IVGCVSW-2911 Android Q compatibility code updates
* Updates on test classes.
Change-Id: I52e11a1d97d02c23e0a33e4e128dc43a4a95b5bc
Signed-off-by: Sadik Armagan <sadik.armagan@arm.com>
diff --git a/test/Concurrent.cpp b/test/Concurrent.cpp
index 55a1a39..0848a88 100644
--- a/test/Concurrent.cpp
+++ b/test/Concurrent.cpp
@@ -45,7 +45,7 @@
// make the prepared models
const size_t maxRequests = 5;
- android::sp<IPreparedModel> preparedModels[maxRequests];
+ android::sp<V1_0::IPreparedModel> preparedModels[maxRequests];
for (size_t i = 0; i < maxRequests; ++i)
{
preparedModels[i] = PrepareModel(model, *driver);
diff --git a/test/Convolution2D.hpp b/test/Convolution2D.hpp
index ff417d9..3fda29b 100644
--- a/test/Convolution2D.hpp
+++ b/test/Convolution2D.hpp
@@ -59,7 +59,7 @@
// make the prepared model
SetModelFp16Flag(model, fp16Enabled);
- android::sp<IPreparedModel> preparedModel = PrepareModel(model, *driver);
+ android::sp<V1_0::IPreparedModel> preparedModel = PrepareModel(model, *driver);
// construct the request
DataLocation inloc = {};
diff --git a/test/DriverTestHelpers.cpp b/test/DriverTestHelpers.cpp
index 3bc0a20..7a6b780 100644
--- a/test/DriverTestHelpers.cpp
+++ b/test/DriverTestHelpers.cpp
@@ -54,7 +54,7 @@
}
Return<void> PreparedModelCallback::notify(ErrorStatus status,
- const android::sp<IPreparedModel>& preparedModel)
+ const android::sp<V1_0::IPreparedModel>& preparedModel)
{
m_ErrorStatus = status;
m_PreparedModel = preparedModel;
@@ -109,10 +109,10 @@
memcpy(dst, data, size * sizeof(float));
}
-android::sp<IPreparedModel> PrepareModelWithStatus(const V1_0::Model& model,
- armnn_driver::ArmnnDriver& driver,
- ErrorStatus& prepareStatus,
- ErrorStatus expectedStatus)
+android::sp<V1_0::IPreparedModel> PrepareModelWithStatus(const V1_0::Model& model,
+ armnn_driver::ArmnnDriver& driver,
+ ErrorStatus& prepareStatus,
+ ErrorStatus expectedStatus)
{
android::sp<PreparedModelCallback> cb(new PreparedModelCallback());
driver.prepareModel(model, cb);
@@ -128,10 +128,10 @@
#ifdef ARMNN_ANDROID_NN_V1_1
-android::sp<IPreparedModel> PrepareModelWithStatus(const V1_1::Model& model,
- armnn_driver::ArmnnDriver& driver,
- ErrorStatus& prepareStatus,
- ErrorStatus expectedStatus)
+android::sp<V1_0::IPreparedModel> PrepareModelWithStatus(const V1_1::Model& model,
+ armnn_driver::ArmnnDriver& driver,
+ ErrorStatus& prepareStatus,
+ ErrorStatus expectedStatus)
{
android::sp<PreparedModelCallback> cb(new PreparedModelCallback());
driver.prepareModel_1_1(model, V1_1::ExecutionPreference::LOW_POWER, cb);
@@ -147,7 +147,7 @@
#endif
-ErrorStatus Execute(android::sp<IPreparedModel> preparedModel,
+ErrorStatus Execute(android::sp<V1_0::IPreparedModel> preparedModel,
const Request& request,
ErrorStatus expectedStatus)
{
@@ -160,7 +160,7 @@
return execStatus;
}
-android::sp<ExecutionCallback> ExecuteNoWait(android::sp<IPreparedModel> preparedModel, const Request& request)
+android::sp<ExecutionCallback> ExecuteNoWait(android::sp<V1_0::IPreparedModel> preparedModel, const Request& request)
{
android::sp<ExecutionCallback> cb(new ExecutionCallback());
BOOST_TEST(preparedModel->execute(request, cb) == ErrorStatus::NONE);
diff --git a/test/DriverTestHelpers.hpp b/test/DriverTestHelpers.hpp
index 394720e..4a8f607 100644
--- a/test/DriverTestHelpers.hpp
+++ b/test/DriverTestHelpers.hpp
@@ -33,7 +33,7 @@
