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