MNN/source/backend/opencl/execution/image/Interp3DExecution.cpp

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//
// InterpExecution.cpp
// MNN
//
// Created by MNN on 2019/02/28.
// Copyright © 2018, Alibaba Group Holding Limited
//
#include "backend/opencl/execution/image/Interp3DExecution.hpp"
#include "core/TensorUtils.hpp"
namespace MNN {
namespace OpenCL {
Interp3DExecution::Interp3DExecution(const std::vector<Tensor *> &inputs, const MNN::Op *op, Backend *backend)
: Execution(backend) {
mOpenCLBackend = static_cast<OpenCLBackend *>(backend);
auto runtime = mOpenCLBackend->getOpenCLRuntime();
auto interp3DParam = op->main_as_Interp3D();
mCordTransform[0] = interp3DParam->widthScale();
mCordTransform[1] = interp3DParam->widthOffset();
mCordTransform[2] = interp3DParam->heightScale();
mCordTransform[3] = interp3DParam->heightOffset();
mCordTransform[4] = interp3DParam->depthScale();
mCordTransform[5] = interp3DParam->depthOffset();
std::set<std::string> buildOptions;
std::string kernelName = "interp3D";
if (op->main_as_Interp3D()->resizeType() == 1) {
mKernel = runtime->buildKernel("nearest", kernelName, buildOptions);
} else {
MNN_ERROR("Resize types other than nearest are not supported in Interp3D opencl! Using nearest instead\n");
mKernel = runtime->buildKernel("nearest", kernelName, buildOptions);
}
mMaxWorkGroupSize = static_cast<uint32_t>(runtime->getMaxWorkGroupSize(mKernel));
}
ErrorCode Interp3DExecution::onResize(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
Tensor *input = inputs[0];
Tensor *output = outputs[0];
auto runtime = ((OpenCLBackend *)backend())->getOpenCLRuntime();
std::vector<int> inputImageShape = tensorShapeFormat(input); // {C/4 * H * W, N * D} for 5-D Tensor
std::vector<int> outputImageShape = tensorShapeFormat(output);
auto inputShape = input->shape();
auto outputShape = output->shape();
const int inputBatch = inputShape[0];
const int inputChannels = inputShape[1];
const int inputDepth = inputShape[2];
const int inputHeight = inputShape[3];
const int inputWidth = inputShape[4];
const int channelBlocks = UP_DIV(inputChannels, 4);
const int outputDepth = outputShape[2];
const int outputHeight = outputShape[3];
const int outputWidth = outputShape[4];
mGWS = {static_cast<uint32_t>(channelBlocks),
static_cast<uint32_t>(outputHeight * outputWidth),
static_cast<uint32_t>(outputDepth * inputBatch)};
MNN_ASSERT(outputDepth > 0 && outputHeight > 0 && outputWidth > 0);
uint32_t idx = 0;
mKernel.setArg(idx++, mGWS[0]);
mKernel.setArg(idx++, mGWS[1]);
mKernel.setArg(idx++, mGWS[2]);
mKernel.setArg(idx++, openCLImage(input));
mKernel.setArg(idx++, openCLImage(output));
mKernel.setArg(idx++, mCordTransform[4]);
mKernel.setArg(idx++, mCordTransform[2]);
mKernel.setArg(idx++, mCordTransform[0]);
mKernel.setArg(idx++, mCordTransform[5]);
mKernel.setArg(idx++, mCordTransform[3]);
mKernel.setArg(idx++, mCordTransform[1]);
mKernel.setArg(idx++, static_cast<int32_t>(inputDepth));
mKernel.setArg(idx++, static_cast<int32_t>(inputHeight));
mKernel.setArg(idx++, static_cast<int32_t>(inputWidth));
mKernel.setArg(idx++, static_cast<int32_t>(outputDepth));
mKernel.setArg(idx++, static_cast<int32_t>(outputHeight));
std::string name = "interp3D";
mLWS = localWS3DDefault(mGWS, mMaxWorkGroupSize, runtime, name, mKernel).first;
return NO_ERROR;
}
ErrorCode Interp3DExecution::onExecute(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
#ifdef LOG_VERBOSE
MNN_PRINT("Start Interp3DExecution onExecute... \n");
#endif
#ifdef ENABLE_OPENCL_TIME_PROFILER
cl::Event event;
run3DKernelDefault(mKernel, mGWS, mLWS,
mOpenCLBackend->getOpenCLRuntime(), &event);
int costTime = (int)mOpenCLBackend->getOpenCLRuntime()->getCostTime(&event);
MNN_PRINT("kernel cost:%d us Interp3D\n",costTime);
#else
run3DKernelDefault(mKernel, mGWS, mLWS, mOpenCLBackend->getOpenCLRuntime());
#endif
#ifdef LOG_VERBOSE
MNN_PRINT("end Interp3DExecution onExecute... \n");
#endif
return NO_ERROR;
}
OpenCLCreatorRegister<TypedCreator<Interp3DExecution>> __Interp3D_op_(OpType_Interp3D, IMAGE);
} // namespace OpenCL
} // namespace MNN