Move NN_TRY macro out of struct initialization
NNAPI NN_TRY macros use Statement Expressions (a GNU extension) to
propagate errors. However, a "return" statement in a Statement
Expression can lead to memory leaks when the Statement Expression is
being used to initialize a member of a struct. Specifically, when one
member of a struct is already initialized, and a Statement Expression
used to initialize a subsequent member early-returns, the previously
initialized members will not have their destructors called.
This CL moves any NN_TRY macro out of struct initialization to avoid any
potential memory leaks.
Bug: 230500484
Test: mma
Test: presubmit
Change-Id: I3493fd4764f8eacc86750e6414e62bc891abaccd
Merged-In: I3493fd4764f8eacc86750e6414e62bc891abaccd
diff --git a/neuralnetworks/1.0/utils/src/Conversions.cpp b/neuralnetworks/1.0/utils/src/Conversions.cpp
index daa10fd..d98fef0 100644
--- a/neuralnetworks/1.0/utils/src/Conversions.cpp
+++ b/neuralnetworks/1.0/utils/src/Conversions.cpp
@@ -110,8 +110,9 @@
return NN_ERROR() << "Unable to convert invalid ashmem memory object with "
<< memory.handle()->numInts << " numInts, but expected 0";
}
+ auto fd = NN_TRY(nn::dupFd(memory.handle()->data[0]));
auto handle = nn::Memory::Ashmem{
- .fd = NN_TRY(nn::dupFd(memory.handle()->data[0])),
+ .fd = std::move(fd),
.size = static_cast<size_t>(memory.size()),
};
return std::make_shared<const nn::Memory>(nn::Memory{.handle = std::move(handle)});
@@ -137,12 +138,13 @@
}
if (memory.name() != "hardware_buffer_blob") {
- auto handle = nn::Memory::Unknown{
- .handle = NN_TRY(unknownHandleFromNativeHandle(memory.handle())),
+ auto handle = NN_TRY(unknownHandleFromNativeHandle(memory.handle()));
+ auto unknown = nn::Memory::Unknown{
+ .handle = std::move(handle),
.size = static_cast<size_t>(memory.size()),
.name = memory.name(),
};
- return std::make_shared<const nn::Memory>(nn::Memory{.handle = std::move(handle)});
+ return std::make_shared<const nn::Memory>(nn::Memory{.handle = std::move(unknown)});
}
#ifdef __ANDROID__
@@ -245,19 +247,23 @@
}
GeneralResult<Operand> unvalidatedConvert(const hal::V1_0::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));
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)),
+ .lifetime = lifetime,
+ .location = location,
};
}
GeneralResult<Operation> unvalidatedConvert(const hal::V1_0::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,
};
@@ -298,26 +304,30 @@
}
}
+ auto operands = NN_TRY(unvalidatedConvert(model.operands));
auto main = Model::Subgraph{
- .operands = NN_TRY(unvalidatedConvert(model.operands)),
+ .operands = std::move(operands),
.operations = std::move(operations),
.inputIndexes = model.inputIndexes,
.outputIndexes = model.outputIndexes,
};
+ auto operandValues = NN_TRY(unvalidatedConvert(model.operandValues));
+ auto pools = NN_TRY(unvalidatedConvert(model.pools));
return Model{
.main = std::move(main),
- .operandValues = NN_TRY(unvalidatedConvert(model.operandValues)),
- .pools = NN_TRY(unvalidatedConvert(model.pools)),
+ .operandValues = std::move(operandValues),
+ .pools = std::move(pools),
};
}
GeneralResult<Request::Argument> unvalidatedConvert(const hal::V1_0::RequestArgument& argument) {
const auto lifetime = argument.hasNoValue ? Request::Argument::LifeTime::NO_VALUE
: Request::Argument::LifeTime::POOL;
+ const auto location = NN_TRY(unvalidatedConvert(argument.location));
return Request::Argument{
.lifetime = lifetime,
- .location = NN_TRY(unvalidatedConvert(argument.location)),
