mirror of https://github.com/alibaba/MNN.git
84 lines
2.6 KiB
C++
84 lines
2.6 KiB
C++
//
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// CPUPack.cpp
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// MNN
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//
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// Created by MNN on 2018/08/14.
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// Copyright © 2018, Alibaba Group Holding Limited
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//
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#include "backend/cpu/CPUPack.hpp"
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#include "backend/cpu/CPUBackend.hpp"
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namespace MNN {
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CPUPack::CPUPack(Backend *backend, int axis)
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: Execution(backend), mAxis(axis) {
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// nothing to do
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}
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template <typename T>
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ErrorCode CPUPack::MNNPackLayerForward(const std::vector<MNN::Tensor *> &inputs,
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const std::vector<MNN::Tensor *> &outputs) {
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auto output = outputs[0];
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const int outputDimensions = output->buffer().dimensions;
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auto mN = inputs.size();
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if (mAxis == 0) {
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auto dstPtr = outputs[0]->buffer().host;
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for (int i = 0; i < mN; i++) {
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auto inputX = inputs[i];
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auto sourcePtr = inputX->buffer().host;
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memcpy(dstPtr, sourcePtr, inputX->size());
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dstPtr += inputX->size();
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}
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} else {
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int outputDataCount = 1;
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for (int i = 0; i < outputDimensions; i++) {
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outputDataCount *= output->buffer().dim[i].extent;
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}
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int r;
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for (int offset = 0, cordOnAxis = 0; offset < outputDataCount; offset++) {
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r = offset;
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int inputOffset = 0;
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for (int i = 0, j = 0, cord; i < outputDimensions; i++) {
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cord = r / output->buffer().dim[i].stride;
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r = r % output->buffer().dim[i].stride;
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if (i != mAxis) {
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inputOffset += (cord * inputs[0]->buffer().dim[j++].stride);
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} else {
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cordOnAxis = cord;
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}
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}
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((T *)output->buffer().host)[offset] = ((T *)inputs[cordOnAxis]->buffer().host)[inputOffset];
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}
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}
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return NO_ERROR;
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}
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ErrorCode CPUPack::onExecute(const std::vector<MNN::Tensor *> &inputs, const std::vector<MNN::Tensor *> &outputs) {
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auto input = inputs[0];
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auto output = outputs[0];
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if (inputs.size() == 1) {
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::memcpy(output->buffer().host, input->buffer().host, input->size());
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return NO_ERROR;
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}
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return MNNPackLayerForward<int32_t>(inputs, outputs);
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}
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class CPUPackCreator : public CPUBackend::Creator {
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public:
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virtual Execution *onCreate(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs,
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const MNN::Op *op, Backend *backend) const {
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auto pack = op->main_as_PackParam();
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return new CPUPack(backend, pack->axis());
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}
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};
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REGISTER_CPU_OP_CREATOR(CPUPackCreator, OpType_Pack);
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} // namespace MNN
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