EVOLUTION-MANAGER

Edit File: segment_reduction_ops.h

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
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http://www.apache.org/licenses/LICENSE-2.0

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distributed under the License is distributed on an "AS IS" BASIS,
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==============================================================================*/

#ifndef TENSORFLOW_CORE_KERNELS_SEGMENT_REDUCTION_OPS_H_
#define TENSORFLOW_CORE_KERNELS_SEGMENT_REDUCTION_OPS_H_

// This file requires the following include because it uses GpuAtomicMax:
// #include "tensorflow/core/util/gpu_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 GpuAtomicMax 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 {

#if GOOGLE_CUDA || TENSORFLOW_USE_ROCM
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 TensorShape& segment_ids_shape,
                  typename TTypes<Index>::ConstFlat segment_ids,
                  typename TTypes<T, 2>::ConstTensor data,
                  typename TTypes<T, 2>::Tensor output);
};

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

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

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

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

#endif  // GOOGLE_CUDA || TENSORFLOW_USE_ROCM

// 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  // TENSORFLOW_CORE_KERNELS_SEGMENT_REDUCTION_OPS_H_