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
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+//
+//  CPUQuantizedLogistic.cpp
+//  MNN
+//
+//  Created by MNN on 2018/12/12.
+//  Copyright © 2018, Alibaba Group Holding Limited
+//
+#include "backend/cpu/CPUBackend.hpp"
+#ifdef MNN_SUPPORT_DEPRECATED_OP
+#include "backend/cpu/CPUQuantizedLogistic.hpp"
+#include "backend/cpu/CPUFixedPoint.hpp"
+#include "backend/cpu/CPUQuantizationUtils.hpp"
+#include "core/Macro.h"
+#include "backend/cpu/compute/OptimizedComputer.hpp"
+
+namespace MNN {
+
+CPUQuantizedLogistic::CPUQuantizedLogistic(Backend *backend, const Op *op) : Execution(backend) {
+    mLogisticParam = op->main_as_QuantizedLogistic();
+}
+
+ErrorCode CPUQuantizedLogistic::onResize(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
+    MNN_ASSERT(1 == inputs.size() && 1 == outputs.size());
+    MNN_ASSERT(0 == mLogisticParam->outputQuantizedParam()->zeroPoint() &&
+               1. / 256 == mLogisticParam->outputQuantizedParam()->scale());
+
+    static constexpr int kInputIntegerBits = 4;
+    const double inputRealMultiplier =
+        mLogisticParam->inputQuantizedParam()->scale() * static_cast<double>(1 << (31 - kInputIntegerBits));
+    QuantizeMultiplierGreaterThanOne(inputRealMultiplier, &mInputMultiplier, &mInputLeftShift);
+    mInputZeroPoint = mLogisticParam->inputQuantizedParam()->zeroPoint();
+    mInputRangeRadius = CalculateInputRadius(kInputIntegerBits, mInputLeftShift);
+    return NO_ERROR;
+}
+
+ErrorCode CPUQuantizedLogistic::onExecute(const std::vector<MNN::Tensor *> &inputs,
+                                          const std::vector<MNN::Tensor *> &outputs) {
+    auto input = inputs[0], output = outputs[0];
+    std::vector<int> inputDims, outputDims;
+    for (int i = 0; i < input->buffer().dimensions; i++) {
+        inputDims.push_back(input->buffer().dim[i].extent);
+    }
+    for (int i = 0; i < output->buffer().dimensions; i++) {
+        outputDims.push_back(output->buffer().dim[i].extent);
+    }
+
+    Optimized::Logistic(input->host<uint8_t>(), inputDims, mInputZeroPoint,
+                        mInputRangeRadius, mInputMultiplier, mInputLeftShift, output->host<uint8_t>(), outputDims);
+
+    return NO_ERROR;
+}
+
+class CPUQuantizedLogisticCreator : public CPUBackend::Creator {
+public:
+    virtual Execution *onCreate(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs,
+                                const MNN::Op *op, Backend *backend) const {
+        return new CPUQuantizedLogistic(backend, op);
+    }
+};
+} // namespace MNN
+#endif
+namespace MNN {
+REGISTER_CPU_OP_CREATOR_OLD(CPUQuantizedLogisticCreator, OpType_QuantizedLogistic);
+};