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-rw-r--r--neuralnetworks/1.3/utils/src/Conversions.cpp164
1 files changed, 106 insertions, 58 deletions
diff --git a/neuralnetworks/1.3/utils/src/Conversions.cpp b/neuralnetworks/1.3/utils/src/Conversions.cpp
index e8a4f55afd..4eeb414dc8 100644
--- a/neuralnetworks/1.3/utils/src/Conversions.cpp
+++ b/neuralnetworks/1.3/utils/src/Conversions.cpp
@@ -28,7 +28,6 @@
#include <nnapi/hal/1.0/Conversions.h>
#include <nnapi/hal/1.2/Conversions.h>
#include <nnapi/hal/CommonUtils.h>
-#include <nnapi/hal/HandleError.h>
#include <algorithm>
#include <chrono>
@@ -131,32 +130,38 @@ GeneralResult<Capabilities> unvalidatedConvert(const hal::V1_3::Capabilities& ca
}
auto operandPerformance = NN_TRY(unvalidatedConvert(capabilities.operandPerformance));
- auto table = NN_TRY(hal::utils::makeGeneralFailure(
- Capabilities::OperandPerformanceTable::create(std::move(operandPerformance)),
- nn::ErrorStatus::GENERAL_FAILURE));
-
+ auto table =
+ NN_TRY(Capabilities::OperandPerformanceTable::create(std::move(operandPerformance)));
+
+ const auto relaxedFloat32toFloat16PerformanceScalar =
+ NN_TRY(unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceScalar));
+ const auto relaxedFloat32toFloat16PerformanceTensor =
+ NN_TRY(unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceTensor));
+ const auto ifPerformance = NN_TRY(unvalidatedConvert(capabilities.ifPerformance));
+ const auto whilePerformance = NN_TRY(unvalidatedConvert(capabilities.whilePerformance));
return Capabilities{
- .relaxedFloat32toFloat16PerformanceScalar = NN_TRY(
- unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceScalar)),
- .relaxedFloat32toFloat16PerformanceTensor = NN_TRY(
- unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceTensor)),
+ .relaxedFloat32toFloat16PerformanceScalar = relaxedFloat32toFloat16PerformanceScalar,
+ .relaxedFloat32toFloat16PerformanceTensor = relaxedFloat32toFloat16PerformanceTensor,
.operandPerformance = std::move(table),
- .ifPerformance = NN_TRY(unvalidatedConvert(capabilities.ifPerformance)),
- .whilePerformance = NN_TRY(unvalidatedConvert(capabilities.whilePerformance)),
+ .ifPerformance = ifPerformance,
+ .whilePerformance = whilePerformance,
};
}
GeneralResult<Capabilities::OperandPerformance> unvalidatedConvert(
const hal::V1_3::Capabilities::OperandPerformance& operandPerformance) {
+ const auto type = NN_TRY(unvalidatedConvert(operandPerformance.type));
+ const auto info = NN_TRY(unvalidatedConvert(operandPerformance.info));
return Capabilities::OperandPerformance{
- .type = NN_TRY(unvalidatedConvert(operandPerformance.type)),
- .info = NN_TRY(unvalidatedConvert(operandPerformance.info)),
+ .type = type,
+ .info = info,
};
}
GeneralResult<Operation> unvalidatedConvert(const hal::V1_3::Operation& operation) {
+ const auto type = NN_TRY(unvalidatedConvert(operation.type));
return Operation{
- .type = NN_TRY(unvalidatedConvert(operation.type)),
+ .type = type,
.inputs = operation.inputs,
.outputs = operation.outputs,
};
@@ -168,25 +173,34 @@ GeneralResult<Operand::LifeTime> unvalidatedConvert(
}
GeneralResult<Operand> unvalidatedConvert(const hal::V1_3::Operand& operand) {
+ const auto type = NN_TRY(unvalidatedConvert(operand.type));
+ const auto lifetime = NN_TRY(unvalidatedConvert(operand.lifetime));
+ const auto location = NN_TRY(unvalidatedConvert(operand.location));
+ auto extraParams = NN_TRY(unvalidatedConvert(operand.extraParams));
return Operand{
