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@ -75,15 +75,37 @@ class SeqExpandKernel : public framework::OpKernel<T> {
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T* out_data = out->mutable_data<T>(context.GetPlace());
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// copy data
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Place place = boost::get<Place>(context.GetPlace());
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auto place = context.GetPlace();
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size_t count = 0;
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for (size_t i = 0; i < scales.size(); ++i) {
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count = element_len * (x_lod[0][i + 1] - x_lod[0][i]);
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for (size_t j = 0; j < scales[i]; ++j) {
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memory::Copy(place, out_data, place, x_data, sizeof(T) * count);
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out_data += count;
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if (platform::is_cpu_place(place)) {
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auto& cpu_place = boost::get<platform::CPUPlace>(place);
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for (size_t i = 0; i < scales.size(); ++i) {
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count = element_len * (x_lod[0][i + 1] - x_lod[0][i]);
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for (size_t j = 0; j < scales[i]; ++j) {
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memory::Copy(cpu_place, out_data, cpu_place, x_data,
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sizeof(T) * count);
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out_data += count;
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}
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x_data += count;
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}
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x_data += count;
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} else {
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#ifdef PADDLE_WITH_CUDA
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auto& gpu_place = boost::get<platform::GPUPlace>(place);
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auto stream = reinterpret_cast<const platform::CUDADeviceContext&>(
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context.device_context())
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.stream();
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for (size_t i = 0; i < scales.size(); ++i) {
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count = element_len * (x_lod[0][i + 1] - x_lod[0][i]);
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for (size_t j = 0; j < scales[i]; ++j) {
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memory::Copy(gpu_place, out_data, gpu_place, x_data,
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sizeof(T) * count, stream);
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out_data += count;
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}
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x_data += count;
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}
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#else
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PADDLE_THROW("Paddle is not compiled with GPU");
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#endif
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}
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out->set_lod(out_lod);
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@ -113,7 +135,7 @@ class SeqExpandGradKernel : public framework::OpKernel<T> {
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Eigen::TensorMap<Eigen::Tensor<T, 1>> d_x_t(
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d_x_data, static_cast<int>((ele_count * element_len) / repeat));
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auto place = context.GetEigenDevice<Place>();
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d_x_t.device(place) = d_out_t.sum(Eigen::array<int, 1>({0}));
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d_x_t.device(place) = d_out_t.sum(Eigen::array<int, 1>({{0}}));
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d_out_data += (ele_count * element_len);
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d_x_data += ((ele_count * element_len) / repeat);
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}
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