MNN/source/backend/opencl/core/OpenCLRunningUtils.hpp

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2019-04-17 10:49:11 +08:00
//
// OpenCLRunningUtils.hpp
// MNN
//
// Created by MNN on 2019/01/31.
// Copyright © 2018, Alibaba Group Holding Limited
//
#ifndef OpenCLRunningUtils_hpp
#define OpenCLRunningUtils_hpp
#include <string>
#include <vector>
#include "Macro.h"
#include "TensorUtils.hpp"
#include "core/runtime/OpenCLRuntime.hpp"
#include "core/runtime/OpenCLWrapper.hpp"
namespace MNN {
namespace OpenCL {
inline std::vector<int> tensorShapeFormat(const Tensor *input) {
int iN = (0 != input->buffer().dim[0].extent) ? input->buffer().dim[0].extent : 1;
int iC = (0 != input->buffer().dim[1].extent) ? input->buffer().dim[1].extent : 1;
int iH = (0 != input->buffer().dim[2].extent) ? input->buffer().dim[2].extent : 1;
int iW = (0 != input->buffer().dim[3].extent) ? input->buffer().dim[3].extent : 1;
if (TensorUtils::getDescribe(input)->dimensionFormat == MNN::MNN_DATA_FORMAT_NHWC) {
iN = (0 < input->buffer().dim[0].extent) ? input->buffer().dim[0].extent : 1;
iH = (0 < input->buffer().dim[1].extent) ? input->buffer().dim[1].extent : 1;
iW = (0 < input->buffer().dim[2].extent) ? input->buffer().dim[2].extent : 1;
iC = (0 < input->buffer().dim[3].extent) ? input->buffer().dim[3].extent : 1;
}
if (input->buffer().dimensions == 2) {
iN = input->buffer().dim[0].extent;
iH = 1;
iW = 1;
iC = input->buffer().dim[1].extent;
}
if (input->buffer().dimensions == 1) {
iN = 1;
iH = 1;
iW = 1;
iC = input->buffer().dim[0].extent;
}
#ifdef LOG_VERBOSE
MNN_PRINT("tensorShapeFormat : [%d, %d, %d, %d] \n", iN, iH, iW, iC);
#endif
std::vector<int> shape_vec{iN, iH, iW, iC};
return shape_vec;
}
enum OpenCLBufferFormat {
CONV2D_FILTER = 0,
NHWC_BUFFER = 1,
ARGUMENT = 2,
DW_CONV2D_FILTER = 3,
NCHW_BUFFER = 4,
NHWC4_BUFFER = 5,
};
template <typename T, typename Dim>
inline void IOHW2OIHW(const T *src, T *dst, Dim O, Dim I, Dim H, Dim W) {
for (Dim i = 0; i < I; i++) {
for (Dim o = 0; o < O; o++) {
for (Dim h = 0; h < H; h++) {
for (Dim w = 0; w < W; w++) {
dst[o * I * H * W + i * H * W + h * W + w] = src[i * O * H * W + o * H * W + h * W + w];
}
}
}
}
};
inline cl::Buffer &openCLBuffer(const Tensor *tensor) {
return (*(cl::Buffer *)(tensor->deviceId()));
}
inline cl::Image &openCLImage(const Tensor *tensor) {
return (*(cl::Image *)(tensor->deviceId()));
}
void getImageShape(const std::vector<int> &shape, /* NHWC */
const OpenCLBufferFormat type, std::vector<size_t> *imageShape);
std::vector<uint32_t> turnLocalSize(cl::Kernel *kernel, std::vector<uint32_t> &gws, OpenCLRuntime *runtime);
void run3DKernelDefault(const ::cl::Kernel &kernel, const std::vector<uint32_t> &gws, const std::vector<uint32_t> &lws,
OpenCLRuntime *runtime);
void run2DKernelDefault(const ::cl::Kernel &kernel, const uint32_t *gws, const std::vector<uint32_t> &lws,
OpenCLRuntime *runtime);
void runKernel2D(const ::cl::Kernel &kernel, const std::vector<uint32_t> &gws, const std::vector<uint32_t> &lws,
OpenCLRuntime *runtime);
void runTurnKernelLWS2D(const ::cl::Kernel &kernel, const std::vector<uint32_t> &gws, const std::vector<uint32_t> &lws,
OpenCLRuntime *runtime);
std::vector<uint32_t> localWS3DDefault(const std::vector<uint32_t> &gws, const uint32_t maxWorkGroupSize,
OpenCLRuntime *runtime);
void copyBufferToImage(OpenCLRuntime *runtime, const cl::Buffer &buffer, const cl::Image &image, int w, int h);
} // namespace OpenCL
} // namespace MNN
#endif /* OpenCLRunningUtils_hpp */