158       mOutputs(mModel->outputCount()) {  in ExecutionBuilder()
160                     << " inputs and " << mOutputs.size() << " outputs";  in ExecutionBuilder()
266     uint32_t count = static_cast<uint32_t>(mOutputs.size());  in setOutput()
280     if (!mOutputs[index].unspecified()) {  in setOutput()
286     std::tie(n, mOutputs[index]) = ModelArgumentInfo::createFromPointer(  in setOutput()
302     uint32_t count = static_cast<uint32_t>(mOutputs.size());  in setOutputFromMemory()
326     if (!mOutputs[index].unspecified()) {  in setOutputFromMemory()
332     std::tie(n, mOutputs[index]) =  in setOutputFromMemory()
491     uint32_t count = static_cast<uint32_t>(mOutputs.size());  in getOutputOperandDimensions()
497     const auto& dims = mOutputs[index].dimensions();  in getOutputOperandDimensions()
504     return mOutputs[index].isSufficient() ? ANEURALNETWORKS_NO_ERROR  in getOutputOperandDimensions()
519     uint32_t count = static_cast<uint32_t>(mOutputs.size());  in getOutputOperandRank()
525     *rank = static_cast<uint32_t>(mOutputs[index].dimensions().size());  in getOutputOperandRank()
526     return mOutputs[index].isSufficient() ? ANEURALNETWORKS_NO_ERROR  in getOutputOperandRank()
567         mValidationResultCode = validateRequest(mInputs, mOutputs);  in getValidationResultCode()
575         for (uint32_t i = 0; i < mOutputs.size(); i++) {  in areOutputsFullySpecified()
576             if (mOutputs[i].state() != ModelArgumentInfo::HAS_NO_VALUE &&  in areOutputsFullySpecified()
579                                                mOutputs[i].initialDimensions())) {  in areOutputsFullySpecified()
1036         for (auto& output : mOutputs) {  in compute()
1091     std::vector<OutputShape> outputShapes(mOutputs.size());  in getInitialOutputShapes()
1092     std::transform(mOutputs.begin(), mOutputs.end(), outputShapes.begin(),  in getInitialOutputShapes()
1128     NN_RET_CHECK_EQ(outputShapes.size(), mOutputs.size());  in updateOutputShapes()
1131         NN_RET_CHECK(isUpdatable(mOutputs[i].dimensions(), outputShapes[i].dimensions));  in updateOutputShapes()
1137         mOutputs[i].dimensions() = outputShapes[i].dimensions;  in updateOutputShapes()
1138         mOutputs[i].isSufficient() = outputShapes[i].isSufficient;  in updateOutputShapes()
1144     for (const auto& output : mOutputs) {  in updateMemories()
1158     for (const auto& output : mOutputs) {  in finishComputation()
1324       mOutputs(model->outputCount()),  in StepExecutor()
1330                     << mOutputs.size() << " outputs";  in StepExecutor()
1339     mOutputs = mExecutionBuilder->mOutputs;  in mapInputsAndOutputsTrivially()
1451                 mInputs, mOutputs, mMemories.getObjects(), measure, loopTimeoutDuration);  in getReusableExecution()
1464         logArguments("output", mOutputs);  in compute()
1482                 mPreparedModel->execute(mInputs, mOutputs, mMemories.getObjects(), burstController,  in compute()
1494         logArguments("output", mOutputs);  in computeFenced()
1519                 mInputs, mOutputs, mMemories.getObjects(), waitFor, measure, deadline,  in computeFenced()
1558     for (auto& output : mOutputs) {  in computeOnCpuFallback()
1595             mInputs, mOutputs, memories, nullptr, measure, {}, loopTimeoutDuration);  in computeOnCpuFallback()