+ .location = location,
.dimensions = argument.dimensions,
};
}
@@ -328,9 +338,11 @@
pools.reserve(memories.size());
std::move(memories.begin(), memories.end(), std::back_inserter(pools));
+ auto inputs = NN_TRY(unvalidatedConvert(request.inputs));
+ auto outputs = NN_TRY(unvalidatedConvert(request.outputs));
return Request{
- .inputs = NN_TRY(unvalidatedConvert(request.inputs)),
- .outputs = NN_TRY(unvalidatedConvert(request.outputs)),
+ .inputs = std::move(inputs),
+ .outputs = std::move(outputs),
.pools = std::move(pools),
};
}
@@ -500,11 +512,13 @@
}
nn::GeneralResult<Capabilities> unvalidatedConvert(const nn::Capabilities& capabilities) {
+ const auto float32Performance = NN_TRY(unvalidatedConvert(
+ capabilities.operandPerformance.lookup(nn::OperandType::TENSOR_FLOAT32)));
+ const auto quantized8Performance = NN_TRY(unvalidatedConvert(
+ capabilities.operandPerformance.lookup(nn::OperandType::TENSOR_QUANT8_ASYMM)));
return Capabilities{
- .float32Performance = NN_TRY(unvalidatedConvert(
- capabilities.operandPerformance.lookup(nn::OperandType::TENSOR_FLOAT32))),
- .quantized8Performance = NN_TRY(unvalidatedConvert(
- capabilities.operandPerformance.lookup(nn::OperandType::TENSOR_QUANT8_ASYMM))),
+ .float32Performance = float32Performance,
+ .quantized8Performance = quantized8Performance,
};
}
@@ -517,20 +531,24 @@
}
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));
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)),
+ .lifetime = lifetime,
+ .location = location,
};
}
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,
};
@@ -572,13 +590,16 @@
operands[i].numberOfConsumers = numberOfConsumers[i];
}
+ auto operations = NN_TRY(unvalidatedConvert(model.main.operations));
+ auto operandValues = NN_TRY(unvalidatedConvert(model.operandValues));
+ auto pools = NN_TRY(unvalidatedConvert(model.pools));
return Model{
.operands = std::move(operands),
- .operations = NN_TRY(unvalidatedConvert(model.main.operations)),
+ .operations = std::move(operations),
.inputIndexes = model.main.inputIndexes,
.outputIndexes = model.main.outputIndexes,
- .operandValues = NN_TRY(unvalidatedConvert(model.operandValues)),
- .pools = NN_TRY(unvalidatedConvert(model.pools)),
+ .operandValues = std::move(operandValues),
+ .pools = std::move(pools),
};
}
@@ -589,9 +610,10 @@
<< "Request cannot be unvalidatedConverted because it contains pointer-based memory";
}
const bool hasNoValue = requestArgument.lifetime == nn::Request::Argument::LifeTime::NO_VALUE;
+ const auto location = NN_TRY(unvalidatedConvert(requestArgument.location));
return RequestArgument{
.hasNoValue = hasNoValue,
- .location = NN_TRY(unvalidatedConvert(requestArgument.location)),
+ .location = location,
.dimensions = requestArgument.dimensions,
};
}
@@ -606,10 +628,13 @@
<< "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),
};
}
diff --git a/neuralnetworks/1.1/utils/src/Conversions.cpp b/neuralnetworks/1.1/utils/src/Conversions.cpp
index 5bdbe31..887c8ec 100644
--- a/neuralnetworks/1.1/utils/src/Conversions.cpp
+++ b/neuralnetworks/1.1/utils/src/Conversions.cpp
@@ -88,8 +88,9 @@
}
GeneralResult<Operation> unvalidatedConvert(const hal::V1_1::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,
};
@@ -110,17 +111,20 @@
}
}
+ auto operands = NN_TRY(unvalidatedConvert(model.operands));
auto main = Model::Subgraph{
- .operands = NN_TRY(unvalidatedConvert(model.operands)),
+ .operands = std::move(operands),
.operations = std::move(operations),
