::make_ddim({3, row_numel}));
std::vector<int64_t> ret_rows{2, 3, 5};
EXPECT_EQ(output->rows(), ret_rows);
auto* out_data = output_cpu.data<float>();
for (size_t i = 0; i < ret_rows.size(); ++i) {
for (size_t j = 0; j < row_numel; ++j) {
EXPECT_EQ(out_data[i * row_numel + j], ret_rows[i]);
std::cout << out_data[i * row_numel + j] << " ";
}
std::cout << "\n";
}
}
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