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#ifndef TEST_SIMPLE_CONVOLUTION_SIMPLE_CONVOLUTION_H_
#define TEST_SIMPLE_CONVOLUTION_SIMPLE_CONVOLUTION_H_

#include <map>
#include <string>
#include <vector>

#include "ctrl/test_kernel.h"

// Class implements simple_convolution kernel parameters
class simple_convolution : public TestKernel {
 public:
  // Kernel buffers IDs
  enum { INPUT_BUF_ID, LOCAL_BUF_ID, MASK_BUF_ID, KERNARG_BUF_ID, REFOUT_BUF_ID };

  // Constructor
  simple_convolution();

  // Initialize method
  void Init();

  // Return compute grid size
  uint32_t GetGridSize() const { return width_ * height_; }

  // Print output
  void PrintOutput(const void* ptr) const;

  // Return name
  std::string Name() const { return std::string("simple_convolution"); }

 private:
  // Local kernel arguments declaration
  struct kernel_args_t {
    void* arg1;
    void* arg2;
    void* arg3;
    uint32_t arg4;
    uint32_t arg41;
    uint32_t arg5;
    uint32_t arg51;
  };

  // Reference CPU implementation of Simple Convolution
  // @param output Output matrix after performing convolution
  // @param input  Input  matrix on which convolution is to be performed
  // @param mask   mask matrix using which convolution was to be performed
  // @param input_dimensions dimensions of the input matrix
  // @param mask_dimensions  dimensions of the mask matrix
  // @return bool true on success and false on failure
  bool ReferenceImplementation(uint32_t* output, const uint32_t* input, const float* mask,
                               const uint32_t width, const uint32_t height,
                               const uint32_t maskWidth, const uint32_t maskHeight);

  // Width of the Input array
  uint32_t width_;

  // Height of the Input array
  uint32_t height_;

  // Mask dimensions
  uint32_t mask_width_;

  // Mask dimensions
  uint32_t mask_height_;

  // Input data
  std::vector<uint32_t> input_data_;
  static std::vector<uint32_t> get_input_data(size_t width, size_t height);
};

#endif  // TEST_SIMPLE_CONVOLUTION_SIMPLE_CONVOLUTION_H_