493     auto [n2, outputShapes, timing] = executor->computeOnCpuFallback();  in cpuFallbackPartial()
494     return {n2, std::move(outputShapes), timing, executor};  in cpuFallbackPartial()
506     std::vector<OutputShape> outputShapes = executionBuilder->getInitialOutputShapes();  in asyncStartComputePartitioned()  local
531             executionCallback->notify(ErrorStatus::NONE, outputShapes, timing);  in asyncStartComputePartitioned()
540         if (!executor->updateOutputShapes(stepOutputShapes, &outputShapes)) {  in asyncStartComputePartitioned()
556             executionCallback->notify(stepStatus, outputShapes, kNoTiming);  in asyncStartComputePartitioned()
583             !fallbackExecutor->updateOutputShapes(fallbackOutputShapes, &outputShapes)) {  in asyncStartComputePartitioned()
599             executionCallback->notify(fallbackStatus, outputShapes, kNoTiming);  in asyncStartComputePartitioned()
821     auto wrappedFinish = [this](ErrorStatus error, const std::vector<OutputShape>& outputShapes) {  in compute()  argument
822         return finishWithoutSyncFence(error, outputShapes);  in compute()
874     std::vector<OutputShape> outputShapes(mOutputs.size());  in getInitialOutputShapes()  local
875     std::transform(mOutputs.begin(), mOutputs.end(), outputShapes.begin(),  in getInitialOutputShapes()
883     return outputShapes;  in getInitialOutputShapes()
897 bool ExecutionBuilder::updateOutputShapes(const std::vector<OutputShape>& outputShapes) {  in updateOutputShapes()  argument
898     if (outputShapes.size() == 0) {  in updateOutputShapes()
901     NN_RET_CHECK_EQ(outputShapes.size(), mOutputs.size());  in updateOutputShapes()
902     for (uint32_t i = 0; i < outputShapes.size(); i++) {  in updateOutputShapes()
904         NN_RET_CHECK(isUpdatable(mOutputs[i].dimensions(), outputShapes[i].dimensions));  in updateOutputShapes()
907                                                                     outputShapes[i].dimensions));  in updateOutputShapes()
909     for (uint32_t i = 0; i < outputShapes.size(); i++) {  in updateOutputShapes()
910         mOutputs[i].dimensions() = outputShapes[i].dimensions;  in updateOutputShapes()
911         mOutputs[i].isSufficient() = outputShapes[i].isSufficient;  in updateOutputShapes()
926                                                      const std::vector<OutputShape>& outputShapes) {  in finishWithoutSyncFence()  argument
930     if (!updateOutputShapes(outputShapes) || !updateMemories()) {  in finishWithoutSyncFence()
1092     const auto [n, outputShapes, timing] = mPreparedModel->execute(  in computeWithMemories()
1096     return {n, std::move(outputShapes), timing};  in computeWithMemories()
1190     auto [nCompute, outputShapes, timing] = computeWithMemories({}, memories);  in computeOnCpuFallback()
1192         return {nCompute, std::move(outputShapes), timing};  in computeOnCpuFallback()
1205     return {ANEURALNETWORKS_NO_ERROR, std::move(outputShapes), timing};  in computeOnCpuFallback()