- .type = NN_TRY(unvalidatedConvert(operand.type)),
+ .type = type,
.dimensions = operand.dimensions,
.scale = operand.scale,
.zeroPoint = operand.zeroPoint,
- .lifetime = NN_TRY(unvalidatedConvert(operand.lifetime)),
- .location = NN_TRY(unvalidatedConvert(operand.location)),
- .extraParams = NN_TRY(unvalidatedConvert(operand.extraParams)),
+ .lifetime = lifetime,
+ .location = location,
+ .extraParams = std::move(extraParams),
};
}
GeneralResult<Model> unvalidatedConvert(const hal::V1_3::Model& model) {
+ auto main = NN_TRY(unvalidatedConvert(model.main));
+ auto referenced = NN_TRY(unvalidatedConvert(model.referenced));
+ auto operandValues = NN_TRY(unvalidatedConvert(model.operandValues));
+ auto pools = NN_TRY(unvalidatedConvert(model.pools));
+ auto extensionNameToPrefix = NN_TRY(unvalidatedConvert(model.extensionNameToPrefix));
return Model{
- .main = NN_TRY(unvalidatedConvert(model.main)),
- .referenced = NN_TRY(unvalidatedConvert(model.referenced)),
- .operandValues = NN_TRY(unvalidatedConvert(model.operandValues)),
- .pools = NN_TRY(unvalidatedConvert(model.pools)),
+ .main = std::move(main),
+ .referenced = std::move(referenced),
+ .operandValues = std::move(operandValues),
+ .pools = std::move(pools),
.relaxComputationFloat32toFloat16 = model.relaxComputationFloat32toFloat16,
- .extensionNameToPrefix = NN_TRY(unvalidatedConvert(model.extensionNameToPrefix)),
+ .extensionNameToPrefix = std::move(extensionNameToPrefix),
};
}
@@ -195,7 +209,7 @@ 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]) {
@@ -206,8 +220,9 @@ GeneralResult<Model::Subgraph> unvalidatedConvert(const hal::V1_3::Subgraph& sub
}
}
+ auto operands = NN_TRY(unvalidatedConvert(subgraph.operands));
return Model::Subgraph{
- .operands = NN_TRY(unvalidatedConvert(subgraph.operands)),
+ .operands = std::move(operands),
.operations = std::move(operations),
.inputIndexes = subgraph.inputIndexes,
.outputIndexes = subgraph.outputIndexes,
@@ -227,10 +242,13 @@ GeneralResult<BufferRole> unvalidatedConvert(const hal::V1_3::BufferRole& buffer
}
GeneralResult<Request> unvalidatedConvert(const hal::V1_3::Request& request) {
+ auto inputs = NN_TRY(unvalidatedConvert(request.inputs));
+ auto outputs = NN_TRY(unvalidatedConvert(request.outputs));
+ auto pools = NN_TRY(unvalidatedConvert(request.pools));
return Request{
- .inputs = NN_TRY(unvalidatedConvert(request.inputs)),
- .outputs = NN_TRY(unvalidatedConvert(request.outputs)),
- .pools = NN_TRY(unvalidatedConvert(request.pools)),
+ .inputs = std::move(inputs),
+ .outputs = std::move(outputs),
+ .pools = std::move(pools),
};
}
@@ -239,7 +257,7 @@ GeneralResult<Request::MemoryPool> unvalidatedConvert(
using Discriminator = hal::V1_3::Request::MemoryPool::hidl_discriminator;
switch (memoryPool.getDiscriminator()) {
case Discriminator::hidlMemory:
- return hal::utils::createSharedMemoryFromHidlMemory(memoryPool.hidlMemory());
+ return unvalidatedConvert(memoryPool.hidlMemory());
case Discriminator::token:
return static_cast<Request::MemoryDomainToken>(memoryPool.token());
}
@@ -381,7 +399,7 @@ nn::GeneralResult<hidl_vec<uint8_t>> unvalidatedConvert(
}
nn::GeneralResult<hidl_handle> unvalidatedConvert(const nn::SharedHandle& handle) {
- return V1_2::utils::unvalidatedConvert(handle);
+ return V1_0::utils::unvalidatedConvert(handle);
}
nn::GeneralResult<hidl_memory> unvalidatedConvert(const nn::SharedMemory& memory) {
@@ -398,7 +416,7 @@ nn::GeneralResult<V1_2::Operand::ExtraParams> unvalidatedConvert(
}
