IVGCVSW-3633 Refactor HalPolicy to fully support V1.2 models
* Templated and moved V1.0 and V1.1 Convert methods to ensure they can work with later versions of models, operations and operands.
* The V1.2 HalPolicy no longer converts V1.2 models, operations and operands to earlier versions.
* The V1.2 HalPolicy no longer passes operations to the V1.1 or V1.0 HalPolicies for conversion.
Signed-off-by: Mike Kelly <mike.kelly@arm.com>
Change-Id: I5de59d43a3abb1f8ac0253dc637ad68318960c76
diff --git a/1.0/HalPolicy.cpp b/1.0/HalPolicy.cpp
index 6c8dcb5..cff678a 100644
--- a/1.0/HalPolicy.cpp
+++ b/1.0/HalPolicy.cpp
@@ -74,63 +74,7 @@
bool HalPolicy::ConvertAdd(const Operation& operation, const Model& model, ConversionData& data)
{
ALOGV("hal_1_0::HalPolicy::ConvertAdd()");
-
- LayerInputHandle input0 = ConvertToLayerInputHandle<hal_1_0::HalPolicy>(operation, 0, model, data);
- LayerInputHandle input1 = ConvertToLayerInputHandle<hal_1_0::HalPolicy>(operation, 1, model, data);
-
- if (!input0.IsValid() || !input1.IsValid())
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- // The FuseActivation parameter is always the input index 2
- // and it should be optional
- ActivationFn activationFunction;
- if (!GetOptionalInputActivation<hal_1_0::HalPolicy>(operation, 2, activationFunction, model, data))
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- const Operand* outputOperand = GetOutputOperand<hal_1_0::HalPolicy>(operation, 0, model);
- if (!outputOperand)
- {
- return false;
- }
-
- const armnn::TensorInfo& inputInfo0 = input0.GetTensorInfo();
- const armnn::TensorInfo& inputInfo1 = input1.GetTensorInfo();
-
- const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*outputOperand);
- if (IsDynamicTensor(outputInfo))
- {
- return Fail("%s: Dynamic output tensors are not supported", __func__);
- }
-
- bool isSupported = false;
- FORWARD_LAYER_SUPPORT_FUNC(__func__,
- IsAdditionSupported,
- data.m_Backends,
- isSupported,
- inputInfo0,
- inputInfo1,
- outputInfo);
- if (!isSupported)
- {
- return false;
- }
-
- armnn::IConnectableLayer* const startLayer = data.m_Network->AddAdditionLayer();
- armnn::IConnectableLayer* const endLayer = ProcessActivation(outputInfo, activationFunction, startLayer, data);
-
- if (endLayer != nullptr)
- {
- BroadcastTensor(input0, input1, startLayer, *data.m_Network);
- return SetupAndTrackLayerOutputSlot<hal_1_0::HalPolicy>(operation, 0, *endLayer, model, data);
- }
- else
- {
- return Fail("%s: ProcessActivation failed", __func__);
- }
+ return ::ConvertAdd<hal_1_0::HalPolicy>(operation, model, data);
}
bool HalPolicy::ConvertAveragePool2d(const Operation& operation, const Model& model, ConversionData& data)
@@ -160,187 +104,19 @@
bool HalPolicy::ConvertDequantize(const Operation& operation, const Model& model, ConversionData& data)
{
ALOGV("hal_1_0::HalPolicy::ConvertDequantize()");
-
- LayerInputHandle input = ConvertToLayerInputHandle<hal_1_0::HalPolicy>(operation, 0, model, data);
- if (!input.IsValid())
- {
- return Fail("%s: Operation has invalid input", __func__);
- }
-
- const Operand* const outputOperand = GetOutputOperand<hal_1_0::HalPolicy>(operation, 0, model);
- if (!outputOperand)
- {
- return Fail("%s: Operation has invalid outputs", __func__);
- }
-
- const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*outputOperand);
- if (IsDynamicTensor(outputInfo))
- {
