Release 18.05.02
diff --git a/test/Android.mk b/test/Android.mk
index d74afec..97e9a90 100644
--- a/test/Android.mk
+++ b/test/Android.mk
@@ -61,6 +61,13 @@
android.hidl.memory@1.0 \
libOpenCL
+ifeq ($(PLATFORM_VERSION),9)
+# Required to build the 1.0 version of the NN Driver on Android P and later versions,
+# as the 1.0 version of the NN API needs the 1.1 HAL headers to be included regardless.
+LOCAL_SHARED_LIBRARIES+= \
+ android.hardware.neuralnetworks@1.1
+endif
+
LOCAL_MODULE := armnn-driver-tests
LOCAL_MODULE_TAGS := eng optional
diff --git a/test/Concurrent.cpp b/test/Concurrent.cpp
index 16734dc..c2d58bd 100644
--- a/test/Concurrent.cpp
+++ b/test/Concurrent.cpp
@@ -22,7 +22,7 @@
ALOGI("ConcurrentExecute: entry");
auto driver = std::make_unique<ArmnnDriver>(DriverOptions(armnn::Compute::CpuRef));
- Model model = {};
+ V1_0::Model model = {};
// add operands
int32_t actValue = 0;
@@ -37,7 +37,7 @@
// make the fully connected operation
model.operations.resize(1);
- model.operations[0].type = OperationType::FULLY_CONNECTED;
+ model.operations[0].type = V1_0::OperationType::FULLY_CONNECTED;
model.operations[0].inputs = hidl_vec<uint32_t>{0, 1, 2, 3};
model.operations[0].outputs = hidl_vec<uint32_t>{4};
diff --git a/test/Convolution2D.cpp b/test/Convolution2D.cpp
index 90edb41..cc301bc 100644
--- a/test/Convolution2D.cpp
+++ b/test/Convolution2D.cpp
@@ -20,7 +20,7 @@
void PaddingTestImpl(android::nn::PaddingScheme paddingScheme)
{
auto driver = std::make_unique<ArmnnDriver>(DriverOptions(armnn::Compute::CpuRef));
- Model model = {};
+ V1_0::Model model = {};
uint32_t outSize = paddingScheme == android::nn::kPaddingSame ? 2 : 1;
@@ -39,7 +39,7 @@
// make the convolution operation
model.operations.resize(1);
- model.operations[0].type = OperationType::CONV_2D;
+ model.operations[0].type = V1_0::OperationType::CONV_2D;
model.operations[0].inputs = hidl_vec<uint32_t>{0, 1, 2, 3, 4, 5, 6};
model.operations[0].outputs = hidl_vec<uint32_t>{7};
diff --git a/test/DriverTestHelpers.cpp b/test/DriverTestHelpers.cpp
index 5b37192..d2d380a 100644
--- a/test/DriverTestHelpers.cpp
+++ b/test/DriverTestHelpers.cpp
@@ -107,13 +107,13 @@
memcpy(dst, data, size * sizeof(float));
}
-void AddOperand(Model& model, const Operand& op)
+void AddOperand(V1_0::Model& model, const Operand& op)
{
model.operands.resize(model.operands.size() + 1);
model.operands[model.operands.size() - 1] = op;
}
-void AddIntOperand(Model& model, int32_t value)
+void AddIntOperand(V1_0::Model& model, int32_t value)
{
DataLocation location = {};
location.offset = model.operandValues.size();
@@ -131,7 +131,7 @@
AddOperand(model, op);
}
-void AddInputOperand(Model& model, hidl_vec<uint32_t> dimensions)
+void AddInputOperand(V1_0::Model& model, hidl_vec<uint32_t> dimensions)
{
Operand op = {};
op.type = OperandType::TENSOR_FLOAT32;
@@ -144,7 +144,7 @@
model.inputIndexes[model.inputIndexes.size() - 1] = model.operands.size() - 1;
}
-void AddOutputOperand(Model& model, hidl_vec<uint32_t> dimensions)