.inputIndexes = model.inputIndexes,
.outputIndexes = model.outputIndexes,
};
+ auto operandValues = NN_TRY(unvalidatedConvert(model.operandValues));
+ auto pools = NN_TRY(unvalidatedConvert(model.pools));
return Model{
.main = std::move(main),
- .operandValues = NN_TRY(unvalidatedConvert(model.operandValues)),
- .pools = NN_TRY(unvalidatedConvert(model.pools)),
+ .operandValues = std::move(operandValues),
+ .pools = std::move(pools),
.relaxComputationFloat32toFloat16 = model.relaxComputationFloat32toFloat16,
};
}
@@ -195,19 +199,23 @@
}
nn::GeneralResult<Capabilities> unvalidatedConvert(const nn::Capabilities& capabilities) {
+ const auto float32Performance = NN_TRY(unvalidatedConvert(
+ capabilities.operandPerformance.lookup(nn::OperandType::TENSOR_FLOAT32)));
+ const auto quanitized8Performance = NN_TRY(unvalidatedConvert(
+ capabilities.operandPerformance.lookup(nn::OperandType::TENSOR_QUANT8_ASYMM)));
+ const auto relaxedFloat32toFloat16Performance =
+ NN_TRY(unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceTensor));
return Capabilities{
- .float32Performance = NN_TRY(unvalidatedConvert(
- capabilities.operandPerformance.lookup(nn::OperandType::TENSOR_FLOAT32))),
- .quantized8Performance = NN_TRY(unvalidatedConvert(
- capabilities.operandPerformance.lookup(nn::OperandType::TENSOR_QUANT8_ASYMM))),
- .relaxedFloat32toFloat16Performance = NN_TRY(
- unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceTensor)),
+ .float32Performance = float32Performance,
+ .quantized8Performance = quanitized8Performance,
+ .relaxedFloat32toFloat16Performance = relaxedFloat32toFloat16Performance,
};
}
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,
};
@@ -229,13 +237,16 @@
operands[i].numberOfConsumers = numberOfConsumers[i];
}
+ auto operations = NN_TRY(unvalidatedConvert(model.main.operations));
+ auto operandValues = NN_TRY(unvalidatedConvert(model.operandValues));
+ auto pools = NN_TRY(unvalidatedConvert(model.pools));
return Model{
.operands = std::move(operands),
- .operations = NN_TRY(unvalidatedConvert(model.main.operations)),
+ .operations = std::move(operations),
.inputIndexes = model.main.inputIndexes,
.outputIndexes = model.main.outputIndexes,
- .operandValues = NN_TRY(unvalidatedConvert(model.operandValues)),
- .pools = NN_TRY(unvalidatedConvert(model.pools)),
+ .operandValues = std::move(operandValues),
+ .pools = std::move(pools),
.relaxComputationFloat32toFloat16 = model.relaxComputationFloat32toFloat16,
};
}
diff --git a/neuralnetworks/1.2/utils/src/Conversions.cpp b/neuralnetworks/1.2/utils/src/Conversions.cpp
index 62ec2ed..78d71cf 100644
--- a/neuralnetworks/1.2/utils/src/Conversions.cpp
+++ b/neuralnetworks/1.2/utils/src/Conversions.cpp
@@ -131,15 +131,18 @@
GeneralResult<Capabilities::OperandPerformance> unvalidatedConvert(
const hal::V1_2::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_2::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,
};
@@ -154,14 +157,18 @@
}
GeneralResult<Operand> unvalidatedConvert(const hal::V1_2::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),
};
}
@@ -196,19 +203,23 @@
}
}
+ auto operands = NN_TRY(unvalidatedConvert(model.operands));
auto main = Model::Subgraph{
- .operands = NN_TRY(unvalidatedConvert(model.operands)),
+ .operands = std::move(operands),
.operations = std::move(operations),
.inputIndexes = model.inputIndexes,
.outputIndexes = model.outputIndexes,
};
+ auto operandValues = NN_TRY(unvalidatedConvert(model.operandValues));
