mirror of https://github.com/alibaba/MNN.git
64 lines
2.0 KiB
C++
64 lines
2.0 KiB
C++
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//
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// CPUGather.cpp
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// MNN
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//
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// Created by MNN on 2018/08/02.
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// Copyright © 2018, Alibaba Group Holding Limited
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//
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#include "CPUGather.hpp"
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#include "CPUBackend.hpp"
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#include "CommonOptFunction.h"
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#include "Macro.h"
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namespace MNN {
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CPUGather::CPUGather(Backend *b, const MNN::Op *op) : MNN::Execution(b), mOp(op) {
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// nothing to do
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}
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ErrorCode CPUGather::onResize(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
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MNN_ASSERT(1 == outputs.size());
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auto indices = inputs[1];
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MNN_ASSERT(indices->buffer().type.bits == 32 && mOp->main_as_Gather()->Tindices() == DataType_DT_INT32);
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return NO_ERROR;
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}
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ErrorCode CPUGather::onExecute(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
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auto embedding = inputs[0];
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auto indices = inputs[1];
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auto output = outputs[0];
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MNN_ASSERT(embedding->buffer().type.bits == 32);
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const size_t indicesCount = indices->size() / (indices->buffer().type.bits / 8);
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const auto limit = embedding->length(0);
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auto outputData = output->host<float>();
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const float *inputData = embedding->host<float>();
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const int firstDimStride = embedding->buffer().dim[0].stride;
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const int *indicesData = indices->host<int32_t>();
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for (int i = 0; i < indicesCount; i++) {
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if (indicesData[i] < 0 || indicesData[i] > limit) {
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return INPUT_DATA_ERROR;
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}
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memcpy(outputData + i * firstDimStride, inputData + firstDimStride * indicesData[i],
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sizeof(float) * firstDimStride);
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}
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return NO_ERROR;
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}
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class CPUGatherCreator : 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 override {
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return new CPUGather(backend, op);
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}
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};
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REGISTER_CPU_OP_CREATOR(CPUGatherCreator, OpType_Gather);
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} // namespace MNN
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