mirror of https://github.com/alibaba/MNN.git
107 lines
4.3 KiB
C++
107 lines
4.3 KiB
C++
//
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// InterpExecution.cpp
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// MNN
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//
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// Created by MNN on 2019/02/28.
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// Copyright © 2018, Alibaba Group Holding Limited
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//
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#include "backend/opencl/execution/image/InterpExecution.hpp"
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#include "core/TensorUtils.hpp"
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namespace MNN {
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namespace OpenCL {
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InterpExecution::InterpExecution(const std::vector<Tensor *> &inputs, const MNN::Op *op, Backend *backend)
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: CommonExecution(backend, op) {
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mUnits.resize(1);
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auto &unit = mUnits[0];
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mOpenCLBackend = static_cast<OpenCLBackend *>(backend);
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auto runtime = mOpenCLBackend->getOpenCLRuntime();
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auto interpParam = op->main_as_Interp();
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mCordTransform[0] = interpParam->widthScale();
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mCordTransform[1] = interpParam->widthOffset();
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mCordTransform[2] = interpParam->heightScale();
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mCordTransform[3] = interpParam->heightOffset();
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std::set<std::string> buildOptions;
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std::string kernelName = "interp";
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if (op->main_as_Interp()->resizeType() == 1) {
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unit.kernel = runtime->buildKernel("nearest", kernelName, buildOptions, mOpenCLBackend->getPrecision());
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}else if (op->main_as_Interp()->resizeType() == 4) {
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buildOptions.emplace("-DUSE_ROUND");
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unit.kernel = runtime->buildKernel("nearest", kernelName, buildOptions, mOpenCLBackend->getPrecision());
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}else {
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unit.kernel = runtime->buildKernel("interp", kernelName, buildOptions, mOpenCLBackend->getPrecision());
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}
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mMaxWorkGroupSize = static_cast<uint32_t>(runtime->getMaxWorkGroupSize(unit.kernel ));
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}
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ErrorCode InterpExecution::onEncode(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
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Tensor *input = inputs[0];
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Tensor *output = outputs[0];
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auto runtime = ((OpenCLBackend *)backend())->getOpenCLRuntime();
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auto &unit = mUnits[0];
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std::vector<int> inputShape = tensorShapeFormat(input);
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std::vector<int> outputShape = tensorShapeFormat(output);
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const int inputBatch = input->batch();
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const int inputHeight = input->height();
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const int inputWidth = input->width();
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const int inputChannels = input->channel();
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const int channelBlocks = UP_DIV(inputChannels, 4);
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const int outputHeight = output->height();
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const int outputWidth = output->width();
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mGWS = {static_cast<uint32_t>(channelBlocks),
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static_cast<uint32_t>(outputWidth),
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static_cast<uint32_t>(outputHeight * inputBatch)};
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MNN_ASSERT(outputHeight > 0 && outputWidth > 0);
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uint32_t idx = 0;
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cl_int ret = CL_SUCCESS;
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ret |= unit.kernel->get().setArg(idx++, mGWS[0]);
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ret |= unit.kernel->get().setArg(idx++, mGWS[1]);
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ret |= unit.kernel->get().setArg(idx++, mGWS[2]);
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ret |= unit.kernel->get().setArg(idx++, openCLImage(input));
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ret |= unit.kernel->get().setArg(idx++, openCLImage(output));
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ret |= unit.kernel->get().setArg(idx++, mCordTransform[2]);
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ret |= unit.kernel->get().setArg(idx++, mCordTransform[0]);
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ret |= unit.kernel->get().setArg(idx++, mCordTransform[3]);
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ret |= unit.kernel->get().setArg(idx++, mCordTransform[1]);
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ret |= unit.kernel->get().setArg(idx++, static_cast<int32_t>(inputHeight));
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ret |= unit.kernel->get().setArg(idx++, static_cast<int32_t>(inputWidth));
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ret |= unit.kernel->get().setArg(idx++, static_cast<int32_t>(outputHeight));
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MNN_CHECK_CL_SUCCESS(ret, "setArg InterpExecution");
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std::string name = "interp";
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mLWS = localWS3DDefault(mGWS, mMaxWorkGroupSize, mOpenCLBackend->getOpenCLRuntime(), name, unit.kernel, mOpenCLBackend->getCLTuneLevel()).first;
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mOpenCLBackend->recordKernel3d(unit.kernel, mGWS, mLWS);
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unit.globalWorkSize = {mGWS[0], mGWS[1], mGWS[2]};
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unit.localWorkSize = {mLWS[0], mLWS[1], mLWS[2]};
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return NO_ERROR;
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}
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class InterpCreator : public OpenCLBackend::Creator {
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public:
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virtual ~InterpCreator() = default;
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virtual Execution *onCreate(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs, const MNN::Op *op, Backend *backend) const override {
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if(op->main_as_Interp()->resizeType() == 3) {
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MNN_PRINT("openCL not support interp type:%d, fallback to cpu\n", op->main_as_Interp()->resizeType());
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return nullptr;
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}
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return new InterpExecution(inputs, op, backend);
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}
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};
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REGISTER_OPENCL_OP_CREATOR(InterpCreator, OpType_Interp, IMAGE);
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} // namespace OpenCL
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} // namespace MNN
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