+ auto pools = NN_TRY(unvalidatedConvert(model.pools));
+ auto extensionNameToPrefix = NN_TRY(unvalidatedConvert(model.extensionNameToPrefix));
return Model{
.main = std::move(main),
- .operandValues = NN_TRY(unvalidatedConvert(model.operandValues)),
- .pools = NN_TRY(unvalidatedConvert(model.pools)),
+ .operandValues = std::move(operandValues),
+ .pools = std::move(pools),
.relaxComputationFloat32toFloat16 = model.relaxComputationFloat32toFloat16,
- .extensionNameToPrefix = NN_TRY(unvalidatedConvert(model.extensionNameToPrefix)),
+ .extensionNameToPrefix = std::move(extensionNameToPrefix),
};
}
@@ -248,9 +259,10 @@
}
GeneralResult<Extension> unvalidatedConvert(const hal::V1_2::Extension& extension) {
+ auto operandTypes = NN_TRY(unvalidatedConvert(extension.operandTypes));
return Extension{
.name = extension.name,
- .operandTypes = NN_TRY(unvalidatedConvert(extension.operandTypes)),
+ .operandTypes = std::move(operandTypes),
};
}
@@ -406,35 +418,41 @@
}
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));
return Capabilities{
- .relaxedFloat32toFloat16PerformanceScalar = NN_TRY(
- unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceScalar)),
- .relaxedFloat32toFloat16PerformanceTensor = NN_TRY(
- unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceTensor)),
- .operandPerformance = NN_TRY(unvalidatedConvert(operandPerformance)),
+ .relaxedFloat32toFloat16PerformanceScalar = relaxedFloat32toFloat16PerformanceScalar,
+ .relaxedFloat32toFloat16PerformanceTensor = relaxedFloat32toFloat16PerformanceTensor,
+ .operandPerformance = std::move(operandPerformance),
};
}
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,
};
@@ -449,15 +467,19 @@
}
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),
};
}
@@ -482,15 +504,19 @@
operands[i].numberOfConsumers = numberOfConsumers[i];
}
+ auto operations = NN_TRY(unvalidatedConvert(model.main.operations));
+ auto operandValues = NN_TRY(unvalidatedConvert(model.operandValues));
+ auto pools = NN_TRY(unvalidatedConvert(model.pools));
+ auto extensionNameToPrefix = NN_TRY(unvalidatedConvert(model.extensionNameToPrefix));
return Model{
.operands = std::move(operands),
- .operations = NN_TRY(unvalidatedConvert(model.main.operations)),
+ .operations = std::move(operations),
.inputIndexes = model.main.inputIndexes,
.outputIndexes = model.main.outputIndexes,
- .operandValues = NN_TRY(unvalidatedConvert(model.operandValues)),
- .pools = NN_TRY(unvalidatedConvert(model.pools)),
+ .operandValues = std::move(operandValues),
+ .pools = std::move(pools),
.relaxComputationFloat32toFloat16 = model.relaxComputationFloat32toFloat16,
- .extensionNameToPrefix = NN_TRY(unvalidatedConvert(model.extensionNameToPrefix)),
+ .extensionNameToPrefix = std::move(extensionNameToPrefix),
};
}
@@ -524,9 +550,10 @@
}
nn::GeneralResult<Extension> unvalidatedConvert(const nn::Extension& extension) {
+ auto operandTypes = NN_TRY(unvalidatedConvert(extension.operandTypes));
return Extension{
.name = extension.name,
- .operandTypes = NN_TRY(unvalidatedConvert(extension.operandTypes)),
+ .operandTypes = std::move(operandTypes),
};
}
diff --git a/neuralnetworks/1.3/utils/src/Conversions.cpp b/neuralnetworks/1.3/utils/src/Conversions.cpp
index 09e9d80..4eeb414 100644
--- a/neuralnetworks/1.3/utils/src/Conversions.cpp
+++ b/neuralnetworks/1.3/utils/src/Conversions.cpp
@@ -133,28 +133,35 @@
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,
};
@@ -166,25 +173,34 @@
}