std::ostream& operator<<(std::ostream& os, V1_0::ErrorStatus stat);
-struct ExecutionCallback : public IExecutionCallback
+struct ExecutionCallback : public V1_0::IExecutionCallback
{
ExecutionCallback() : mNotified(false) {}
Return<void> notify(ErrorStatus status) override;
@@ -48,7 +48,7 @@
bool mNotified;
};
-class PreparedModelCallback : public IPreparedModelCallback
+class PreparedModelCallback : public V1_0::IPreparedModelCallback
{
public:
PreparedModelCallback()
@@ -58,13 +58,13 @@
~PreparedModelCallback() override { }
Return<void> notify(ErrorStatus status,
- const android::sp<IPreparedModel>& preparedModel) override;
+ const android::sp<V1_0::IPreparedModel>& preparedModel) override;
ErrorStatus GetErrorStatus() { return m_ErrorStatus; }
- android::sp<IPreparedModel> GetPreparedModel() { return m_PreparedModel; }
+ android::sp<V1_0::IPreparedModel> GetPreparedModel() { return m_PreparedModel; }
private:
ErrorStatus m_ErrorStatus;
- android::sp<IPreparedModel> m_PreparedModel;
+ android::sp<V1_0::IPreparedModel> m_PreparedModel;
};
hidl_memory allocateSharedMemory(int64_t size);
@@ -74,7 +74,7 @@
void AddPoolAndSetData(uint32_t size, Request& request, const float* data);
template<typename HalModel>
-void AddOperand(HalModel& model, const Operand& op)
+void AddOperand(HalModel& model, const V1_0::Operand& op)
{
model.operands.resize(model.operands.size() + 1);
model.operands[model.operands.size() - 1] = op;
@@ -87,11 +87,11 @@
location.offset = model.operandValues.size();
location.length = sizeof(int32_t);
- Operand op = {};
- op.type = OperandType::INT32;
- op.dimensions = hidl_vec<uint32_t>{};
- op.lifetime = OperandLifeTime::CONSTANT_COPY;
- op.location = location;
+ V1_0::Operand op = {};
+ op.type = V1_0::OperandType::INT32;
+ op.dimensions = hidl_vec<uint32_t>{};
+ op.lifetime = V1_0::OperandLifeTime::CONSTANT_COPY;
+ op.location = location;
model.operandValues.resize(model.operandValues.size() + location.length);
*reinterpret_cast<int32_t*>(&model.operandValues[location.offset]) = value;
@@ -112,8 +112,8 @@
void AddTensorOperand(HalModel& model,
const hidl_vec<uint32_t>& dimensions,
const T* values,
- OperandType operandType = OperandType::TENSOR_FLOAT32,
- OperandLifeTime operandLifeTime = OperandLifeTime::CONSTANT_COPY)
+ V1_0::OperandType operandType = V1_0::OperandType::TENSOR_FLOAT32,
+ V1_0::OperandLifeTime operandLifeTime = V1_0::OperandLifeTime::CONSTANT_COPY)
{
uint32_t totalElements = 1;
for (uint32_t dim : dimensions)
@@ -124,16 +124,16 @@
DataLocation location = {};
location.length = totalElements * sizeof(T);
- if(operandLifeTime == OperandLifeTime::CONSTANT_COPY)
+ if(operandLifeTime == V1_0::OperandLifeTime::CONSTANT_COPY)
{
location.offset = model.operandValues.size();
}
- Operand op = {};
- op.type = operandType;
- op.dimensions = dimensions;
- op.lifetime = OperandLifeTime::CONSTANT_COPY;
- op.location = location;
+ V1_0::Operand op = {};
+ op.type = operandType;
+ op.dimensions = dimensions;
+ op.lifetime = V1_0::OperandLifeTime::CONSTANT_COPY;
+ op.location = location;
model.operandValues.resize(model.operandValues.size() + location.length);
for (uint32_t i = 0; i < totalElements; i++)
@@ -148,8 +148,8 @@
void AddTensorOperand(HalModel& model,
const hidl_vec<uint32_t>& dimensions,
const std::vector<T>& values,
- OperandType operandType = OperandType::TENSOR_FLOAT32,
