chore: import upstream snapshot with attribution

2026-07-13 13:33:03 +08:00
commit 5b57521aa1
8226 changed files with 3425766 additions and 0 deletions
@@ -0,0 +1,76 @@
+//
+//  SelectExecution.cpp
+//  MNN
+//
+//  Created by MNN on 2023/12/1.
+//  Copyright © 2018, Alibaba Group Holding Limited
+//
+
+#include "backend/opencl/execution/image/SelectExecution.hpp"
+#include "core/Macro.h"
+#include "core/TensorUtils.hpp"
+#include "backend/opencl/core/OpenCLBackend.hpp"
+
+namespace MNN {
+namespace OpenCL {
+
+SelectExecution::SelectExecution(const MNN::Op *op, Backend* backend) : CommonExecution(backend, op) {
+    // Do nothing
+}
+ErrorCode SelectExecution::onEncode(const std::vector<Tensor*>& inputs, const std::vector<Tensor*>& outputs) {
+    mUnits.resize(1);
+    auto &unit = mUnits[0];
+    auto inSize1 = inputs[1]->elementSize();
+    auto inSize2 = inputs[2]->elementSize();
+    auto openCLBackend = static_cast<OpenCLBackend*>(backend());
+    auto runtime       = openCLBackend->getOpenCLRuntime();
+    std::set<std::string> buildOptions = mBuildOptions;
+    if(inSize1 == 1)
+        buildOptions.emplace("-DINSIZE1_EUQAL_1");
+    if(inSize2 == 1)
+        buildOptions.emplace("-DINSIZE2_EUQAL_1");
+    unit.kernel = runtime->buildKernel("select", "select_img", buildOptions, openCLBackend->getPrecision());
+    mMaxWorkGroupSize = static_cast<uint32_t>(runtime->getMaxWorkGroupSize(unit.kernel));
+
+    std::vector<int> outputShape = tensorShapeFormat(outputs[0]);
+
+    int batch        = outputShape.at(0);
+    int outputHeight = outputShape.at(1);
+    int outputWidth  = outputShape.at(2);
+    int channels     = outputShape.at(3);
+    int channelBlocks = (channels + 3) / 4;
+
+    mGlobalWorkSize = {
+        static_cast<uint32_t>(channelBlocks * outputWidth),
+        static_cast<uint32_t>(batch * outputHeight)
+    };
+
+    uint32_t idx = 0;
+    cl_int ret = CL_SUCCESS;
+    ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[0]);
+    ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[1]);
+    ret |= unit.kernel->get().setArg(idx++, openCLImage(inputs[0]));
+    ret |= unit.kernel->get().setArg(idx++, openCLImage(inputs[1]));
+    ret |= unit.kernel->get().setArg(idx++, openCLImage(inputs[2]));
+    ret |= unit.kernel->get().setArg(idx++, openCLImage(outputs[0]));
+    MNN_CHECK_CL_SUCCESS(ret, "setArg SelectExecution");
+
+    std::string kernelName = "select_img";
+    mLocalSize = localWS2DDefault(mGlobalWorkSize, mMaxWorkGroupSize, openCLBackend->getOpenCLRuntime(), kernelName, unit.kernel, openCLBackend->getCLTuneLevel(), "select").first;
+    openCLBackend->recordKernel2d(unit.kernel, mGlobalWorkSize, mLocalSize);
+    unit.globalWorkSize = {mGlobalWorkSize[0], mGlobalWorkSize[1]};
+    unit.localWorkSize = {mLocalSize[0], mLocalSize[1]};
+    return NO_ERROR;
+}
+
+class SelectCreator : public OpenCLBackend::Creator {
+public:
+    virtual Execution* onCreate(const std::vector<Tensor*>& inputs, const std::vector<Tensor*>& outputs,
+                                const MNN::Op* op, Backend* backend) const override {
+        OPENCL_CREATOR_CHECK(new SelectExecution(op, backend));
+    }
+};
+
+REGISTER_OPENCL_OP_CREATOR(SelectCreator, OpType_Select, IMAGE);
+} // namespace OpenCL
+} // namespace MNN