+void AddOutputOperand(V1_0::Model& model, hidl_vec<uint32_t> dimensions)
{
Operand op = {};
op.type = OperandType::TENSOR_FLOAT32;
@@ -158,7 +158,7 @@
}
-android::sp<IPreparedModel> PrepareModelWithStatus(const Model& model,
+android::sp<IPreparedModel> PrepareModelWithStatus(const V1_0::Model& model,
armnn_driver::ArmnnDriver& driver,
ErrorStatus & prepareStatus,
ErrorStatus expectedStatus)
@@ -176,7 +176,7 @@
return cb->GetPreparedModel();
}
-android::sp<IPreparedModel> PrepareModel(const Model& model,
+android::sp<IPreparedModel> PrepareModel(const V1_0::Model& model,
armnn_driver::ArmnnDriver& driver)
{
ErrorStatus prepareStatus = ErrorStatus::NONE;
diff --git a/test/DriverTestHelpers.hpp b/test/DriverTestHelpers.hpp
index e90f7ec..57541a3 100644
--- a/test/DriverTestHelpers.hpp
+++ b/test/DriverTestHelpers.hpp
@@ -72,9 +72,9 @@
void AddPoolAndSetData(uint32_t size, Request& request, const float* data);
-void AddOperand(Model& model, const Operand& op);
+void AddOperand(V1_0::Model& model, const Operand& op);
-void AddIntOperand(Model& model, int32_t value);
+void AddIntOperand(V1_0::Model& model, int32_t value);
template<typename T>
OperandType TypeToOperandType();
@@ -86,7 +86,7 @@
OperandType TypeToOperandType<int32_t>();
template<typename T>
-void AddTensorOperand(Model& model, hidl_vec<uint32_t> dimensions, T* values)
+void AddTensorOperand(V1_0::Model& model, hidl_vec<uint32_t> dimensions, T* values)
{
uint32_t totalElements = 1;
for (uint32_t dim : dimensions)
@@ -113,14 +113,14 @@
AddOperand(model, op);
}
-void AddInputOperand(Model& model, hidl_vec<uint32_t> dimensions);
+void AddInputOperand(V1_0::Model& model, hidl_vec<uint32_t> dimensions);
-void AddOutputOperand(Model& model, hidl_vec<uint32_t> dimensions);
+void AddOutputOperand(V1_0::Model& model, hidl_vec<uint32_t> dimensions);
-android::sp<IPreparedModel> PrepareModel(const Model& model,
+android::sp<IPreparedModel> PrepareModel(const V1_0::Model& model,
armnn_driver::ArmnnDriver& driver);
-android::sp<IPreparedModel> PrepareModelWithStatus(const Model& model,
+android::sp<IPreparedModel> PrepareModelWithStatus(const V1_0::Model& model,
armnn_driver::ArmnnDriver& driver,
ErrorStatus & prepareStatus,
ErrorStatus expectedStatus=ErrorStatus::NONE);
diff --git a/test/FullyConnected.cpp b/test/FullyConnected.cpp
index ea6c871..4feda30 100644
--- a/test/FullyConnected.cpp
+++ b/test/FullyConnected.cpp
@@ -19,7 +19,7 @@
// but that uses slightly weird dimensions which I don't think we need to support for now
auto driver = std::make_unique<ArmnnDriver>(DriverOptions(armnn::Compute::CpuRef));
- Model model = {};
+ V1_0::Model model = {};
// add operands
int32_t actValue = 0;
@@ -34,7 +34,7 @@
// make the fully connected operation
model.operations.resize(1);
- model.operations[0].type = OperationType::FULLY_CONNECTED;
+ model.operations[0].type = V1_0::OperationType::FULLY_CONNECTED;
model.operations[0].inputs = hidl_vec<uint32_t>{0, 1, 2, 3};
model.operations[0].outputs = hidl_vec<uint32_t>{4};
@@ -90,7 +90,7 @@
sup = supported;
};
- Model model = {};
