MNN/source/backend/opencl/execution/buffer/InterpBufExecution.cpp

134 lines
5.0 KiB
C++

//
// InterpBufExecution.cpp
// MNN
//
// Created by MNN on 2019/02/28.
// Copyright © 2018, Alibaba Group Holding Limited
//
#ifndef MNN_OPENCL_BUFFER_CLOSED
#include "backend/opencl/execution/buffer/InterpBufExecution.hpp"
#include "core/TensorUtils.hpp"
namespace MNN {
namespace OpenCL {
InterpBufExecution::InterpBufExecution(const std::vector<Tensor *> &inputs, const MNN::Op *op, Backend *backend) : Execution(backend) {
mOpenCLBackend = static_cast<OpenCLBackend *>(backend);
auto runtime = mOpenCLBackend->getOpenCLRuntime();
auto interpParam = op->main_as_Interp();
mCordTransform[0] = interpParam->widthScale();
mCordTransform[1] = interpParam->widthOffset();
mCordTransform[2] = interpParam->heightScale();
mCordTransform[3] = interpParam->heightOffset();
std::set<std::string> buildOptions;
if (op->main_as_Interp()->resizeType() == 1) {
mKernelName = "nearest_buf";
mKernel = runtime->buildKernel("interp_buf", mKernelName, buildOptions);
} else if(op->main_as_Interp()->resizeType() == 4) {
mKernelName = "nearest_buf";
buildOptions.emplace("-DUSE_ROUND");
mKernel = runtime->buildKernel("interp_buf", mKernelName, buildOptions);
}else {
mKernelName = "bilinear_buf";
mKernel = runtime->buildKernel("interp_buf", mKernelName, buildOptions);
}
mMaxWorkGroupSize = static_cast<uint32_t>(runtime->getMaxWorkGroupSize(mKernel));
}
ErrorCode InterpBufExecution::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> inputShape = tensorShapeFormat(input);
std::vector<int> outputShape = tensorShapeFormat(output);
const int inputBatch = input->batch();
const int inputHeight = input->height();
const int inputWidth = input->width();
const int inputChannels = input->channel();
const int channelBlocks = UP_DIV(inputChannels, 4);
const int outputHeight = output->height();
const int outputWidth = output->width();
mGWS = {static_cast<uint32_t>(channelBlocks),
static_cast<uint32_t>(outputWidth),
static_cast<uint32_t>(outputHeight * inputBatch)};
MNN_ASSERT(outputHeight > 0 && outputWidth > 0);
uint32_t idx = 0;
cl_int ret = CL_SUCCESS;
ret |= mKernel.setArg(idx++, mGWS[0]);
ret |= mKernel.setArg(idx++, mGWS[1]);
ret |= mKernel.setArg(idx++, mGWS[2]);
ret |= mKernel.setArg(idx++, openCLBuffer(input));
ret |= mKernel.setArg(idx++, openCLBuffer(output));
ret |= mKernel.setArg(idx++, mCordTransform[2]);
ret |= mKernel.setArg(idx++, mCordTransform[0]);
ret |= mKernel.setArg(idx++, mCordTransform[3]);
ret |= mKernel.setArg(idx++, mCordTransform[1]);
ret |= mKernel.setArg(idx++, static_cast<int32_t>(inputHeight));
ret |= mKernel.setArg(idx++, static_cast<int32_t>(inputWidth));
ret |= mKernel.setArg(idx++, static_cast<int32_t>(outputHeight));
ret |= mKernel.setArg(idx++, static_cast<int32_t>(outputWidth));
ret |= mKernel.setArg(idx++, static_cast<int32_t>(channelBlocks));
MNN_CHECK_CL_SUCCESS(ret, "setArg InterpBufExecution");
mLWS = localWS3DDefault(mGWS, mMaxWorkGroupSize, runtime, mKernelName, mKernel).first;
return NO_ERROR;
}
ErrorCode InterpBufExecution::onExecute(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
#ifdef LOG_VERBOSE
MNN_PRINT("Start InterpBufExecution onExecute... \n");
#endif
#ifdef ENABLE_OPENCL_TIME_PROFILER
cl::Event event;
run3DKernelDefault(mKernel, mGWS, mLWS,
mOpenCLBackend->getOpenCLRuntime(), &event);
mOpenCLBackend->getOpenCLRuntime()->pushEvent({"Interp", event});
#else
run3DKernelDefault(mKernel, mGWS, mLWS, mOpenCLBackend->getOpenCLRuntime());
#endif
#ifdef LOG_VERBOSE
MNN_PRINT("end InterpBufExecution onExecute... \n");
#endif
return NO_ERROR;
}
class InterpBufCreator : public OpenCLBackend::Creator {
public:
virtual ~InterpBufCreator() = default;
virtual Execution *onCreate(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs, const MNN::Op *op, Backend *backend) const override {
for (int i = 0; i < inputs.size(); ++i) {
TensorUtils::setTensorSupportPack(inputs[i], false);
}
for (int i = 0; i < outputs.size(); ++i) {
TensorUtils::setTensorSupportPack(outputs[i], false);
}
if(op->main_as_Interp()->resizeType() == 3) {
MNN_PRINT("openCL buffer not support interp type:%d, fallback to cpu\n", op->main_as_Interp()->resizeType());
return nullptr;
}
return new InterpBufExecution(inputs, op, backend);
}
};
OpenCLCreatorRegister<InterpBufCreator> __InterpBuf_op_(OpType_Interp, BUFFER);
} // namespace OpenCL
} // namespace MNN
#endif /* MNN_OPENCL_BUFFER_CLOSED */