EVOLUTION-MANAGER

Edit File: bias_op_gpu.h

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,
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==============================================================================*/

#ifndef TENSORFLOW_CORE_KERNELS_BIAS_OP_GPU_H_
#define TENSORFLOW_CORE_KERNELS_BIAS_OP_GPU_H_

#define EIGEN_USE_GPU

#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/tensor_types.h"
#include "tensorflow/core/kernels/gpu_utils.h"
#include "tensorflow/core/util/tensor_format.h"

namespace tensorflow {

typedef Eigen::GpuDevice GPUDevice;

template <typename T>
struct BiasGPU {
  static void compute(const GPUDevice& d, const T* input, const T* bias,
                      T* output, int32 batch, int32 height, int32 width,
                      int32 depth, int32 channel, TensorFormat data_format);
};

template <typename T>
struct BiasGradGPU {
  static void compute(const GPUDevice& device, const T* output_backprop,
                      T* bias_backprop, int32 batch, int32 height, int32 width,
                      int32 depth, int32 channel, TensorFormat data_format);

static void DoRowReduction(OpKernelContext* context, T* output,
                             const T* input, int rows, int cols);

static void DoColReduction(OpKernelContext* context, T* output,
                             const T* input, int rows, int cols);
};

enum class BiasAddGradGPUMode {
  kInvalid = 0,
  kNative = 1,
  kReduction = 2,
};

// Describe the BiasGradGPU result from a perf experiment.
//
// Arguments:
// algorithm: returns the method to use for bias add grad.
// elapsed_time; returns the measured elapsed time in microseconds.
class BiasGradGPUProfileResult {
 public:
  bool is_valid() const {
    return (algorithm_ != BiasAddGradGPUMode::kInvalid &&
            elapsed_time_ != std::numeric_limits<float>::max());
  }
  BiasAddGradGPUMode algorithm() const { return algorithm_; }
  void set_algorithm(BiasAddGradGPUMode val) { algorithm_ = val; }
  uint64 elapsed_time() const { return elapsed_time_; }
  void set_elapsed_time(uint64 val) { elapsed_time_ = val; }

private:
  BiasAddGradGPUMode algorithm_ = BiasAddGradGPUMode::kInvalid;
  uint64 elapsed_time_ = std::numeric_limits<uint64>::max();
};

}  // namespace tensorflow

#endif  // TENSORFLOW_CORE_KERNELS_BIAS_OP_GPU_H_