Make NNAPI countNumberOfConsumers return GeneralResult -- hal
Previously, countNumberOfConsumers would trigger a CHECK if the input
was invalid. This CL makes countNumberOfConsumers gracefully fail on
errors, instead returning the error through the GeneralResult.
Bug: N/A
Test: mma
Change-Id: Iee54f87768e52fdf701c22d94083c053b881733d
Merged-In: Iee54f87768e52fdf701c22d94083c053b881733d
(cherry picked from commit c4d98007fd2ff50031b270801274ee4c498afd87)
diff --git a/neuralnetworks/1.0/utils/src/Conversions.cpp b/neuralnetworks/1.0/utils/src/Conversions.cpp
index 7a099cf..700b050 100644
--- a/neuralnetworks/1.0/utils/src/Conversions.cpp
+++ b/neuralnetworks/1.0/utils/src/Conversions.cpp
@@ -162,7 +162,7 @@
// Verify number of consumers.
const auto numberOfConsumers =
- hal::utils::countNumberOfConsumers(model.operands.size(), operations);
+ NN_TRY(hal::utils::countNumberOfConsumers(model.operands.size(), operations));
CHECK(model.operands.size() == numberOfConsumers.size());
for (size_t i = 0; i < model.operands.size(); ++i) {
if (model.operands[i].numberOfConsumers != numberOfConsumers[i]) {
@@ -360,7 +360,7 @@
// Update number of consumers.
const auto numberOfConsumers =
- hal::utils::countNumberOfConsumers(operands.size(), model.main.operations);
+ NN_TRY(hal::utils::countNumberOfConsumers(operands.size(), model.main.operations));
CHECK(operands.size() == numberOfConsumers.size());
for (size_t i = 0; i < operands.size(); ++i) {
operands[i].numberOfConsumers = numberOfConsumers[i];
diff --git a/neuralnetworks/1.1/utils/src/Conversions.cpp b/neuralnetworks/1.1/utils/src/Conversions.cpp
index 07bf7bc..d07f7d0 100644
--- a/neuralnetworks/1.1/utils/src/Conversions.cpp
+++ b/neuralnetworks/1.1/utils/src/Conversions.cpp
@@ -111,7 +111,7 @@
// Verify number of consumers.
const auto numberOfConsumers =
- hal::utils::countNumberOfConsumers(model.operands.size(), operations);
+ NN_TRY(hal::utils::countNumberOfConsumers(model.operands.size(), operations));
CHECK(model.operands.size() == numberOfConsumers.size());
for (size_t i = 0; i < model.operands.size(); ++i) {
if (model.operands[i].numberOfConsumers != numberOfConsumers[i]) {
@@ -241,7 +241,7 @@
// Update number of consumers.
const auto numberOfConsumers =
- hal::utils::countNumberOfConsumers(operands.size(), model.main.operations);
+ NN_TRY(hal::utils::countNumberOfConsumers(operands.size(), model.main.operations));
CHECK(operands.size() == numberOfConsumers.size());
for (size_t i = 0; i < operands.size(); ++i) {
operands[i].numberOfConsumers = numberOfConsumers[i];
diff --git a/neuralnetworks/1.2/utils/src/Conversions.cpp b/neuralnetworks/1.2/utils/src/Conversions.cpp
index 7ae483e..86a417a 100644
--- a/neuralnetworks/1.2/utils/src/Conversions.cpp
+++ b/neuralnetworks/1.2/utils/src/Conversions.cpp
@@ -227,7 +227,7 @@
// Verify number of consumers.
const auto numberOfConsumers =
- hal::utils::countNumberOfConsumers(model.operands.size(), operations);
+ NN_TRY(hal::utils::countNumberOfConsumers(model.operands.size(), operations));
CHECK(model.operands.size() == numberOfConsumers.size());
for (size_t i = 0; i < model.operands.size(); ++i) {
if (model.operands[i].numberOfConsumers != numberOfConsumers[i]) {
@@ -529,7 +529,7 @@
// Update number of consumers.
const auto numberOfConsumers =
- hal::utils::countNumberOfConsumers(operands.size(), model.main.operations);
+ NN_TRY(hal::utils::countNumberOfConsumers(operands.size(), model.main.operations));
CHECK(operands.size() == numberOfConsumers.size());
for (size_t i = 0; i < operands.size(); ++i) {
operands[i].numberOfConsumers = numberOfConsumers[i];
diff --git a/neuralnetworks/1.3/utils/src/Conversions.cpp b/neuralnetworks/1.3/utils/src/Conversions.cpp
index 6e74a62..320c74c 100644
--- a/neuralnetworks/1.3/utils/src/Conversions.cpp
+++ b/neuralnetworks/1.3/utils/src/Conversions.cpp
@@ -217,7 +217,7 @@
// Verify number of consumers.
