Files
rocm-systems/test/simple_convolution/simple_convolution.h
T
Evgeny f6f857f6f4 licensing annotation
Change-Id: Icdd79e25e7ba30e777f1024697f87d583f380a62
2018-08-19 04:18:55 -05:00

95 rader
3.2 KiB
C++

/******************************************************************************
Copyright (c) 2018 Advanced Micro Devices, Inc. All rights reserved.
Permission is hereby granted, free of charge, to any person obtaining a copy
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in the Software without restriction, including without limitation the rights
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The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.
*******************************************************************************/
#ifndef TEST_SIMPLE_CONVOLUTION_SIMPLE_CONVOLUTION_H_
#define TEST_SIMPLE_CONVOLUTION_SIMPLE_CONVOLUTION_H_
#include <map>
#include <vector>
#include "ctrl/test_kernel.h"
// Class implements SimpleConvolution kernel parameters
class SimpleConvolution : public TestKernel {
public:
// Kernel buffers IDs
enum { INPUT_BUF_ID, LOCAL_BUF_ID, MASK_BUF_ID, KERNARG_BUF_ID, REFOUT_BUF_ID };
// Constructor
SimpleConvolution();
// 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("SimpleConvolution"); }
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_;
// Randomize input data
unsigned randomize_seed_;
// Input data
static const uint32_t input_data_[];
};
#endif // TEST_SIMPLE_CONVOLUTION_SIMPLE_CONVOLUTION_H_