+ V1_0::Model model = {};
// operands
int32_t actValue = 0;
@@ -113,7 +113,7 @@
model.operations.resize(1);
- model.operations[0].type = OperationType::FULLY_CONNECTED;
+ model.operations[0].type = V1_0::OperationType::FULLY_CONNECTED;
model.operations[0].inputs = hidl_vec<uint32_t>{0,1,2,3};
model.operations[0].outputs = hidl_vec<uint32_t>{4};
@@ -177,7 +177,7 @@
sup = supported;
};
- Model model = {};
+ V1_0::Model model = {};
// operands
int32_t actValue = 0;
@@ -200,7 +200,7 @@
model.operations.resize(1);
- model.operations[0].type = OperationType::FULLY_CONNECTED;
+ model.operations[0].type = V1_0::OperationType::FULLY_CONNECTED;
model.operations[0].inputs = hidl_vec<uint32_t>{0,1,2,3};
model.operations[0].outputs = hidl_vec<uint32_t>{4};
diff --git a/test/GenericLayerTests.cpp b/test/GenericLayerTests.cpp
index 5c6c041..7116f0b 100644
--- a/test/GenericLayerTests.cpp
+++ b/test/GenericLayerTests.cpp
@@ -25,7 +25,7 @@
sup = supported;
};
- Model model1 = {};
+ V1_0::Model model1 = {};
// add operands
int32_t actValue = 0;
@@ -40,14 +40,14 @@
// make a correct fully connected operation
model1.operations.resize(2);
- model1.operations[0].type = OperationType::FULLY_CONNECTED;
+ model1.operations[0].type = V1_0::OperationType::FULLY_CONNECTED;
model1.operations[0].inputs = hidl_vec<uint32_t>{0, 1, 2, 3};
model1.operations[0].outputs = hidl_vec<uint32_t>{4};
// make an incorrect fully connected operation
AddIntOperand(model1, actValue);
AddOutputOperand(model1, hidl_vec<uint32_t>{1, 1});
- model1.operations[1].type = OperationType::FULLY_CONNECTED;
+ model1.operations[1].type = V1_0::OperationType::FULLY_CONNECTED;
model1.operations[1].inputs = hidl_vec<uint32_t>{4};
model1.operations[1].outputs = hidl_vec<uint32_t>{5};
@@ -57,7 +57,7 @@
BOOST_TEST(sup[1] == false);
// Broadcast add/mul are not supported
- Model model2 = {};
+ V1_0::Model model2 = {};
AddInputOperand(model2, hidl_vec<uint32_t>{1, 1, 3, 4});
AddInputOperand(model2, hidl_vec<uint32_t>{4});
@@ -66,11 +66,11 @@
model2.operations.resize(2);
- model2.operations[0].type = OperationType::ADD;
+ model2.operations[0].type = V1_0::OperationType::ADD;
model2.operations[0].inputs = hidl_vec<uint32_t>{0,1};
model2.operations[0].outputs = hidl_vec<uint32_t>{2};
- model2.operations[1].type = OperationType::MUL;
+ model2.operations[1].type = V1_0::OperationType::MUL;
model2.operations[1].inputs = hidl_vec<uint32_t>{0,1};
model2.operations[1].outputs = hidl_vec<uint32_t>{3};
@@ -79,14 +79,14 @@
BOOST_TEST(sup[0] == false);
BOOST_TEST(sup[1] == false);
- Model model3 = {};
+ V1_0::Model model3 = {};
// Add unsupported operation, should return no error but we don't support it
AddInputOperand(model3, hidl_vec<uint32_t>{1, 1, 1, 8});
AddIntOperand(model3, 2);
AddOutputOperand(model3, hidl_vec<uint32_t>{1, 2, 2, 2});
model3.operations.resize(1);
- model3.operations[0].type = OperationType::DEPTH_TO_SPACE;
+ model3.operations[0].type = V1_0::OperationType::DEPTH_TO_SPACE;
model1.operations[0].inputs = hidl_vec<uint32_t>{0, 1};