- return Fail("%s: Dynamic output tensors are not supported", __func__);
- }
-
- bool isSupported = false;
- FORWARD_LAYER_SUPPORT_FUNC(__func__,
- IsDequantizeSupported,
- data.m_Backends,
- isSupported,
- input.GetTensorInfo(),
- GetTensorInfoForOperand(*outputOperand));
- if (!isSupported)
- {
- return false;
- }
-
- armnn::IConnectableLayer* const layer = data.m_Network->AddDequantizeLayer();
- assert(layer != nullptr);
- input.Connect(layer->GetInputSlot(0));
-
- return SetupAndTrackLayerOutputSlot<hal_1_0::HalPolicy>(operation, 0, *layer, model, data);
+ return ::ConvertDequantize<hal_1_0::HalPolicy>(operation, model, data);
}
bool HalPolicy::ConvertFloor(const Operation& operation, const Model& model, ConversionData& data)
{
ALOGV("hal_1_0::HalPolicy::ConvertFloor()");
-
- LayerInputHandle input = ConvertToLayerInputHandle<hal_1_0::HalPolicy>(operation, 0, model, data);
- if (!input.IsValid())
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- const Operand* const outputOperand = GetOutputOperand<hal_1_0::HalPolicy>(operation, 0, model);
- if (!outputOperand)
- {
- return Fail("%s: Operation has invalid outputs", __func__);
- }
-
- const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*outputOperand);
- if (IsDynamicTensor(outputInfo))
- {
- return Fail("%s: Dynamic output tensors are not supported", __func__);
- }
-
- bool isSupported = false;
- FORWARD_LAYER_SUPPORT_FUNC(__func__,
- IsFloorSupported,
- data.m_Backends,
- isSupported,
- input.GetTensorInfo(),
- outputInfo);
- if (!isSupported)
- {
- return false;
- }
-
- armnn::IConnectableLayer* layer = data.m_Network->AddFloorLayer();
- assert(layer != nullptr);
- input.Connect(layer->GetInputSlot(0));
-
- return SetupAndTrackLayerOutputSlot<hal_1_0::HalPolicy>(operation, 0, *layer, model, data);
+ return ::ConvertFloor<hal_1_0::HalPolicy>(operation, model, data);
}
bool HalPolicy::ConvertFullyConnected(const Operation& operation, const Model& model, ConversionData& data)
{
ALOGV("hal_1_0::HalPolicy::ConvertFullyConnected()");
-
- LayerInputHandle input = ConvertToLayerInputHandle<hal_1_0::HalPolicy>(operation, 0, model, data);
- if (!input.IsValid())
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- const Operand* output = GetOutputOperand<hal_1_0::HalPolicy>(operation, 0, model);
- if (!output)
- {
- return Fail("%s: Could not read output 0", __func__);
- }
-
- const armnn::TensorInfo& inputInfo = input.GetTensorInfo();
- const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
-
- if (IsDynamicTensor(outputInfo))
- {
- return Fail("%s: Dynamic output tensors are not supported", __func__);
- }
-
- // ArmNN does not currently support non-fixed weights or bias
- ConstTensorPin weightsPin =
- ConvertOperationInputToConstTensorPin<hal_1_0::HalPolicy>(operation, 1, model, data); // 2D
- ConstTensorPin biasPin =
- ConvertOperationInputToConstTensorPin<hal_1_0::HalPolicy>(operation, 2, model, data); // 1D
-
- if (!weightsPin.IsValid() || !biasPin.IsValid())
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- armnn::ConstTensor weights = weightsPin.GetConstTensor();
- armnn::ConstTensor bias = biasPin.GetConstTensor();
- armnn::TensorInfo reshapedInfo = inputInfo;
-
- try
- {
- reshapedInfo.SetShape(FlattenFullyConnectedInput(inputInfo.GetShape(), weights.GetInfo().GetShape()));
- } catch (const std::exception &e) {
- return Fail("%s: %s", __func__, e.what());
- }
-
