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 +1,67 @@
+//
+//  NPUConvertTensor.cpp
+//  MNN
+//
+//  Created by MNN on b'2020/10/15'.
+//  Copyright © 2018, Alibaba Group Holding Limited
+//
+
+#include "NPUConvertTensor.hpp"
+#include "NPUBackend.hpp"
+
+using namespace std;
+
+namespace MNN {
+
+NPUConvertTensor::NPUConvertTensor(MNN::Backend *b, const MNN::Op *op, const std::vector<Tensor *> &inputs, const std::vector<MNN::Tensor *> &outputs) : NPUCommonExecution(b, op) {
+}
+
+ErrorCode NPUConvertTensor::onResize(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
+    mNpuBackend->setNetworkInput(inputs, mOp);
+
+    auto opName = mOp->name()->str();
+    auto xOp = mNpuBackend->getInputOps(mOp);
+    //om input weight const op
+    std::vector<int32_t> inputShape = inputs[0]->shape();
+    std::vector<int32_t> outShape = outputs[0]->shape();
+    std::vector<std::vector<int64_t>> dims ={{0,1,2,3}, {0,2,3,1}, {0,3,1,2}, {0,1,2}, {0,2,1}, {0,1}, {1,0}};
+
+    int32_t dimIndex = -1;
+    bool flag = true;
+    if (inputShape.size() != outShape.size()) {
+        std::cout<<"inputsize not equal outputs size" <<std::endl;
+        return NOT_SUPPORT;
+    }
+    for (int32_t i = 0; i < dims.size(); i++) {
+        flag = true;
+        for (int32_t j = 0; j < inputShape.size(); j++) {
+            if (dims[i].size() != inputShape.size() || inputShape[dims[i][j]] != outShape[j]) {
+                flag = false;
+                break;
+            }
+        }
+        if (flag) {
+            dimIndex = i;
+            break;
+        }
+    }
+    if (dimIndex == -1) {
+        std::cout<<"inputsize cannot tans output" <<std::endl;
+        return NOT_SUPPORT;
+    }
+    shared_ptr<hiai::op::Permute> convertTensor(new hiai::op::Permute(opName));
+    int index = mOp->inputIndexes()->data()[0];
+    auto iter = mNpuBackend->mSclipMap.find(index);
+    if (iter != mNpuBackend->mSclipMap.end()){
+        (*convertTensor).set_input_x(xOp->GetOutput(mNpuBackend->mSclipMap[index]))
+                        .set_attr_order(dims[dimIndex]);
+    } else {
+        (*convertTensor).set_input_x(*xOp).set_attr_order(dims[dimIndex]);
+    }
+    mNpuBackend->setOutputOps(mOp, {convertTensor}, outputs);
+    return NO_ERROR;
+}
+
+NPUCreatorRegister<TypedCreator<NPUConvertTensor>> __convert_tensor_op(OpType_ConvertTensor);
+
+} // namespace MNN