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Remove hal::utils::countNumberOfConsumers

Browse source 
This CL removes hal::utils::countNumberOfConsumers and uses the existing
nn::countNumberOfConsumers.

This change is part of a larger chain of changes to remove HIDL and AIDL
libraries from neuralnetworks_utils_hal_common.

Bug: N/A
Test: mma
Change-Id: I7d06ea355eae7aa80b94b09a23d606bbb2322120
This commit is contained in:
Michael Butler 2021-10-14 22:04:59 -07:00
parent 68e98f40dc
commit 301ef060e9
7 changed files with 10 additions and 18 deletions
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4
neuralnetworks/1.0/utils/src/Conversions.cpp
View file

@ -155,7 +155,7 @@ GeneralResult<Model> unvalidatedConvert(const hal::V1_0::Model& model) {
// Verify number of consumers.
const auto numberOfConsumers =
NN_TRY(hal::utils::countNumberOfConsumers(model.operands.size(), operations));
NN_TRY(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]) {
@ -346,7 +346,7 @@ nn::GeneralResult<Model> unvalidatedConvert(const nn::Model& model) {
// Update number of consumers.
const auto numberOfConsumers =
NN_TRY(hal::utils::countNumberOfConsumers(operands.size(), model.main.operations));
NN_TRY(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];

4
neuralnetworks/1.1/utils/src/Conversions.cpp
View file

@ -100,7 +100,7 @@ GeneralResult<Model> unvalidatedConvert(const hal::V1_1::Model& model) {
// Verify number of consumers.
const auto numberOfConsumers =
NN_TRY(hal::utils::countNumberOfConsumers(model.operands.size(), operations));
NN_TRY(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]) {
@ -223,7 +223,7 @@ nn::GeneralResult<Model> unvalidatedConvert(const nn::Model& model) {
// Update number of consumers.
const auto numberOfConsumers =
NN_TRY(hal::utils::countNumberOfConsumers(operands.size(), model.main.operations));
NN_TRY(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];

4
neuralnetworks/1.2/utils/src/Conversions.cpp
View file

@ -187,7 +187,7 @@ GeneralResult<Model> unvalidatedConvert(const hal::V1_2::Model& model) {
// Verify number of consumers.
const auto numberOfConsumers =
NN_TRY(hal::utils::countNumberOfConsumers(model.operands.size(), operations));
NN_TRY(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]) {
@ -481,7 +481,7 @@ nn::GeneralResult<Model> unvalidatedConvert(const nn::Model& model) {
// Update number of consumers.
const auto numberOfConsumers =
NN_TRY(hal::utils::countNumberOfConsumers(operands.size(), model.main.operations));
NN_TRY(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];

4
neuralnetworks/1.3/utils/src/Conversions.cpp
View file

@ -194,7 +194,7 @@ GeneralResult<Model::Subgraph> unvalidatedConvert(const hal::V1_3::Subgraph& sub
// Verify number of consumers.
const auto numberOfConsumers =
NN_TRY(hal::utils::countNumberOfConsumers(subgraph.operands.size(), operations));
NN_TRY(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]) {
@ -543,7 +543,7 @@ nn::GeneralResult<Subgraph> unvalidatedConvert(const nn::Model::Subgraph& subgra
// Update number of consumers.
const auto numberOfConsumers =
NN_TRY(hal::utils::countNumberOfConsumers(operands.size(), subgraph.operations));
NN_TRY(countNumberOfConsumers(operands.size(), subgraph.operations));
CHECK(operands.size() == numberOfConsumers.size());
for (size_t i = 0; i < operands.size(); ++i) {
operands[i].numberOfConsumers = numberOfConsumers[i];

4
neuralnetworks/aidl/vts/functional/ValidateModel.cpp
View file

@ -1315,8 +1315,8 @@ static void mutateExecutionPriorityTest(const std::shared_ptr<IDevice>& device,
void validateModel(const std::shared_ptr<IDevice>& device, const Model& model) {
const auto numberOfConsumers =
nn::countNumberOfConsumers(model.main.operands.size(),
nn::unvalidatedConvert(model.main.operations).value())
countNumberOfConsumers(model.main.operands.size(),
nn::unvalidatedConvert(model.main.operations).value())
.value();
mutateExecutionOrderTest(device, model, numberOfConsumers);
mutateOperandTypeTest(device, model);

3
neuralnetworks/utils/common/include/nnapi/hal/CommonUtils.h
View file

@ -125,9 +125,6 @@ nn::GeneralResult<std::reference_wrapper<const nn::Request>> convertRequestFromP
const nn::Request* request, uint32_t alignment, uint32_t padding,
std::optional<nn::Request>* maybeRequestInSharedOut, RequestRelocation* relocationOut);
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);

5
neuralnetworks/utils/common/src/CommonUtils.cpp
View file

@ -331,11 +331,6 @@ nn::GeneralResult<std::reference_wrapper<const nn::Request>> convertRequestFromP
return **maybeRequestInSharedOut;
}
nn::GeneralResult<std::vector<uint32_t>> countNumberOfConsumers(
size_t numberOfOperands, const std::vector<nn::Operation>& operations) {
return nn::countNumberOfConsumers(numberOfOperands, operations);
}
nn::GeneralResult<hidl_memory> createHidlMemoryFromSharedMemory(const nn::SharedMemory& memory) {
if (memory == nullptr) {
return NN_ERROR() << "Memory must be non-empty";