nn::GeneralResult<V1_2::Model::ExtensionNameAndPrefix> unvalidatedConvert(
- const nn::Model::ExtensionNameAndPrefix& extensionNameAndPrefix) {
+ const nn::ExtensionNameAndPrefix& extensionNameAndPrefix) {
return V1_2::utils::unvalidatedConvert(extensionNameAndPrefix);
}
@@ -465,37 +483,45 @@ nn::GeneralResult<Priority> unvalidatedConvert(const nn::Priority& priority) {
}
nn::GeneralResult<Capabilities> unvalidatedConvert(const nn::Capabilities& capabilities) {
- std::vector<nn::Capabilities::OperandPerformance> operandPerformance;
- operandPerformance.reserve(capabilities.operandPerformance.asVector().size());
+ std::vector<nn::Capabilities::OperandPerformance> filteredOperandPerformances;
+ filteredOperandPerformances.reserve(capabilities.operandPerformance.asVector().size());
std::copy_if(capabilities.operandPerformance.asVector().begin(),
capabilities.operandPerformance.asVector().end(),
- std::back_inserter(operandPerformance),
+ std::back_inserter(filteredOperandPerformances),
[](const nn::Capabilities::OperandPerformance& operandPerformance) {
return compliantVersion(operandPerformance.type).has_value();
});
+ const auto relaxedFloat32toFloat16PerformanceScalar =
+ NN_TRY(unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceScalar));
+ const auto relaxedFloat32toFloat16PerformanceTensor =
+ NN_TRY(unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceTensor));
+ auto operandPerformance = NN_TRY(unvalidatedConvert(filteredOperandPerformances));
+ const auto ifPerformance = NN_TRY(unvalidatedConvert(capabilities.ifPerformance));
+ const auto whilePerformance = NN_TRY(unvalidatedConvert(capabilities.whilePerformance));
return Capabilities{
- .relaxedFloat32toFloat16PerformanceScalar = NN_TRY(
- unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceScalar)),
- .relaxedFloat32toFloat16PerformanceTensor = NN_TRY(
- unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceTensor)),
- .operandPerformance = NN_TRY(unvalidatedConvert(operandPerformance)),
- .ifPerformance = NN_TRY(unvalidatedConvert(capabilities.ifPerformance)),
- .whilePerformance = NN_TRY(unvalidatedConvert(capabilities.whilePerformance)),
+ .relaxedFloat32toFloat16PerformanceScalar = relaxedFloat32toFloat16PerformanceScalar,
+ .relaxedFloat32toFloat16PerformanceTensor = relaxedFloat32toFloat16PerformanceTensor,
+ .operandPerformance = std::move(operandPerformance),
+ .ifPerformance = ifPerformance,
+ .whilePerformance = whilePerformance,
};
}
nn::GeneralResult<Capabilities::OperandPerformance> unvalidatedConvert(
const nn::Capabilities::OperandPerformance& operandPerformance) {
+ const auto type = NN_TRY(unvalidatedConvert(operandPerformance.type));
+ const auto info = NN_TRY(unvalidatedConvert(operandPerformance.info));
return Capabilities::OperandPerformance{
- .type = NN_TRY(unvalidatedConvert(operandPerformance.type)),
- .info = NN_TRY(unvalidatedConvert(operandPerformance.info)),
+ .type = type,
+ .info = info,
};
}
nn::GeneralResult<Operation> unvalidatedConvert(const nn::Operation& operation) {
+ const auto type = NN_TRY(unvalidatedConvert(operation.type));
return Operation{
- .type = NN_TRY(unvalidatedConvert(operation.type)),
+ .type = type,
.inputs = operation.inputs,
.outputs = operation.outputs,
};
@@ -511,15 +537,19 @@ nn::GeneralResult<OperandLifeTime> unvalidatedConvert(
}
nn::GeneralResult<Operand> unvalidatedConvert(const nn::Operand& operand) {
+ const auto type = NN_TRY(unvalidatedConvert(operand.type));
