/* Copyright 2016 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 THIRD_PARTY_TENSORFLOW_CORE_KERNELS_SEGMENT_REDUCTION_OPS_H_
#define THIRD_PARTY_TENSORFLOW_CORE_KERNELS_SEGMENT_REDUCTION_OPS_H_


// This file requires the following include because it uses CudaAtomicMax:
// #include "tensorflow/core/util/cuda_kernel_helper.h"

// Unfortunately we can't add the #include, since it breaks compilation for
// non-GPU targets. This only breaks in clang, because it's more strict for
// template code and CudaAtomicMax is used in template context.

// This file requires the following include because it uses CudaAtomicMax:
// #include "tensorflow/core/util/cuda_kernel_helper.h"

// Unfortunately we can't add the #include, since it breaks compilation for
// non-GPU targets. This only breaks in clang, because it's more strict for
// template code and CudaAtomicMax is used in template context.

#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/tensor_types.h"

namespace tensorflow {

class OpKernelContext;

namespace functor {

#ifdef GOOGLE_CUDA
typedef Eigen::GpuDevice GPUDevice;
// Functor for SegmentSumGPUOp.
// output_rows: the number of output segments (unique segment ids in
//                'segment_ids').
// segment_ids_shape: shape of 'segment_ids' tensor.
// segment_ids: unsorted map from input to output segment ids at which to
//                perform segment sum operation.
// data_size: size of input data tensor.
// data: input data tensor.
// output: output reshaped to {output_rows, output.size/output_rows}
template <typename T, typename Index>
struct SegmentSumFunctor {
  void operator()(OpKernelContext* ctx, const GPUDevice& d,
                  const Index output_rows, const TensorShape& segment_ids_shape,
                  typename TTypes<Index>::ConstFlat segment_ids,
                  const Index data_size, const T* data,
                  typename TTypes<T, 2>::Tensor output);
};

#endif

template <typename Device, typename T, typename Index, typename InitialValueF,
          typename ReductionF>
struct UnsortedSegmentFunctor {
  void operator()(OpKernelContext* ctx, const Index num_segments,
                  const TensorShape& segment_ids_shape,
                  typename TTypes<Index>::ConstFlat segment_ids,
                  const Index data_size, const T* data,
                  typename TTypes<T, 2>::Tensor output);
};

#ifdef GOOGLE_CUDA
// reduction functors for the gpu
template <typename T>
struct SumOpGpu {
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void operator()(T* dest,
                                                        const T& value) {
    CudaAtomicAdd(dest, value);
  }
};

template <typename T>
struct ProdOpGpu {
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void operator()(T* dest,
                                                        const T& value) {
    CudaAtomicMul(dest, value);
  }
};

template <typename T>
struct MaxOpGpu {
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void operator()(T* dest,
                                                        const T& value) {
    CudaAtomicMax(dest, value);
  }
};

template <typename T>
struct MinOpGpu {
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void operator()(T* dest,
                                                        const T& value) {
    CudaAtomicMin(dest, value);
  }
};

#endif  // GOOGLE_CUDA

// initial value functors
template <typename T>
struct Zero {
  EIGEN_STRONG_INLINE T operator()() const { return T(0); }
};

template <typename T>
struct One {
  EIGEN_STRONG_INLINE T operator()() const { return T(1); }
};

template <typename T>
struct Lowest {
  EIGEN_STRONG_INLINE T operator()() const {
    return Eigen::NumTraits<T>::lowest();
  }
};

template <typename T>
struct Highest {
  EIGEN_STRONG_INLINE T operator()() const {
    return Eigen::NumTraits<T>::highest();
  }
};

}  // namespace functor
}  // namespace tensorflow

#endif  // THIRD_PARTY_TENSORFLOW_CORE_KERNELS_SEGMENT_REDUCTION_OPS_H_