- OperandLifeTime operandLifeTime = OperandLifeTime::CONSTANT_COPY)
+ V1_0::OperandType operandType = V1_0::OperandType::TENSOR_FLOAT32,
+ V1_0::OperandLifeTime operandLifeTime = V1_0::OperandLifeTime::CONSTANT_COPY)
{
AddTensorOperand<HalModel, T>(model, dimensions, values.data(), operandType, operandLifeTime);
}
@@ -157,13 +157,13 @@
template<typename HalModel>
void AddInputOperand(HalModel& model,
const hidl_vec<uint32_t>& dimensions,
- OperandType operandType = OperandType::TENSOR_FLOAT32)
+ V1_0::OperandType operandType = V1_0::OperandType::TENSOR_FLOAT32)
{
- Operand op = {};
- op.type = operandType;
- op.scale = operandType == OperandType::TENSOR_QUANT8_ASYMM ? 1.f / 255.f : 0.f;
- op.dimensions = dimensions;
- op.lifetime = OperandLifeTime::MODEL_INPUT;
+ V1_0::Operand op = {};
+ op.type = operandType;
+ op.scale = operandType == V1_0::OperandType::TENSOR_QUANT8_ASYMM ? 1.f / 255.f : 0.f;
+ op.dimensions = dimensions;
+ op.lifetime = V1_0::OperandLifeTime::MODEL_INPUT;
AddOperand<HalModel>(model, op);
@@ -174,13 +174,13 @@
template<typename HalModel>
void AddOutputOperand(HalModel& model,
const hidl_vec<uint32_t>& dimensions,
- OperandType operandType = OperandType::TENSOR_FLOAT32)
+ V1_0::OperandType operandType = V1_0::OperandType::TENSOR_FLOAT32)
{
- Operand op = {};
- op.type = operandType;
- op.scale = operandType == OperandType::TENSOR_QUANT8_ASYMM ? 1.f / 255.f : 0.f;
- op.dimensions = dimensions;
- op.lifetime = OperandLifeTime::MODEL_OUTPUT;
+ V1_0::Operand op = {};
+ op.type = operandType;
+ op.scale = operandType == V1_0::OperandType::TENSOR_QUANT8_ASYMM ? 1.f / 255.f : 0.f;
+ op.dimensions = dimensions;
+ op.lifetime = V1_0::OperandLifeTime::MODEL_OUTPUT;
AddOperand<HalModel>(model, op);
@@ -188,14 +188,14 @@
model.outputIndexes[model.outputIndexes.size() - 1] = model.operands.size() - 1;
}
-android::sp<IPreparedModel> PrepareModelWithStatus(const V1_0::Model& model,
- armnn_driver::ArmnnDriver& driver,
- ErrorStatus& prepareStatus,
- ErrorStatus expectedStatus = ErrorStatus::NONE);
+android::sp<V1_0::IPreparedModel> PrepareModelWithStatus(const V1_0::Model& model,
+ armnn_driver::ArmnnDriver& driver,
+ ErrorStatus& prepareStatus,
+ ErrorStatus expectedStatus = ErrorStatus::NONE);
#ifdef ARMNN_ANDROID_NN_V1_1
-android::sp<IPreparedModel> PrepareModelWithStatus(const V1_1::Model& model,
+android::sp<V1_0::IPreparedModel> PrepareModelWithStatus(const V1_1::Model& model,
armnn_driver::ArmnnDriver& driver,
ErrorStatus& prepareStatus,
ErrorStatus expectedStatus = ErrorStatus::NONE);
@@ -203,18 +203,18 @@
#endif
template<typename HalModel>
-android::sp<IPreparedModel> PrepareModel(const HalModel& model,
+android::sp<V1_0::IPreparedModel> PrepareModel(const HalModel& model,
armnn_driver::ArmnnDriver& driver)
{
ErrorStatus prepareStatus = ErrorStatus::NONE;
return PrepareModelWithStatus(model, driver, prepareStatus);
}
-ErrorStatus Execute(android::sp<IPreparedModel> preparedModel,
+ErrorStatus Execute(android::sp<V1_0::IPreparedModel> preparedModel,
const Request& request,
ErrorStatus expectedStatus = ErrorStatus::NONE);
-android::sp<ExecutionCallback> ExecuteNoWait(android::sp<IPreparedModel> preparedModel,
+android::sp<ExecutionCallback> ExecuteNoWait(android::sp<V1_0::IPreparedModel> preparedModel,
const Request& request);
} // namespace driverTestHelpers
diff --git a/test/FullyConnected.cpp b/test/FullyConnected.cpp