- // ensuring that the bias value is within 1% of the weights input (small float differences can exist)
- SanitizeBiasQuantizationScale(bias.GetInfo(), weights.GetInfo(), reshapedInfo);
-
- ActivationFn activationFunction;
- if (!GetInputActivationFunction<hal_1_0::HalPolicy>(operation, 3, activationFunction, model, data))
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- armnn::FullyConnectedDescriptor desc;
- desc.m_TransposeWeightMatrix = true;
- desc.m_BiasEnabled = true;
-
- bool isSupported = false;
- FORWARD_LAYER_SUPPORT_FUNC(__func__,
- IsFullyConnectedSupported,
- data.m_Backends,
- isSupported,
- reshapedInfo,
- outputInfo,
- weights.GetInfo(),
- bias.GetInfo(),
- desc);
- if (!isSupported)
- {
- return false;
- }
-
- armnn::IConnectableLayer* startLayer =
- data.m_Network->AddFullyConnectedLayer(desc, weights, armnn::Optional<armnn::ConstTensor>(bias));
- armnn::IConnectableLayer* endLayer = ProcessActivation(outputInfo, activationFunction, startLayer, data);
-
- if (endLayer != nullptr)
- {
- if (inputInfo.GetNumDimensions() > 2U)
- {
- armnn::ReshapeDescriptor reshapeDescriptor;
- reshapeDescriptor.m_TargetShape = reshapedInfo.GetShape();
-
- armnn::IConnectableLayer* reshapeLayer = data.m_Network->AddReshapeLayer(reshapeDescriptor);
- assert(reshapeLayer != nullptr);
- input.Connect(reshapeLayer->GetInputSlot(0));
- reshapeLayer->GetOutputSlot(0).SetTensorInfo(reshapedInfo);
- reshapeLayer->GetOutputSlot(0).Connect(startLayer->GetInputSlot(0));
- }
- else
- {
- input.Connect(startLayer->GetInputSlot(0));
- }
-
- return SetupAndTrackLayerOutputSlot<hal_1_0::HalPolicy>(operation, 0, *endLayer, model, data);
- }
- else
- {
- return Fail("%s: ProcessActivation failed", __func__);
- }
+ return ::ConvertFullyConnected<hal_1_0::HalPolicy>(operation, model, data);
}
bool HalPolicy::ConvertLocalResponseNormalization(const Operation& operation,
@@ -348,74 +124,13 @@
ConversionData& data)
{
ALOGV("hal_1_0::HalPolicy::ConvertLocalResponseNormalization()");
-
- LayerInputHandle input = ConvertToLayerInputHandle<hal_1_0::HalPolicy>(operation, 0, model, data);
- if (!input.IsValid())
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- const Operand* output = GetOutputOperand<hal_1_0::HalPolicy>(operation, 0, model);
- if (!output)
- {
- return Fail("%s: Could not read output 0", __func__);
- }
-
- const armnn::TensorInfo& inputInfo = input.GetTensorInfo();
- const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
-
- if (IsDynamicTensor(outputInfo))
- {
- return Fail("%s: Dynamic output tensors are not supported", __func__);
- }
-
- armnn::NormalizationDescriptor descriptor;
- descriptor.m_DataLayout = armnn::DataLayout::NHWC;
- descriptor.m_NormChannelType = armnn::NormalizationAlgorithmChannel::Across;
- descriptor.m_NormMethodType = armnn::NormalizationAlgorithmMethod::LocalBrightness;
-
- if (!input.IsValid() ||
- !GetInputScalar<hal_1_0::HalPolicy>(operation, 1, OperandType::INT32, descriptor.m_NormSize, model, data) ||
- !GetInputFloat32<hal_1_0::HalPolicy>(operation, 2, descriptor.m_K, model, data) ||
- !GetInputFloat32<hal_1_0::HalPolicy>(operation, 3, descriptor.m_Alpha, model, data) ||
- !GetInputFloat32<hal_1_0::HalPolicy>(operation, 4, descriptor.m_Beta, model, data))
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- // ArmNN expects normSize to be the full size of the normalization
- // window rather than the radius as in AndroidNN.