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),
};
}
@@ -204,8 +220,9 @@
}
}
+ 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,
@@ -225,10 +242,13 @@
}
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),
};
}
@@ -463,37 +483,45 @@
}
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,
};
@@ -509,15 +537,19 @@
}
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),
};
}
@@ -527,13 +559,18 @@
<< "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),
};
}
@@ -548,9 +585,10 @@
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,
};
@@ -574,10 +612,13 @@
<< "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),
};
}
diff --git a/neuralnetworks/aidl/utils/src/Conversions.cpp b/neuralnetworks/aidl/utils/src/Conversions.cpp
index 081e3d7..47c72b4 100644
--- a/neuralnetworks/aidl/utils/src/Conversions.cpp
+++ b/neuralnetworks/aidl/utils/src/Conversions.cpp
@@ -177,22 +177,28 @@
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 aidl_hal::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,
};
}
@@ -228,10 +234,13 @@
}
GeneralResult<Operation> unvalidatedConvert(const aidl_hal::Operation& operation) {
+ const auto type = NN_TRY(unvalidatedConvert(operation.type));
+ auto inputs = NN_TRY(toUnsigned(operation.inputs));
+ auto outputs = NN_TRY(toUnsigned(operation.outputs));
return Operation{
- .type = NN_TRY(unvalidatedConvert(operation.type)),
- .inputs = NN_TRY(toUnsigned(operation.inputs)),
- .outputs = NN_TRY(toUnsigned(operation.outputs)),
+ .type = type,
+ .inputs = std::move(inputs),
+ .outputs = std::move(outputs),
};
}
@@ -241,14 +250,19 @@
}
GeneralResult<Operand> unvalidatedConvert(const aidl_hal::Operand& operand) {
+ const auto type = NN_TRY(unvalidatedConvert(operand.type));
+ auto dimensions = NN_TRY(toUnsigned(operand.dimensions));
+ 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)),
- .dimensions = NN_TRY(toUnsigned(operand.dimensions)),
+ .type = type,
+ .dimensions = std::move(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),
};
}
@@ -280,22 +294,31 @@
}
GeneralResult<Model> unvalidatedConvert(const aidl_hal::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),
};
}
GeneralResult<Model::Subgraph> unvalidatedConvert(const aidl_hal::Subgraph& subgraph) {
+ auto operands = NN_TRY(unvalidatedConvert(subgraph.operands));
+ auto operations = NN_TRY(unvalidatedConvert(subgraph.operations));
+ auto inputIndexes = NN_TRY(toUnsigned(subgraph.inputIndexes));
+ auto outputIndexes = NN_TRY(toUnsigned(subgraph.outputIndexes));
return Model::Subgraph{
- .operands = NN_TRY(unvalidatedConvert(subgraph.operands)),
- .operations = NN_TRY(unvalidatedConvert(subgraph.operations)),
- .inputIndexes = NN_TRY(toUnsigned(subgraph.inputIndexes)),
- .outputIndexes = NN_TRY(toUnsigned(subgraph.outputIndexes)),
+ .operands = std::move(operands),
+ .operations = std::move(operations),
+ .inputIndexes = std::move(inputIndexes),
+ .outputIndexes = std::move(outputIndexes),
};
}
@@ -308,9 +331,10 @@
}
GeneralResult<Extension> unvalidatedConvert(const aidl_hal::Extension& extension) {
+ auto operandTypes = NN_TRY(unvalidatedConvert(extension.operandTypes));
return Extension{
.name = extension.name,
- .operandTypes = NN_TRY(unvalidatedConvert(extension.operandTypes)),
+ .operandTypes = std::move(operandTypes),
};
}
@@ -326,8 +350,9 @@
}
GeneralResult<OutputShape> unvalidatedConvert(const aidl_hal::OutputShape& outputShape) {
+ auto dimensions = NN_TRY(toUnsigned(outputShape.dimensions));