const auto numberOfConsumers =
- hal::utils::countNumberOfConsumers(subgraph.operands.size(), operations);
+ NN_TRY(hal::utils::countNumberOfConsumers(subgraph.operands.size(), operations));
CHECK(subgraph.operands.size() == numberOfConsumers.size());
for (size_t i = 0; i < subgraph.operands.size(); ++i) {
if (subgraph.operands[i].numberOfConsumers != numberOfConsumers[i]) {
@@ -559,7 +559,7 @@
// Update number of consumers.
const auto numberOfConsumers =
- hal::utils::countNumberOfConsumers(operands.size(), subgraph.operations);
+ NN_TRY(hal::utils::countNumberOfConsumers(operands.size(), subgraph.operations));
CHECK(operands.size() == numberOfConsumers.size());
for (size_t i = 0; i < operands.size(); ++i) {
operands[i].numberOfConsumers = numberOfConsumers[i];
diff --git a/neuralnetworks/aidl/vts/functional/ValidateModel.cpp b/neuralnetworks/aidl/vts/functional/ValidateModel.cpp
index b84d981..6d84e1e 100644
--- a/neuralnetworks/aidl/vts/functional/ValidateModel.cpp
+++ b/neuralnetworks/aidl/vts/functional/ValidateModel.cpp
@@ -1310,8 +1310,10 @@
////////////////////////// ENTRY POINT //////////////////////////////
void validateModel(const std::shared_ptr<IDevice>& device, const Model& model) {
- const auto numberOfConsumers = nn::countNumberOfConsumers(
- model.main.operands.size(), nn::convert(model.main.operations).value());
+ const auto numberOfConsumers =
+ nn::countNumberOfConsumers(model.main.operands.size(),
+ nn::convert(model.main.operations).value())
+ .value();
mutateExecutionOrderTest(device, model, numberOfConsumers);
mutateOperandTypeTest(device, model);
mutateOperandRankTest(device, model);
diff --git a/neuralnetworks/utils/common/include/nnapi/hal/CommonUtils.h b/neuralnetworks/utils/common/include/nnapi/hal/CommonUtils.h
index 547f203..2f6112a 100644
--- a/neuralnetworks/utils/common/include/nnapi/hal/CommonUtils.h
+++ b/neuralnetworks/utils/common/include/nnapi/hal/CommonUtils.h
@@ -71,8 +71,8 @@
nn::GeneralResult<void> unflushDataFromSharedToPointer(
const nn::Request& request, const std::optional<nn::Request>& maybeRequestInShared);
-std::vector<uint32_t> countNumberOfConsumers(size_t numberOfOperands,
- const std::vector<nn::Operation>& operations);
+nn::GeneralResult<std::vector<uint32_t>> countNumberOfConsumers(
+ size_t numberOfOperands, const std::vector<nn::Operation>& operations);
nn::GeneralResult<hidl_memory> createHidlMemoryFromSharedMemory(const nn::SharedMemory& memory);
nn::GeneralResult<nn::SharedMemory> createSharedMemoryFromHidlMemory(const hidl_memory& memory);
diff --git a/neuralnetworks/utils/common/src/CommonUtils.cpp b/neuralnetworks/utils/common/src/CommonUtils.cpp
index 7a5035f..924ecb2 100644
--- a/neuralnetworks/utils/common/src/CommonUtils.cpp
+++ b/neuralnetworks/utils/common/src/CommonUtils.cpp
@@ -246,9 +246,9 @@
return {};
}
-std::vector<uint32_t> countNumberOfConsumers(size_t numberOfOperands,
- const std::vector<nn::Operation>& operations) {
- return nn::countNumberOfConsumers(numberOfOperands, operations);
+nn::GeneralResult<std::vector<uint32_t>> countNumberOfConsumers(
+ size_t numberOfOperands, const std::vector<nn::Operation>& operations) {
+ return makeGeneralFailure(nn::countNumberOfConsumers(numberOfOperands, operations));
}
nn::GeneralResult<hidl_memory> createHidlMemoryFromSharedMemory(const nn::SharedMemory& memory) {