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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+//
+//  NNAPIActivation.cpp
+//  MNN
+//
+//  Created by MNN on 2022/09/30.
+//  Copyright © 2018, Alibaba Group Holding Limited
+//
+
+#include "NNAPIActivation.hpp"
+
+namespace MNN {
+
+
+NNAPIActivation::NNAPIActivation(MNN::Backend *b, const MNN::Op *op, const std::vector<Tensor *> &inputs, const std::vector<MNN::Tensor *> &outputs) : NNAPICommonExecution(b, op) {
+}
+
+ErrorCode NNAPIActivation::onResize(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
+    auto inputIdxs = getTensorIdxs(inputs);
+    auto opType = mOp->type();
+    int activateType = -1;
+    switch (opType) {
+        case OpType_Softmax: {
+            // NNAPI Softmax inputs: [input, beta, axis]
+            activateType = ANEURALNETWORKS_SOFTMAX;
+            int axis = mOp->main_as_Axis()->axis();
+            float beta = 1.0;
+            inputIdxs.push_back(buildScalar(beta));
+            bool needAxis = false;
+            auto dims = inputs[0]->shape();
+            for (int i = 0; i < dims.size(); i++) {
+                if (i != axis && dims[i] > 1) {
+                    needAxis = true;
+                    break;
+                }
+            }
+            if (needAxis) {
+                inputIdxs.push_back(buildScalar(formatAxis(axis, inputs[0])));
+            }
+            break;
+        }
+        case OpType_ReLU:
+            activateType = ANEURALNETWORKS_RELU;
+            break;
+        case OpType_ReLU6:
+            activateType = ANEURALNETWORKS_RELU6;
+            break;
+        case OpType_PReLU:
+            activateType = ANEURALNETWORKS_PRELU;
+            inputIdxs.push_back(buildConstant(mOp->main_as_PRelu()->slope()->Data(),
+                                              mOp->main_as_PRelu()->slopeCount() * sizeof(float),
+                                              ANEURALNETWORKS_TENSOR_FLOAT32,
+                                              {static_cast<uint32_t>(mOp->main_as_PRelu()->slopeCount())}));
+            break;
+        case OpType_Sigmoid:
+            activateType = ANEURALNETWORKS_LOGISTIC;
+            break;
+        case OpType_ELU:
+            activateType = ANEURALNETWORKS_ELU;
+            inputIdxs.push_back(buildScalar(mOp->main_as_ELU()->alpha()));
+            break;
+        default:
+            MNN_ERROR("[NNAPI] Activation not support %s\n", MNN::EnumNameOpType(opType));
+            return NOT_SUPPORT;
+    }
+    return buildOperation(activateType, inputIdxs, getTensorIdxs(outputs));
+}
+
+REGISTER_NNAPI_OP_CREATOR(NNAPIActivation, OpType_Softmax)
+REGISTER_NNAPI_OP_CREATOR(NNAPIActivation, OpType_ReLU)
+REGISTER_NNAPI_OP_CREATOR(NNAPIActivation, OpType_ReLU6)
+REGISTER_NNAPI_OP_CREATOR(NNAPIActivation, OpType_PReLU)
+REGISTER_NNAPI_OP_CREATOR(NNAPIActivation, OpType_Sigmoid)
+REGISTER_NNAPI_OP_CREATOR(NNAPIActivation, OpType_ELU)
+} // namespace MNN