return OutputShape{
- .dimensions = NN_TRY(toUnsigned(outputShape.dimensions)),
+ .dimensions = std::move(dimensions),
.isSufficient = outputShape.isSufficient,
};
}
@@ -346,8 +371,9 @@
return NN_ERROR() << "Memory: size must be <= std::numeric_limits<size_t>::max()";
}
+ auto fd = NN_TRY(dupFd(ashmem.fd.get()));
auto handle = Memory::Ashmem{
- .fd = NN_TRY(dupFd(ashmem.fd.get())),
+ .fd = std::move(fd),
.size = static_cast<size_t>(ashmem.size),
};
return std::make_shared<const Memory>(Memory{.handle = std::move(handle)});
@@ -426,7 +452,8 @@
}
GeneralResult<BufferDesc> unvalidatedConvert(const aidl_hal::BufferDesc& bufferDesc) {
- return BufferDesc{.dimensions = NN_TRY(toUnsigned(bufferDesc.dimensions))};
+ auto dimensions = NN_TRY(toUnsigned(bufferDesc.dimensions));
+ return BufferDesc{.dimensions = std::move(dimensions)};
}
GeneralResult<BufferRole> unvalidatedConvert(const aidl_hal::BufferRole& bufferRole) {
@@ -440,20 +467,25 @@
}
GeneralResult<Request> unvalidatedConvert(const aidl_hal::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),
};
}
GeneralResult<Request::Argument> unvalidatedConvert(const aidl_hal::RequestArgument& argument) {
const auto lifetime = argument.hasNoValue ? Request::Argument::LifeTime::NO_VALUE
: Request::Argument::LifeTime::POOL;
+ const auto location = NN_TRY(unvalidatedConvert(argument.location));
+ auto dimensions = NN_TRY(toUnsigned(argument.dimensions));
return Request::Argument{
.lifetime = lifetime,
- .location = NN_TRY(unvalidatedConvert(argument.location)),
- .dimensions = NN_TRY(toUnsigned(argument.dimensions)),
+ .location = location,
+ .dimensions = std::move(dimensions),
};
}
@@ -720,8 +752,9 @@
nn::GeneralResult<OperandPerformance> unvalidatedConvert(
const nn::Capabilities::OperandPerformance& operandPerformance) {
- return OperandPerformance{.type = NN_TRY(unvalidatedConvert(operandPerformance.type)),
- .info = NN_TRY(unvalidatedConvert(operandPerformance.info))};
+ const auto type = NN_TRY(unvalidatedConvert(operandPerformance.type));
+ const auto info = NN_TRY(unvalidatedConvert(operandPerformance.info));
+ return OperandPerformance{.type = type, .info = info};
}
nn::GeneralResult<std::vector<OperandPerformance>> unvalidatedConvert(
@@ -788,7 +821,8 @@
}
nn::GeneralResult<BufferDesc> unvalidatedConvert(const nn::BufferDesc& bufferDesc) {
- return BufferDesc{.dimensions = NN_TRY(toSigned(bufferDesc.dimensions))};
+ auto dimensions = NN_TRY(toSigned(bufferDesc.dimensions));
+ return BufferDesc{.dimensions = std::move(dimensions)};
}
nn::GeneralResult<BufferRole> unvalidatedConvert(const nn::BufferRole& bufferRole) {
@@ -847,7 +881,8 @@
}
nn::GeneralResult<OutputShape> unvalidatedConvert(const nn::OutputShape& outputShape) {
- return OutputShape{.dimensions = NN_TRY(toSigned(outputShape.dimensions)),
+ auto dimensions = NN_TRY(toSigned(outputShape.dimensions));
+ return OutputShape{.dimensions = std::move(dimensions),
.isSufficient = outputShape.isSufficient};
}
@@ -915,14 +950,19 @@
}
nn::GeneralResult<Operand> unvalidatedConvert(const nn::Operand& operand) {
+ const auto type = NN_TRY(unvalidatedConvert(operand.type));
+ auto dimensions = NN_TRY(toSigned(operand.dimensions));
+ 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)),
- .dimensions = NN_TRY(toSigned(operand.dimensions)),
+ .type = type,
+ .dimensions = std::move(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),
};
}
@@ -934,19 +974,26 @@
}
nn::GeneralResult<Operation> unvalidatedConvert(const nn::Operation& operation) {