index 5c204ca..6ab63ff 100644
--- a/test/FullyConnected.cpp
+++ b/test/FullyConnected.cpp
@@ -39,7 +39,7 @@
model.operations[0].outputs = hidl_vec<uint32_t>{4};
// make the prepared model
- android::sp<IPreparedModel> preparedModel = PrepareModel(model, *driver);
+ android::sp<V1_0::IPreparedModel> preparedModel = PrepareModel(model, *driver);
// construct the request
DataLocation inloc = {};
@@ -118,7 +118,7 @@
model.operations[0].outputs = hidl_vec<uint32_t>{4};
// make the prepared model
- android::sp<IPreparedModel> preparedModel = PrepareModel(model, *driver);
+ android::sp<V1_0::IPreparedModel> preparedModel = PrepareModel(model, *driver);
// construct the request
@@ -205,7 +205,7 @@
model.operations[0].outputs = hidl_vec<uint32_t>{4};
// make the prepared model
- android::sp<IPreparedModel> preparedModel = PrepareModel(model, *driver);
+ android::sp<V1_0::IPreparedModel> preparedModel = PrepareModel(model, *driver);
// construct the request
diff --git a/test/Lstm.cpp b/test/Lstm.cpp
index 66f2cf0..b1b7c9d 100644
--- a/test/Lstm.cpp
+++ b/test/Lstm.cpp
@@ -137,7 +137,7 @@
// 01: The input-to-input weights: Optional. A 2-D tensor of ANEURALNETWORKS_TENSOR_FLOAT32, of shape
// [num_units, input_size], where “num_units” corresponds to the number of cell units.
- AddTensorOperand(model, inputToInputWeightsDimensions, inputToInputWeightsValue, OperandType::TENSOR_FLOAT32,
+ AddTensorOperand(model, inputToInputWeightsDimensions, inputToInputWeightsValue, V1_0::OperandType::TENSOR_FLOAT32,
CreateNoValueLifeTime(inputToInputWeightsDimensions));
// 02: The input-to-forget weights: A 2-D tensor of ANEURALNETWORKS_TENSOR_FLOAT32, of shape
// [num_units, input_size].
@@ -151,7 +151,7 @@
// [num_units, output_size], where “output_size” corresponds to either the number of cell units (i.e.,
// “num_units”), or the second dimension of the “projection_weights”, if defined.
AddTensorOperand(model, recurrentToInputWeightsDimensions, recurrentToInputWeightsValue,
- OperandType::TENSOR_FLOAT32, CreateNoValueLifeTime(recurrentToInputWeightsDimensions));
+ V1_0::OperandType::TENSOR_FLOAT32, CreateNoValueLifeTime(recurrentToInputWeightsDimensions));
// 06: The recurrent-to-forget weights: A 2-D tensor of ANEURALNETWORKS_TENSOR_FLOAT32, of shape
// [num_units, output_size].
AddTensorOperand(model, recurrentToForgetWeightsDimensions, recurrentToForgetWeightsValue);
@@ -163,16 +163,16 @@
AddTensorOperand(model, recurrentToOutputWeightsDimensions, recurrentToOutputWeightsValue);
// 09: The cell-to-input weights: Optional. A 1-D tensor of ANEURALNETWORKS_TENSOR_FLOAT32, of shape [num_units].
AddTensorOperand(model, cellToInputWeightsDimensions, cellToInputWeightsValue,
- OperandType::TENSOR_FLOAT32, CreateNoValueLifeTime(cellToInputWeightsDimensions));
+ V1_0::OperandType::TENSOR_FLOAT32, CreateNoValueLifeTime(cellToInputWeightsDimensions));
// 10: The cell-to-forget weights: Optional. A 1-D tensor of ANEURALNETWORKS_TENSOR_FLOAT32, of shape [num_units].
AddTensorOperand(model, cellToForgetWeightsDimensions, cellToForgetWeightsValue,
- OperandType::TENSOR_FLOAT32, CreateNoValueLifeTime(cellToForgetWeightsDimensions));
+ V1_0::OperandType::TENSOR_FLOAT32, CreateNoValueLifeTime(cellToForgetWeightsDimensions));
// 11: The cell-to-output weights: Optional. A 1-D tensor of ANEURALNETWORKS_TENSOR_FLOAT32, of shape [num_units].