+ const auto lifetime = NN_TRY(unvalidatedConvert(operand.lifetime));
+ const auto location = NN_TRY(unvalidatedConvert(operand.location));
+ auto extraParams = NN_TRY(unvalidatedConvert(operand.extraParams));
return Operand{
- .type = NN_TRY(unvalidatedConvert(operand.type)),
+ .type = type,
.dimensions = operand.dimensions,
.numberOfConsumers = 0,
.scale = operand.scale,
.zeroPoint = operand.zeroPoint,
- .lifetime = NN_TRY(unvalidatedConvert(operand.lifetime)),
- .location = NN_TRY(unvalidatedConvert(operand.location)),
- .extraParams = NN_TRY(unvalidatedConvert(operand.extraParams)),
+ .lifetime = lifetime,
+ .location = location,
+ .extraParams = std::move(extraParams),
};
}
@@ -529,13 +559,18 @@ nn::GeneralResult<Model> unvalidatedConvert(const nn::Model& model) {
<< "Model cannot be unvalidatedConverted because it contains pointer-based memory";
}
+ auto main = NN_TRY(unvalidatedConvert(model.main));
+ auto referenced = NN_TRY(unvalidatedConvert(model.referenced));
+ auto operandValues = NN_TRY(unvalidatedConvert(model.operandValues));
+ auto pools = NN_TRY(unvalidatedConvert(model.pools));
+ auto extensionNameToPrefix = NN_TRY(unvalidatedConvert(model.extensionNameToPrefix));
return Model{
- .main = NN_TRY(unvalidatedConvert(model.main)),
- .referenced = NN_TRY(unvalidatedConvert(model.referenced)),
- .operandValues = NN_TRY(unvalidatedConvert(model.operandValues)),
- .pools = NN_TRY(unvalidatedConvert(model.pools)),
+ .main = std::move(main),
+ .referenced = std::move(referenced),
+ .operandValues = std::move(operandValues),
+ .pools = std::move(pools),
.relaxComputationFloat32toFloat16 = model.relaxComputationFloat32toFloat16,
- .extensionNameToPrefix = NN_TRY(unvalidatedConvert(model.extensionNameToPrefix)),
+ .extensionNameToPrefix = std::move(extensionNameToPrefix),
};
}
@@ -544,15 +579,16 @@ 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];
}
+ auto operations = NN_TRY(unvalidatedConvert(subgraph.operations));
return Subgraph{
.operands = std::move(operands),
- .operations = NN_TRY(unvalidatedConvert(subgraph.operations)),
+ .operations = std::move(operations),
.inputIndexes = subgraph.inputIndexes,
.outputIndexes = subgraph.outputIndexes,
};
@@ -576,10 +612,13 @@ nn::GeneralResult<Request> unvalidatedConvert(const nn::Request& request) {
<< "Request cannot be unvalidatedConverted because it contains pointer-based memory";
}
+ auto inputs = NN_TRY(unvalidatedConvert(request.inputs));
+ auto outputs = NN_TRY(unvalidatedConvert(request.outputs));
+ auto pools = NN_TRY(unvalidatedConvert(request.pools));
return Request{
- .inputs = NN_TRY(unvalidatedConvert(request.inputs)),
- .outputs = NN_TRY(unvalidatedConvert(request.outputs)),
- .pools = NN_TRY(unvalidatedConvert(request.pools)),
+ .inputs = std::move(inputs),
+ .outputs = std::move(outputs),
+ .pools = std::move(pools),
};
}
@@ -728,4 +767,13 @@ nn::GeneralResult<V1_2::Timing> convert(const nn::Timing& timing) {
return V1_2::utils::convert(timing);
}
+nn::GeneralResult<hidl_vec<hidl_handle>> convertSyncFences(
+ const std::vector<nn::SyncFence>& syncFences) {
+ std::vector<nn::SharedHandle> handles;
+ handles.reserve(syncFences.size());
+ std::transform(syncFences.begin(), syncFences.end(), std::back_inserter(handles),
+ [](const nn::SyncFence& syncFence) { return syncFence.getSharedHandle(); });
+ return convert(handles);
+}
+
} // namespace android::hardware::neuralnetworks::V1_3::utils
generated by cgit v1.2.3 (git 2.25.1) at 2025-10-03 10:51:47 +0000