- descriptor.m_NormSize = 1 + (2 * descriptor.m_NormSize);
-
- bool isSupported = false;
- FORWARD_LAYER_SUPPORT_FUNC(__func__,
- IsNormalizationSupported,
- data.m_Backends,
- isSupported,
- inputInfo,
- outputInfo,
- descriptor);
- if (!isSupported)
- {
- return false;
- }
-
-
- armnn::IConnectableLayer* layer = data.m_Network->AddNormalizationLayer(descriptor);
- assert(layer != nullptr);
- input.Connect(layer->GetInputSlot(0));
-
- return SetupAndTrackLayerOutputSlot<hal_1_0::HalPolicy>(operation, 0, *layer, model, data);
+ return ::ConvertLocalResponseNormalization<hal_1_0::HalPolicy>(operation, model, data);
}
bool HalPolicy::ConvertLogistic(const Operation& operation, const Model& model, ConversionData& data)
{
ALOGV("hal_1_0::HalPolicy::ConvertLogistic()");
-
- armnn::ActivationDescriptor desc;
- desc.m_Function = armnn::ActivationFunction::Sigmoid;
-
- return ConvertToActivation<hal_1_0::HalPolicy>(operation, __func__, desc, model, data);
+ return ::ConvertLogistic<hal_1_0::HalPolicy>(operation, model, data);
}
bool HalPolicy::ConvertLstm(const Operation& operation, const Model& model, ConversionData& data)
@@ -775,48 +490,7 @@
bool HalPolicy::ConvertL2Normalization(const Operation& operation, const Model& model, ConversionData& data)
{
ALOGV("hal_1_0::HalPolicy::ConvertL2Normalization()");
-
- LayerInputHandle input = ConvertToLayerInputHandle<hal_1_0::HalPolicy>(operation, 0, model, data);
- if (!input.IsValid())
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- const Operand* output = GetOutputOperand<hal_1_0::HalPolicy>(operation, 0, model);
- if (!output)
- {
- return Fail("%s: Could not read output 0", __func__);
- }
-
- const armnn::TensorInfo& inputInfo = input.GetTensorInfo();
- const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
-
- if (IsDynamicTensor(outputInfo))
- {
- return Fail("%s: Dynamic output tensors are not supported", __func__);
- }
-
- armnn::L2NormalizationDescriptor desc;
- desc.m_DataLayout = armnn::DataLayout::NHWC;
-
- bool isSupported = false;
- FORWARD_LAYER_SUPPORT_FUNC(__func__,
- IsL2NormalizationSupported,
- data.m_Backends,
- isSupported,
- inputInfo,
- outputInfo,
- desc);
- if (!isSupported)
- {
- return false;
- }
-
- armnn::IConnectableLayer* layer = data.m_Network->AddL2NormalizationLayer(desc);
- assert(layer != nullptr);
- input.Connect(layer->GetInputSlot(0));
-
- return SetupAndTrackLayerOutputSlot<hal_1_0::HalPolicy>(operation, 0, *layer, model, data);
+ return ::ConvertL2Normalization<hal_1_0::HalPolicy>(operation, model, data);
}
bool HalPolicy::ConvertL2Pool2d(const Operation& operation, const Model& model, ConversionData& data)
@@ -834,64 +508,7 @@
bool HalPolicy::ConvertMul(const Operation& operation, const Model& model, ConversionData& data)
{
ALOGV("hal_1_0::HalPolicy::ConvertMul()");
-
- LayerInputHandle input0 = ConvertToLayerInputHandle<hal_1_0::HalPolicy>(operation, 0, model, data);
- LayerInputHandle input1 = ConvertToLayerInputHandle<hal_1_0::HalPolicy>(operation, 1, model, data);
-
- if (!input0.IsValid() || !input1.IsValid())
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- // The FuseActivation parameter is always the input index 2
- // and it should be optional
- ActivationFn activationFunction;
- if (!GetOptionalInputActivation<hal_1_0::HalPolicy>(operation, 2, activationFunction, model, data))
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- const Operand* outputOperand = GetOutputOperand<hal_1_0::HalPolicy>(operation, 0, model);
-
- if (outputOperand == nullptr)
- {
- return false;
- }
-
- const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*outputOperand);
