mirror of https://github.com/alibaba/MNN.git
123 lines
4.4 KiB
C++
123 lines
4.4 KiB
C++
//
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// InterpBufExecution.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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#ifndef MNN_OPENCL_BUFFER_CLOSED
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#include "backend/opencl/execution/buffer/InterpBufExecution.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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InterpBufExecution::InterpBufExecution(const std::vector<Tensor *> &inputs, const MNN::Op *op, Backend *backend) : Execution(backend) {
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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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if (op->main_as_Interp()->resizeType() == 1) {
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mKernelName = "nearest_buf";
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mKernel = runtime->buildKernel("interp_buf", mKernelName, buildOptions);
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} else {
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mKernelName = "bilinear_buf";
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mKernel = runtime->buildKernel("interp_buf", mKernelName, buildOptions);
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}
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mMaxWorkGroupSize = static_cast<uint32_t>(runtime->getMaxWorkGroupSize(mKernel));
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}
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ErrorCode InterpBufExecution::onResize(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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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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mKernel.setArg(idx++, mGWS[0]);
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mKernel.setArg(idx++, mGWS[1]);
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mKernel.setArg(idx++, mGWS[2]);
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mKernel.setArg(idx++, openCLBuffer(input));
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mKernel.setArg(idx++, openCLBuffer(output));
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mKernel.setArg(idx++, mCordTransform[2]);
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mKernel.setArg(idx++, mCordTransform[0]);
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mKernel.setArg(idx++, mCordTransform[3]);
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mKernel.setArg(idx++, mCordTransform[1]);
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mKernel.setArg(idx++, static_cast<int32_t>(inputHeight));
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mKernel.setArg(idx++, static_cast<int32_t>(inputWidth));
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mKernel.setArg(idx++, static_cast<int32_t>(outputHeight));
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mKernel.setArg(idx++, static_cast<int32_t>(outputWidth));
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mKernel.setArg(idx++, static_cast<int32_t>(channelBlocks));
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mLWS = localWS3DDefault(mGWS, mMaxWorkGroupSize, runtime, mKernelName, mKernel).first;
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return NO_ERROR;
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}
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ErrorCode InterpBufExecution::onExecute(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
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#ifdef LOG_VERBOSE
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MNN_PRINT("Start InterpBufExecution onExecute... \n");
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#endif
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#ifdef ENABLE_OPENCL_TIME_PROFILER
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cl::Event event;
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run3DKernelDefault(mKernel, mGWS, mLWS,
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mOpenCLBackend->getOpenCLRuntime(), &event);
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int costTime = (int)mOpenCLBackend->getOpenCLRuntime()->getCostTime(&event);
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MNN_PRINT("kernel cost:%d us Interp\n",costTime);
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#else
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run3DKernelDefault(mKernel, mGWS, mLWS, mOpenCLBackend->getOpenCLRuntime());
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#endif
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#ifdef LOG_VERBOSE
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MNN_PRINT("end InterpBufExecution onExecute... \n");
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#endif
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return NO_ERROR;
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}
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class InterpBufCreator : public OpenCLBackend::Creator {
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public:
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virtual ~InterpBufCreator() = 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() != 1 && op->main_as_Interp()->resizeType() != 2) {
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MNN_PRINT("openCL buffer 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 InterpBufExecution(inputs, op, backend);
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}
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};
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OpenCLCreatorRegister<InterpBufCreator> __InterpBuf_op_(OpType_Interp, BUFFER);
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} // namespace OpenCL
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} // namespace MNN
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#endif /* MNN_OPENCL_BUFFER_CLOSED */
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