AddTensorOperand(model, cellToOutputWeightsDimensions, cellToOutputWeightsValue,
- OperandType::TENSOR_FLOAT32, CreateNoValueLifeTime(cellToOutputWeightsDimensions));
+ V1_0::OperandType::TENSOR_FLOAT32, CreateNoValueLifeTime(cellToOutputWeightsDimensions));
// 12: The input gate bias: Optional. A 1-D tensor of ANEURALNETWORKS_TENSOR_FLOAT32, of shape [num_units].
AddTensorOperand(model, inputGateBiasDimensions, inputGateBiasValue,
- OperandType::TENSOR_FLOAT32, CreateNoValueLifeTime(inputGateBiasDimensions));
+ V1_0::OperandType::TENSOR_FLOAT32, CreateNoValueLifeTime(inputGateBiasDimensions));
// 13: The forget gate bias: A 1-D tensor of ANEURALNETWORKS_TENSOR_FLOAT32, of shape [num_units].
AddTensorOperand(model, forgetGateBiasDimensions, forgetGateBiasValue);
// 14: The cell bias: A 1-D tensor of ANEURALNETWORKS_TENSOR_FLOAT32, of shape [num_units].
@@ -182,10 +182,10 @@
// 16: The projection weights: Optional. A 2-D tensor of ANEURALNETWORKS_TENSOR_FLOAT32, of shape
// [output_size, num_units].
AddTensorOperand(model, projectionWeightsDimensions, projectionWeightsValue,
- OperandType::TENSOR_FLOAT32, CreateNoValueLifeTime(projectionWeightsDimensions));
+ V1_0::OperandType::TENSOR_FLOAT32, CreateNoValueLifeTime(projectionWeightsDimensions));
// 17: The projection bias: Optional. A 1-D tensor of ANEURALNETWORKS_TENSOR_FLOAT32, of shape [output_size].
AddTensorOperand(model, projectionBiasDimensions, projectionBiasValue,
- OperandType::TENSOR_FLOAT32, CreateNoValueLifeTime(projectionBiasDimensions));
+ V1_0::OperandType::TENSOR_FLOAT32, CreateNoValueLifeTime(projectionBiasDimensions));
// 18: The output state: A 2-D tensor of ANEURALNETWORKS_TENSOR_FLOAT32, of shape [batch_size, output_size].
AddInputOperand(model, outputStateInDimensions);
@@ -196,15 +196,15 @@
// 20: The activation function: A value indicating the activation function:
// 0: None; 1: Relu; 3: Relu6; 4: Tanh; 6: Sigmoid.
AddTensorOperand(model, activationFunctionDimensions,
- activationFunctionValue, OperandType::INT32);
+ activationFunctionValue, V1_0::OperandType::INT32);
// 21: The clipping threshold: for the cell state, such that values are bound within [-cell_clip, cell_clip].
// If set to 0.0 then clipping is disabled.
AddTensorOperand(model, cellClippingThresholdDimensions,
- cellClippingThresholdValue, OperandType::FLOAT32);
+ cellClippingThresholdValue, V1_0::OperandType::FLOAT32);
// 22: The clipping threshold: for the output from the projection layer, such that values are bound within
// [-proj_clip, proj_clip]. If set to 0.0 then clipping is disabled.
AddTensorOperand(model, projectionClippingThresholdDimensions,
- projectionClippingThresholdValue, OperandType::FLOAT32);
+ projectionClippingThresholdValue, V1_0::OperandType::FLOAT32);
// Outputs:
// 0: The scratch buffer: A 2-D tensor of ANEURALNETWORKS_TENSOR_FLOAT32, of shape [batch_size, num_units * 4] with
@@ -261,7 +261,7 @@
float* outputData = static_cast<float*>(static_cast<void*>(outputMemory->getPointer()));
// make the prepared model and run the execution
- android::sp<IPreparedModel> preparedModel = PrepareModel(model, *driver);
+ android::sp<V1_0::IPreparedModel> preparedModel = PrepareModel(model, *driver);
if (preparedModel.get() != nullptr)
{
Execute(preparedModel, request);
diff --git a/test/Merger.cpp b/test/Merger.cpp
index 118e0d6..16ac451 100644
--- a/test/Merger.cpp
+++ b/test/Merger.cpp
@@ -51,7 +51,7 @@
// make the prepared model
ErrorStatus prepareStatus=ErrorStatus::NONE;
- android::sp<IPreparedModel> preparedModel = PrepareModelWithStatus(model,
+ android::sp<V1_0::IPreparedModel> preparedModel = PrepareModelWithStatus(model,
*driver,
prepareStatus,
expectedPrepareStatus);