- if (IsDynamicTensor(outputInfo))
- {
- return Fail("%s: Dynamic output tensors are not supported", __func__);
- }
-
- bool isSupported = false;
- FORWARD_LAYER_SUPPORT_FUNC(__func__,
- IsMultiplicationSupported,
- data.m_Backends,
- isSupported,
- input0.GetTensorInfo(),
- input1.GetTensorInfo(),
- outputInfo);
- if (!isSupported)
- {
- return false;
- }
-
- armnn::IConnectableLayer* const startLayer = data.m_Network->AddMultiplicationLayer();
- armnn::IConnectableLayer* const endLayer = ProcessActivation(outputInfo, activationFunction, startLayer, data);
-
- const armnn::TensorInfo& inputTensorInfo0 = input0.GetTensorInfo();
- const armnn::TensorInfo& inputTensorInfo1 = input1.GetTensorInfo();
-
- if (endLayer != nullptr)
- {
- BroadcastTensor(input0, input1, startLayer, *data.m_Network);
- return SetupAndTrackLayerOutputSlot<hal_1_0::HalPolicy>(operation, 0, *endLayer, model, data);
- }
- else
- {
- return Fail("%s: ProcessActivation failed", __func__);
- }
+ return ::ConvertMul<hal_1_0::HalPolicy>(operation, model, data);
}
bool HalPolicy::ConvertReLu(const Operation& operation, const Model& model, ConversionData& data)
@@ -1029,74 +646,7 @@
bool HalPolicy::ConvertReshape(const Operation& operation, const Model& model, ConversionData& data)
{
ALOGV("hal_1_0::HalPolicy::ConvertReshape()");
-
- const Operand* inputOperand = GetInputOperand<hal_1_0::HalPolicy>(operation, 0, model);
- const Operand* requestedShapeOperand = GetInputOperand<hal_1_0::HalPolicy>(operation, 1, model);
- const Operand* outputOperand = GetOutputOperand<hal_1_0::HalPolicy>(operation, 0, model);
-
- if (inputOperand == nullptr
- || requestedShapeOperand == nullptr
- || outputOperand == nullptr)
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
-
- if (requestedShapeOperand->dimensions.size() != 1)
- {
- return Fail("%s: Input 1 expected to be one-dimensional (found %i dimensions)",
- __func__, requestedShapeOperand->dimensions.size());
- }
-
- std::vector<int32_t> targetDimensions;
- if (!GetTensorInt32Values<hal_1_0::HalPolicy>(*requestedShapeOperand, targetDimensions, model, data))
- {
- return Fail("%s: Could not read values of input 1", __func__);
- }
-
- const Shape inputOperandShape = GetOperandShape(*inputOperand);
-
- Shape requestedShape;
- // targetDimensions may contain special values (e.g. -1). reshapePrepare() is an AndroidNN provided utility
- // function that resolves these values into a fully specified tensor shape.
- if (!reshapePrepare(inputOperandShape, targetDimensions.data(), targetDimensions.size(), &requestedShape))
- {
- return Fail("%s: Failed to resolve the requested shape", __func__);
- }
-
- const Shape outputOperandShape = GetOperandShape(*outputOperand);
- if (!SameShape(requestedShape, outputOperandShape))
- {
- return Fail("%s: Shape of output operand does not match resolved requested shape", __func__);
- }
-
- LayerInputHandle input = ConvertToLayerInputHandle<hal_1_0::HalPolicy>(operation, 0, model, data);
- if (!input.IsValid())
- {
- return Fail("%s: Could not read input 0", __func__);
- }
-
- armnn::ReshapeDescriptor reshapeDescriptor;
- reshapeDescriptor.m_TargetShape = armnn::TensorShape(requestedShape.dimensions.size(),
- requestedShape.dimensions.data());
-
- bool isSupported = false;
- FORWARD_LAYER_SUPPORT_FUNC(__func__,
- IsReshapeSupported,
- data.m_Backends,
- isSupported,
- input.GetTensorInfo(),
- reshapeDescriptor);
- if (!isSupported)
- {
- return false;
- }
-
- armnn::IConnectableLayer* layer = data.m_Network->AddReshapeLayer(reshapeDescriptor);
- assert(layer != nullptr);
- input.Connect(layer->GetInputSlot(0));
-