+ const auto type = NN_TRY(unvalidatedConvert(operation.type));
+ auto inputs = NN_TRY(toSigned(operation.inputs));
+ auto outputs = NN_TRY(toSigned(operation.outputs));
return Operation{
- .type = NN_TRY(unvalidatedConvert(operation.type)),
- .inputs = NN_TRY(toSigned(operation.inputs)),
- .outputs = NN_TRY(toSigned(operation.outputs)),
+ .type = type,
+ .inputs = std::move(inputs),
+ .outputs = std::move(outputs),
};
}
nn::GeneralResult<Subgraph> unvalidatedConvert(const nn::Model::Subgraph& subgraph) {
+ auto operands = NN_TRY(unvalidatedConvert(subgraph.operands));
+ auto operations = NN_TRY(unvalidatedConvert(subgraph.operations));
+ auto inputIndexes = NN_TRY(toSigned(subgraph.inputIndexes));
+ auto outputIndexes = NN_TRY(toSigned(subgraph.outputIndexes));
return Subgraph{
- .operands = NN_TRY(unvalidatedConvert(subgraph.operands)),
- .operations = NN_TRY(unvalidatedConvert(subgraph.operations)),
- .inputIndexes = NN_TRY(toSigned(subgraph.inputIndexes)),
- .outputIndexes = NN_TRY(toSigned(subgraph.outputIndexes)),
+ .operands = std::move(operands),
+ .operations = std::move(operations),
+ .inputIndexes = std::move(inputIndexes),
+ .outputIndexes = std::move(outputIndexes),
};
}
@@ -969,13 +1016,18 @@
<< "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),
};
}
@@ -989,10 +1041,13 @@
<< "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),
};
}
@@ -1003,10 +1058,12 @@
<< "Request cannot be unvalidatedConverted because it contains pointer-based memory";
}
const bool hasNoValue = requestArgument.lifetime == nn::Request::Argument::LifeTime::NO_VALUE;
+ const auto location = NN_TRY(unvalidatedConvert(requestArgument.location));
+ auto dimensions = NN_TRY(toSigned(requestArgument.dimensions));
return RequestArgument{
.hasNoValue = hasNoValue,
- .location = NN_TRY(unvalidatedConvert(requestArgument.location)),
- .dimensions = NN_TRY(toSigned(requestArgument.dimensions)),
+ .location = location,
+ .dimensions = std::move(dimensions),
};
}
@@ -1033,9 +1090,11 @@
}
nn::GeneralResult<Timing> unvalidatedConvert(const nn::Timing& timing) {
+ const auto timeOnDeviceNs = NN_TRY(unvalidatedConvert(timing.timeOnDevice));
+ const auto timeInDriverNs = NN_TRY(unvalidatedConvert(timing.timeInDriver));
return Timing{
- .timeOnDeviceNs = NN_TRY(unvalidatedConvert(timing.timeOnDevice)),
- .timeInDriverNs = NN_TRY(unvalidatedConvert(timing.timeInDriver)),
+ .timeOnDeviceNs = timeOnDeviceNs,
+ .timeInDriverNs = timeInDriverNs,
};
}
@@ -1064,20 +1123,25 @@
}
nn::GeneralResult<Capabilities> unvalidatedConvert(const nn::Capabilities& capabilities) {
+ const auto relaxedFloat32toFloat16PerformanceTensor =
+ NN_TRY(unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceTensor));
+ const auto relaxedFloat32toFloat16PerformanceScalar =
+ NN_TRY(unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceScalar));
+ auto operandPerformance = NN_TRY(unvalidatedConvert(capabilities.operandPerformance));
+ const auto ifPerformance = NN_TRY(unvalidatedConvert(capabilities.ifPerformance));
+ const auto whilePerformance = NN_TRY(unvalidatedConvert(capabilities.whilePerformance));
return Capabilities{
- .relaxedFloat32toFloat16PerformanceTensor = NN_TRY(
- unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceTensor)),
- .relaxedFloat32toFloat16PerformanceScalar = NN_TRY(
- unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceScalar)),
- .operandPerformance = NN_TRY(unvalidatedConvert(capabilities.operandPerformance)),