model3.operations[0].outputs = hidl_vec<uint32_t>{2};
@@ -95,10 +95,10 @@
BOOST_TEST(sup[0] == false);
// Add invalid operation
- Model model4 = {};
+ V1_0::Model model4 = {};
AddIntOperand(model4, 0);
model4.operations.resize(1);
- model4.operations[0].type = static_cast<OperationType>(100);
+ model4.operations[0].type = static_cast<V1_0::OperationType>(100);
model4.operations[0].outputs = hidl_vec<uint32_t>{0};
driver->getSupportedOperations(model4, cb);
@@ -121,7 +121,7 @@
sup = supported;
};
- Model model = {};
+ V1_0::Model model = {};
// operands
int32_t actValue = 0;
@@ -146,17 +146,17 @@
model.operations.resize(3);
// unsupported
- model.operations[0].type = OperationType::ADD;
+ model.operations[0].type = V1_0::OperationType::ADD;
model.operations[0].inputs = hidl_vec<uint32_t>{0,1};
model.operations[0].outputs = hidl_vec<uint32_t>{2};
// supported
- model.operations[1].type = OperationType::FULLY_CONNECTED;
+ model.operations[1].type = V1_0::OperationType::FULLY_CONNECTED;
model.operations[1].inputs = hidl_vec<uint32_t>{3, 4, 5, 6};
model.operations[1].outputs = hidl_vec<uint32_t>{7};
// unsupported
- model.operations[2].type = OperationType::MUL;
+ model.operations[2].type = V1_0::OperationType::MUL;
model.operations[2].inputs = hidl_vec<uint32_t>{0,1};
model.operations[2].outputs = hidl_vec<uint32_t>{8};
@@ -184,7 +184,7 @@
sup = supported;
};
- Model model = {};
+ V1_0::Model model = {};
model.pools = hidl_vec<hidl_memory>{hidl_memory("Unsuported hidl memory type", nullptr, 0)};
diff --git a/test/Merger.cpp b/test/Merger.cpp
index 6c069a8..4825360 100644
--- a/test/Merger.cpp
+++ b/test/Merger.cpp
@@ -25,7 +25,7 @@
ErrorStatus expectedExecStatus=ErrorStatus::NONE)
{
std::unique_ptr<ArmnnDriver> driver = std::make_unique<ArmnnDriver>(DriverOptions(armnn::Compute::CpuRef));
- Model model{};
+ V1_0::Model model{};
hidl_vec<uint32_t> modelInputIds;
modelInputIds.resize(inputs.size()+1);
@@ -40,7 +40,7 @@
// make the concat operation
model.operations.resize(1);
- model.operations[0].type = OperationType::CONCATENATION;
+ model.operations[0].type = V1_0::OperationType::CONCATENATION;
model.operations[0].inputs = modelInputIds;
model.operations[0].outputs = hidl_vec<uint32_t>{static_cast<uint32_t>(inputs.size()+1)};
diff --git a/test/Tests.cpp b/test/Tests.cpp
index 37aece7..3fa8e12 100644
--- a/test/Tests.cpp
+++ b/test/Tests.cpp
@@ -31,9 +31,9 @@
auto driver = std::make_unique<ArmnnDriver>(DriverOptions(armnn::Compute::CpuRef));
ErrorStatus error;
- Capabilities cap;
+ V1_0::Capabilities cap;
- ArmnnDriver::getCapabilities_cb cb = [&](ErrorStatus status, const Capabilities& capabilities)
+ ArmnnDriver::getCapabilities_cb cb = [&](ErrorStatus status, const V1_0::Capabilities& capabilities)
{
error = status;
cap = capabilities;
diff --git a/test/UtilsTests.cpp b/test/UtilsTests.cpp
index b429920..e7e6cde 100644
--- a/test/UtilsTests.cpp
+++ b/test/UtilsTests.cpp
@@ -95,7 +95,7 @@
}
std::string m_RequestInputsAndOutputsDumpDir;
- Model m_Model;
+ V1_0::Model m_Model;
private:
std::string m_FileName;