wehub-resource-sync
78 lines
3.0 KiB
C++
78 lines
3.0 KiB
C++
//
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// NPUScale.cpp
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// MNN
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//
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// Created by MNN on 2019/09/19.
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// Copyright © 2018, Alibaba Group Holding Limited
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//
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#include "NPUScale.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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NPUScale::NPUScale(Backend *b, const Op *op, const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) : MNN::NPUCommonExecution(b,op) {}
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ErrorCode NPUScale::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 param = mOp->main_as_Scale();
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auto scaleData = param->scaleData();
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auto biasData = param->biasData();
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shared_ptr<hiai::op::Scale> scale(new hiai::op::Scale(opName + "_scale"));
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auto xOp = mNpuBackend->getInputOps(mOp);
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// om input filter const op
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mConst_fliter = hiai::op::Const(opName + "_filter_const");
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{
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ge::TensorDesc fdesc(ge::Shape({1, scaleData->size(), 1, 1}), ge::FORMAT_NCHW, ge::DT_FLOAT); // in o h w ?
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ge::TensorPtr filter = std::make_shared<ge::Tensor>();
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filter->SetTensorDesc(fdesc);
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filter->SetData((uint8_t *)scaleData->data(), scaleData->size() * sizeof(float));
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mConst_fliter.set_attr_value(filter);
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}
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// om input bias const op
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mConst_bias = hiai::op::Const(opName + "_bias_const");
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{
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ge::TensorDesc fdesc(ge::Shape({1, biasData->size(), 1, 1}), ge::FORMAT_NCHW, ge::DT_FLOAT);
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ge::TensorPtr filter = std::make_shared<ge::Tensor>();
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filter->SetTensorDesc(fdesc);
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filter->SetData((uint8_t *)biasData->data(), biasData->size() * sizeof(float));
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mConst_bias.set_attr_value(filter);
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}
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if (inputs[0]->buffer().dimensions == 2) {
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vector<int32_t> shape;
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for (int32_t i = 0; i < inputs[0]->buffer().dimensions; i++) {
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shape.push_back(inputs[0]->buffer().dim[i].extent);
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}
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for (int32_t i = inputs[0]->buffer().dimensions; i < 4; i++) {
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shape.push_back(1);
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}
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shapeConst = hiai::op::Const(opName + "_shape_const");
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{
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ge::TensorDesc fdesc(ge::Shape({static_cast<int64_t>(shape.size())}), ge::FORMAT_NCHW, ge::DT_INT32); // in o h w ?
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ge::TensorPtr filter = std::make_shared<ge::Tensor>();
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filter->SetTensorDesc(fdesc);
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filter->SetData((uint8_t *)shape.data(), shape.size() * sizeof(int32_t));
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shapeConst.set_attr_value(filter);
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}
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shared_ptr<hiai::op::Reshape> reshape(new hiai::op::Reshape(opName + "_reshape"));
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(*reshape).set_input_x(*xOp.get()).set_input_shape(shapeConst);
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(*scale).set_input_x(*reshape.get()).set_input_scale(mConst_fliter).set_input_bias(mConst_bias);
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mNpuBackend->setOutputOps(mOp, {reshape, scale}, outputs);
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} else {
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(*scale).set_input_x(*xOp.get()).set_input_scale(mConst_fliter).set_input_bias(mConst_bias);
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mNpuBackend->setOutputOps(mOp, {scale}, outputs);
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}
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return NO_ERROR;
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}
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NPUCreatorRegister<TypedCreator<NPUScale>> __scale_op(OpType_Scale);
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} // namespace MNN
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