| /* Copyright 2019 The TensorFlow Authors. All Rights Reserved. |
| |
| Licensed under the Apache License, Version 2.0 (the "License"); |
| you may not use this file except in compliance with the License. |
| You may obtain a copy of the License at |
| |
| http://www.apache.org/licenses/LICENSE-2.0 |
| |
| Unless required by applicable law or agreed to in writing, software |
| distributed under the License is distributed on an "AS IS" BASIS, |
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| See the License for the specific language governing permissions and |
| limitations under the License. |
| ==============================================================================*/ |
| |
| #ifndef TENSORFLOW_CORE_KERNELS_CONCAT_LIB_GPU_H_ |
| #define TENSORFLOW_CORE_KERNELS_CONCAT_LIB_GPU_H_ |
| |
| #define EIGEN_USE_THREADS |
| #define EIGEN_USE_GPU |
| |
| #include <memory> |
| #include <vector> |
| |
| #include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor" |
| #include "tensorflow/core/framework/register_types.h" |
| #include "tensorflow/core/kernels/concat_lib.h" |
| #include "tensorflow/core/kernels/gpu_device_array_gpu.h" |
| |
| namespace tensorflow { |
| |
| template <typename T, typename IntType> |
| void ConcatGPUSlice( |
| const Eigen::GpuDevice& gpu_device, |
| const std::vector<std::unique_ptr<typename TTypes<T, 2>::ConstMatrix>>& |
| inputs_flat, |
| typename TTypes<T, 2>::Matrix* output); |
| |
| template <typename T, typename IntType> |
| void ConcatGPUImpl(const Eigen::GpuDevice& d, |
| const GpuDeviceArrayStruct<const T*>& input_ptrs, |
| const GpuDeviceArrayStruct<IntType>& ptr_offsets, |
| bool same_size, int slice_size, |
| typename TTypes<T, 2>::Matrix* output); |
| |
| // Explicit instantiations in concat_lib_gpu_impl.cu.cc. |
| #define REGISTER(T) \ |
| extern template void ConcatGPUSlice<T, int32>( \ |
| const Eigen::GpuDevice& gpu_device, \ |
| const std::vector<std::unique_ptr<typename TTypes<T, 2>::ConstMatrix>>& \ |
| inputs_flat, \ |
| typename TTypes<T, 2>::Matrix* output); \ |
| extern template void ConcatGPUSlice<T, int64>( \ |
| const Eigen::GpuDevice& gpu_device, \ |
| const std::vector<std::unique_ptr<typename TTypes<T, 2>::ConstMatrix>>& \ |
| inputs_flat, \ |
| typename TTypes<T, 2>::Matrix* output); \ |
| extern template void ConcatGPUImpl<T, int32>( \ |
| const Eigen::GpuDevice& d, \ |
| const GpuDeviceArrayStruct<const T*>& input_ptrs, \ |
| const GpuDeviceArrayStruct<int32>& ptr_offsets, bool fixed_size, \ |
| int split_size, typename TTypes<T, 2>::Matrix* output); \ |
| extern template void ConcatGPUImpl<T, int64>( \ |
| const Eigen::GpuDevice& d, \ |
| const GpuDeviceArrayStruct<const T*>& input_ptrs, \ |
| const GpuDeviceArrayStruct<int64>& ptr_offsets, bool fixed_size, \ |
| int split_size, typename TTypes<T, 2>::Matrix* output); |
| |
| TF_CALL_GPU_NUMBER_TYPES(REGISTER); |
| TF_CALL_complex64(REGISTER); |
| TF_CALL_complex128(REGISTER); |
| TF_CALL_int32(REGISTER); // Needed for TensorLists. |
| TF_CALL_int64(REGISTER); |
| TF_CALL_int16(REGISTER); |
| TF_CALL_bfloat16(REGISTER); |
| TF_CALL_bool(REGISTER); |
| TF_CALL_uint8(REGISTER); |
| #undef REGISTER |
| |
| } // namespace tensorflow |
| |
| #endif // TENSORFLOW_CORE_KERNELS_CONCAT_LIB_GPU_H_ |