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 @@
+//
+//  NNAPICommonExecution.cpp
+//  MNN
+//
+//  Created by MNN on 2022/09/05.
+//  Copyright © 2018, Alibaba Group Holding Limited
+//
+
+#include "NNAPICommonExecution.hpp"
+namespace MNN {
+
+NNAPICommonExecution::NNAPICommonExecution(Backend *backend, const Op *op) : Execution(backend), mOp(op) {
+    mNNAPIBackend = (NNAPIBackend*)backend;
+    mNCHW = mNNAPIBackend->NCHW();
+}
+
+ErrorCode NNAPICommonExecution::onResize(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
+    return NO_ERROR;
+}
+
+ErrorCode NNAPICommonExecution::onExecute(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
+    return NO_ERROR;
+}
+
+std::vector<uint32_t> NNAPICommonExecution::getTensorIdxs(const std::vector<Tensor*>& tensors) {
+    std::vector<uint32_t> idxs(tensors.size());
+    for (int i = 0; i < tensors.size(); i++) {
+        idxs[i] = mNNAPIBackend->getTensorIdx(tensors[i], true);
+    }
+    return idxs;
+}
+
+uint32_t NNAPICommonExecution::buildConstant(const void* data, size_t size, OperandCode dtype, std::vector<uint32_t> dims, const float* scales, int zero) {
+    return mNNAPIBackend->buildOperand(data, size, dtype, dims, scales, zero);
+}
+
+uint32_t NNAPICommonExecution::buildVector(const std::vector<int32_t>& vec) {
+    return buildConstant(vec.data(), vec.size() * sizeof(int), ANEURALNETWORKS_TENSOR_INT32, {static_cast<uint32_t>(vec.size())});
+}
+
+uint32_t NNAPICommonExecution::buildVector(const std::vector<float>& vec) {
+    return buildConstant(vec.data(), vec.size() * sizeof(float), ANEURALNETWORKS_TENSOR_FLOAT32, {static_cast<uint32_t>(vec.size())});
+}
+
+uint32_t NNAPICommonExecution::buildTensor(OperandCode dtype, std::vector<int> dims) {
+    std::vector<uint32_t> udims(dims.begin(), dims.end());
+    if (!mNCHW) {
+        // NCHW -> NHWC
+        udims[0] = dims[0];
+        udims[1] = dims[2];
+        udims[2] = dims[3];
+        udims[3] = dims[1];
+    }
+    return mNNAPIBackend->buildOperand(nullptr, 0, dtype, udims);
+}
+
+int NNAPICommonExecution::formatAxis(int axis, const Tensor* t) {
+    if (t->dimensions() < 4) {
+        return axis;
+    }
+    if (!mNCHW && TensorUtils::getDescribe(t)->dimensionFormat != MNN_DATA_FORMAT_NHWC) {
+        // NCHW -> NHWC
+        const int axisChange[4] = {0, 3, 1, 2};
+        if (axis > 3) {
+            axis = axis;
+        } else {
+            axis = axisChange[axis];
+        }
+    }
+    return axis;
+}
+ErrorCode NNAPICommonExecution::buildOperation(int op, const std::vector<uint32_t> &inputs, const std::vector<uint32_t> &outputs) {
+    auto name = mOp->name() ? mOp->name()->c_str() : EnumNameOpType(mOp->type());
+    return mNNAPIBackend->buildOperation(op, inputs, outputs, name);
+}
+}; // namespace MNN