- return SetupAndTrackLayerOutputSlot<hal_1_0::HalPolicy>(operation, 0, *layer, model, data);
+ return ::ConvertReshape<hal_1_0::HalPolicy>(operation, model, data);
}
bool HalPolicy::ConvertResizeBilinear(const Operation& operation, const Model& model, ConversionData& data)
diff --git a/1.1/HalPolicy.cpp b/1.1/HalPolicy.cpp
index e75b5c2..aa650e9 100644
--- a/1.1/HalPolicy.cpp
+++ b/1.1/HalPolicy.cpp
@@ -106,61 +106,7 @@
bool HalPolicy::ConvertDiv(const Operation& operation, const Model& model, ConversionData& data)
{
ALOGV("hal_1_1::HalPolicy::ConvertDiv()");
-
- LayerInputHandle input0 = ConvertToLayerInputHandle<hal_1_1::HalPolicy>(operation, 0, model, data);
- LayerInputHandle input1 = ConvertToLayerInputHandle<hal_1_1::HalPolicy>(operation, 1, model, data);
-
- if (!input0.IsValid() || !input1.IsValid())
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- // The FuseActivation parameter is always the input index 2
- // and it should be optional
- ActivationFn activationFunction;
- if (!GetOptionalInputActivation<hal_1_1::HalPolicy>(operation, 2, activationFunction, model, data))
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- const Operand* output = GetOutputOperand<hal_1_1::HalPolicy>(operation, 0, model);
- if (!output)
- {
- return Fail("%s: Could not read output 0", __func__);
- }
-
- const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
- if (IsDynamicTensor(outputInfo))
- {
- return Fail("%s: Dynamic output tensors are not supported", __func__);
- }
-
- bool isSupported = false;
- FORWARD_LAYER_SUPPORT_FUNC(__func__,
- IsDivisionSupported,
- data.m_Backends,
- isSupported,
- input0.GetTensorInfo(),
- input1.GetTensorInfo(),
- outputInfo);
- if (!isSupported)
- {
- return false;
- }
-
- armnn::IConnectableLayer* const startLayer = data.m_Network->AddDivisionLayer();
- armnn::IConnectableLayer* const endLayer = ProcessActivation(outputInfo, activationFunction, startLayer, data);
-
- const armnn::TensorInfo& inputTensorInfo0 = input0.GetTensorInfo();
- const armnn::TensorInfo& inputTensorInfo1 = input1.GetTensorInfo();
-
- if (endLayer)
- {
- BroadcastTensor(input0, input1, startLayer, *data.m_Network);
- return SetupAndTrackLayerOutputSlot<hal_1_1::HalPolicy>(operation, 0, *endLayer, model, data);
- }
-
- return Fail("%s: ProcessActivation failed", __func__);
+ return ::ConvertDiv<hal_1_1::HalPolicy>(operation, model, data);
}
bool HalPolicy::ConvertSub(const Operation& operation, const Model& model, ConversionData& data)
@@ -172,75 +118,7 @@
bool HalPolicy::ConvertMean(const Operation& operation, const Model& model, ConversionData& data)
{
ALOGV("hal_1_1::HalPolicy::ConvertMean()");
-
- LayerInputHandle input = ConvertToLayerInputHandle<hal_1_1::HalPolicy>(operation, 0, model, data);
- if (!input.IsValid())
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- const Operand* output = GetOutputOperand<hal_1_1::HalPolicy>(operation, 0, model);
- if (!output)
- {
- return Fail("%s: Could not read output 0", __func__);
- }
-
- const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
- if (IsDynamicTensor(outputInfo))
- {
- return Fail("%s: Dynamic output tensors are not supported", __func__);
- }
-
- const Operand* axisOperand = GetInputOperand<hal_1_1::HalPolicy>(operation, 1, model);
- if (!axisOperand)
- {
- return Fail("%s: Could not read input 1", __func__);
- }
-
- std::vector<int32_t> axis;
- if (!GetTensorInt32Values<hal_1_1::HalPolicy>(*axisOperand, axis, model, data))
- {
- return Fail("%s: Input 1 has invalid values", __func__);
- }
-
- const armnn::TensorInfo& inputInfo = input.GetTensorInfo();
-
- // Convert the axis to unsigned int and remove duplicates.
