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126 lines
4.8 KiB
126 lines
4.8 KiB
#include <cassert>
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#include <stdlib.h>
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#include "common/util.h"
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#include "snpemodel.h"
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void PrintErrorStringAndExit() {
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const char* const errStr = zdl::DlSystem::getLastErrorString();
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std::cerr << zdl::DlSystem::getLastErrorString() << std::endl;
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std::exit(EXIT_FAILURE);
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}
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SNPEModel::SNPEModel(const char *path, float *output, size_t output_size, int runtime) {
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#ifdef QCOM
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zdl::DlSystem::Runtime_t Runtime;
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if (runtime==USE_GPU_RUNTIME) {
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Runtime = zdl::DlSystem::Runtime_t::GPU;
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} else if (runtime==USE_DSP_RUNTIME) {
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Runtime = zdl::DlSystem::Runtime_t::DSP;
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} else {
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Runtime = zdl::DlSystem::Runtime_t::CPU;
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}
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assert(zdl::SNPE::SNPEFactory::isRuntimeAvailable(Runtime));
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#endif
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size_t model_size;
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model_data = (uint8_t *)read_file(path, &model_size);
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assert(model_data);
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// load model
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std::unique_ptr<zdl::DlContainer::IDlContainer> container = zdl::DlContainer::IDlContainer::open(model_data, model_size);
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if (!container) { PrintErrorStringAndExit(); }
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printf("loaded model with size: %u\n", model_size);
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// create model runner
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zdl::SNPE::SNPEBuilder snpeBuilder(container.get());
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while (!snpe) {
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#ifdef QCOM
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snpe = snpeBuilder.setOutputLayers({})
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.setRuntimeProcessor(Runtime)
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.setUseUserSuppliedBuffers(true)
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.setPerformanceProfile(zdl::DlSystem::PerformanceProfile_t::HIGH_PERFORMANCE)
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.build();
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#else
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snpe = snpeBuilder.setOutputLayers({})
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.setUseUserSuppliedBuffers(true)
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.setPerformanceProfile(zdl::DlSystem::PerformanceProfile_t::HIGH_PERFORMANCE)
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.build();
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#endif
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if (!snpe) std::cerr << zdl::DlSystem::getLastErrorString() << std::endl;
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}
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// get input and output names
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const auto &strListi_opt = snpe->getInputTensorNames();
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if (!strListi_opt) throw std::runtime_error("Error obtaining Input tensor names");
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const auto &strListi = *strListi_opt;
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//assert(strListi.size() == 1);
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const char *input_tensor_name = strListi.at(0);
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const auto &strListo_opt = snpe->getOutputTensorNames();
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if (!strListo_opt) throw std::runtime_error("Error obtaining Output tensor names");
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const auto &strListo = *strListo_opt;
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assert(strListo.size() == 1);
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const char *output_tensor_name = strListo.at(0);
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printf("model: %s -> %s\n", input_tensor_name, output_tensor_name);
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zdl::DlSystem::UserBufferEncodingFloat userBufferEncodingFloat;
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zdl::DlSystem::IUserBufferFactory& ubFactory = zdl::SNPE::SNPEFactory::getUserBufferFactory();
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// create input buffer
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{
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const auto &inputDims_opt = snpe->getInputDimensions(input_tensor_name);
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const zdl::DlSystem::TensorShape& bufferShape = *inputDims_opt;
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std::vector<size_t> strides(bufferShape.rank());
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strides[strides.size() - 1] = sizeof(float);
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size_t product = 1;
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for (size_t i = 0; i < bufferShape.rank(); i++) product *= bufferShape[i];
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size_t stride = strides[strides.size() - 1];
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for (size_t i = bufferShape.rank() - 1; i > 0; i--) {
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stride *= bufferShape[i];
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strides[i-1] = stride;
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}
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printf("input product is %u\n", product);
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inputBuffer = ubFactory.createUserBuffer(NULL, product*sizeof(float), strides, &userBufferEncodingFloat);
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inputMap.add(input_tensor_name, inputBuffer.get());
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}
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// create output buffer
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{
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std::vector<size_t> outputStrides = {output_size * sizeof(float), sizeof(float)};
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outputBuffer = ubFactory.createUserBuffer(output, output_size * sizeof(float), outputStrides, &userBufferEncodingFloat);
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outputMap.add(output_tensor_name, outputBuffer.get());
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}
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}
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void SNPEModel::addRecurrent(float *state, int state_size) {
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recurrentBuffer = this->addExtra(state, state_size, 2);
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}
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void SNPEModel::addDesire(float *state, int state_size) {
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desireBuffer = this->addExtra(state, state_size, 1);
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}
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std::unique_ptr<zdl::DlSystem::IUserBuffer> SNPEModel::addExtra(float *state, int state_size, int idx) {
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// get input and output names
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const auto &strListi_opt = snpe->getInputTensorNames();
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if (!strListi_opt) throw std::runtime_error("Error obtaining Input tensor names");
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const auto &strListi = *strListi_opt;
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const char *input_tensor_name = strListi.at(idx);
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printf("adding index %d: %s\n", idx, input_tensor_name);
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zdl::DlSystem::UserBufferEncodingFloat userBufferEncodingFloat;
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zdl::DlSystem::IUserBufferFactory& ubFactory = zdl::SNPE::SNPEFactory::getUserBufferFactory();
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std::vector<size_t> retStrides = {state_size * sizeof(float), sizeof(float)};
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auto ret = ubFactory.createUserBuffer(state, state_size * sizeof(float), retStrides, &userBufferEncodingFloat);
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inputMap.add(input_tensor_name, ret.get());
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return ret;
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}
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void SNPEModel::execute(float *net_input_buf) {
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assert(inputBuffer->setBufferAddress(net_input_buf));
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if (!snpe->execute(inputMap, outputMap)) {
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PrintErrorStringAndExit();
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}
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}
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