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