- .ifPerformance = NN_TRY(unvalidatedConvert(capabilities.ifPerformance)),
- .whilePerformance = NN_TRY(unvalidatedConvert(capabilities.whilePerformance)),
+ .relaxedFloat32toFloat16PerformanceTensor = relaxedFloat32toFloat16PerformanceTensor,
+ .relaxedFloat32toFloat16PerformanceScalar = relaxedFloat32toFloat16PerformanceScalar,
+ .operandPerformance = std::move(operandPerformance),
+ .ifPerformance = ifPerformance,
+ .whilePerformance = whilePerformance,
};
}
nn::GeneralResult<Extension> unvalidatedConvert(const nn::Extension& extension) {
- return Extension{.name = extension.name,
- .operandTypes = NN_TRY(unvalidatedConvert(extension.operandTypes))};
+ auto operandTypes = NN_TRY(unvalidatedConvert(extension.operandTypes));
+ return Extension{.name = extension.name, .operandTypes = std::move(operandTypes)};
}
#ifdef NN_AIDL_V4_OR_ABOVE
nn::GeneralResult<TokenValuePair> unvalidatedConvert(const nn::TokenValuePair& tokenValuePair) {
diff --git a/neuralnetworks/aidl/utils/src/Utils.cpp b/neuralnetworks/aidl/utils/src/Utils.cpp
index 76a0b07..f9b4f6e 100644
--- a/neuralnetworks/aidl/utils/src/Utils.cpp
+++ b/neuralnetworks/aidl/utils/src/Utils.cpp
@@ -51,8 +51,9 @@
}
nn::GeneralResult<common::NativeHandle> clone(const common::NativeHandle& handle) {
+ auto fds = NN_TRY(cloneVec(handle.fds));
return common::NativeHandle{
- .fds = NN_TRY(cloneVec(handle.fds)),
+ .fds = std::move(fds),
.ints = handle.ints,
};
}
@@ -63,29 +64,32 @@
switch (memory.getTag()) {
case Memory::Tag::ashmem: {
const auto& ashmem = memory.get<Memory::Tag::ashmem>();
+ auto fd = NN_TRY(clone(ashmem.fd));
auto handle = common::Ashmem{
- .fd = NN_TRY(clone(ashmem.fd)),
+ .fd = std::move(fd),
.size = ashmem.size,
};
return Memory::make<Memory::Tag::ashmem>(std::move(handle));
}
case Memory::Tag::mappableFile: {
const auto& memFd = memory.get<Memory::Tag::mappableFile>();
+ auto fd = NN_TRY(clone(memFd.fd));
auto handle = common::MappableFile{
.length = memFd.length,
.prot = memFd.prot,
- .fd = NN_TRY(clone(memFd.fd)),
+ .fd = std::move(fd),
.offset = memFd.offset,
};
return Memory::make<Memory::Tag::mappableFile>(std::move(handle));
}
case Memory::Tag::hardwareBuffer: {
const auto& hardwareBuffer = memory.get<Memory::Tag::hardwareBuffer>();
- auto handle = graphics::common::HardwareBuffer{
+ auto handle = NN_TRY(clone(hardwareBuffer.handle));
+ auto ahwbHandle = graphics::common::HardwareBuffer{
.description = hardwareBuffer.description,
- .handle = NN_TRY(clone(hardwareBuffer.handle)),
+ .handle = std::move(handle),
};
- return Memory::make<Memory::Tag::hardwareBuffer>(std::move(handle));
+ return Memory::make<Memory::Tag::hardwareBuffer>(std::move(ahwbHandle));
}
}
return (NN_ERROR() << "Unrecognized Memory::Tag: " << underlyingType(memory.getTag()))
@@ -109,19 +113,21 @@
}
nn::GeneralResult<Request> clone(const Request& request) {
+ auto pools = NN_TRY(clone(request.pools));
return Request{
.inputs = request.inputs,
.outputs = request.outputs,
- .pools = NN_TRY(clone(request.pools)),
+ .pools = std::move(pools),
};
}
nn::GeneralResult<Model> clone(const Model& model) {
+ auto pools = NN_TRY(clone(model.pools));
return Model{
.main = model.main,
.referenced = model.referenced,
.operandValues = model.operandValues,
- .pools = NN_TRY(clone(model.pools)),
+ .pools = std::move(pools),
.relaxComputationFloat32toFloat16 = model.relaxComputationFloat32toFloat16,
.extensionNameToPrefix = model.extensionNameToPrefix,
};