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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+//
+//  TransformBatchNormal.cpp
+//  MNNConverter
+//
+//  Created by MNN on 2019/09/05.
+//  Copyright © 2018, Alibaba Group Holding Limited
+//
+
+#include "../PostTreatUtils.hpp"
+
+class TransformBatchNormal : public PostConverter {
+public:
+    virtual bool onExecute(std::unique_ptr<MNN::NetT>& net) const override {
+        for (auto iter = net->oplists.begin(); iter != net->oplists.end();) {
+            auto& op                 = *iter;
+            const MNN::OpType opType = op->type;
+
+            if (MNN::OpType_BatchNorm != opType) {
+                iter++;
+                continue;
+            }
+            const int inputSize = op->inputIndexes.size();
+            DCHECK(inputSize == 1 || inputSize == 3) << "MNN BatchnNorm input size error!";
+            // instance norm have three input tensors(input_tensor, mean, variance)
+            if (inputSize == 3) {
+                iter++;
+                continue;
+            }
+            // DLOG(INFO) << "change BatchNorm to Scale: " << op->name;
+            auto batchnormParam  = op->main.AsBatchNorm();
+            auto scaleParam      = new MNN::ScaleT;
+            scaleParam->channels = batchnormParam->channels;
+            scaleParam->scaleData.resize(batchnormParam->channels);
+            scaleParam->biasData.resize(batchnormParam->channels);
+            const float* slopePtr    = batchnormParam->slopeData.data();
+            const float* meanDataPtr = batchnormParam->meanData.data();
+            const float* varDataPtr  = batchnormParam->varData.data();
+            const float* biasDataPtr = batchnormParam->biasData.data();
+            const float eps          = batchnormParam->epsilon;
+
+            for (int i = 0; i < batchnormParam->channels; i++) {
+                float sqrt_var           = sqrt(varDataPtr[i] + eps);
+                scaleParam->biasData[i]  = biasDataPtr[i] - slopePtr[i] * meanDataPtr[i] / sqrt_var;
+                scaleParam->scaleData[i] = slopePtr[i] / sqrt_var;
+            }
+
+            op->type       = MNN::OpType_Scale;
+            op->main.type  = MNN::OpParameter_Scale;
+            op->main.value = scaleParam;
+        }
+        return true;
+    }
+};
+static PostConverterRegister<TransformBatchNormal> __l("TransformBatchNormal");