- unsigned int rank = inputInfo.GetNumDimensions();
- std::set<unsigned int> uniqueAxis;
- std::transform(axis.begin(), axis.end(),
- std::inserter(uniqueAxis, uniqueAxis.begin()),
- [rank](int i) -> unsigned int { return (i + rank) % rank; });
-
- // Get the "keep dims" flag.
- int32_t keepDims = 0;
- if (!GetInputInt32<hal_1_1::HalPolicy>(operation, 2, keepDims, model, data))
- {
- return Fail("%s: Could not read input 2", __func__);
- }
-
- armnn::MeanDescriptor descriptor;
- descriptor.m_Axis.assign(uniqueAxis.begin(), uniqueAxis.end());
- descriptor.m_KeepDims = keepDims > 0;
-
- bool isSupported = false;
- FORWARD_LAYER_SUPPORT_FUNC(__func__,
- IsMeanSupported,
- data.m_Backends,
- isSupported,
- inputInfo,
- outputInfo,
- descriptor);
- if (!isSupported)
- {
- return false;
- }
-
- armnn::IConnectableLayer* const layer = data.m_Network->AddMeanLayer(descriptor);
- assert(layer != nullptr);
- input.Connect(layer->GetInputSlot(0));
-
- return SetupAndTrackLayerOutputSlot<hal_1_1::HalPolicy>(operation, 0, *layer, model, data);
+ return ::ConvertMean<hal_1_1::HalPolicy>(operation, model, data);
}
bool HalPolicy::ConvertPad(const Operation& operation, const Model& model, ConversionData& data)
@@ -258,261 +136,19 @@
bool HalPolicy::ConvertSqueeze(const Operation& operation, const Model& model, ConversionData& data)
{
ALOGV("hal_1_1::HalPolicy::ConvertSqueeze()");
-
- LayerInputHandle input = ConvertToLayerInputHandle<hal_1_1::HalPolicy>(operation, 0, model, data);
- if (!input.IsValid())
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- const armnn::TensorInfo& inputInfo = input.GetTensorInfo();
- unsigned int rank = inputInfo.GetNumDimensions();
- if (rank > 4)
- {
- Fail("%s: Inputs with rank greater than 4 are not supported", __func__);
- }
-
- const Operand* output = GetOutputOperand<hal_1_1::HalPolicy>(operation, 0, model);
- if (!output)
- {
- return Fail("%s: Could not read output 0", __func__);
- }
-
- if (IsDynamicTensor(GetTensorInfoForOperand(*output)))
- {
- return Fail("%s: Dynamic output tensors are not supported", __func__);
- }
-
- // NOTE: Axis is an optional parameter to SQUEEZE, therefore we do not want to generate a failure
- // if the operand index is out of bounds.
- const Operand* axisOperand = GetInputOperand<hal_1_1::HalPolicy>(operation, 1, model, false);
-
- const uint32_t dimensionSequence[] = { 0, 1, 2, 3 };
-
- std::vector<int32_t> axis;
- if (!axisOperand)
- {
- axis.assign(dimensionSequence,
- dimensionSequence + rank);
- }
- else
- {
- GetTensorInt32Values<hal_1_1::HalPolicy>(*axisOperand, axis, model, data);
- }
-
-
- std::vector<uint32_t> outputDims;
- for (unsigned int i = 0; i < rank; i++)
- {
- bool skipSqueeze = (std::find(axis.begin(), axis.end(), i) == axis.end());
- auto currentDimension = inputInfo.GetShape()[i];
- if (skipSqueeze || currentDimension != 1)
- {
- outputDims.push_back(currentDimension);
- }
- }
-
- armnn::TensorShape outShape = armnn::TensorShape(outputDims.size(), outputDims.data());
-
- armnn::TensorInfo outputInfo = inputInfo;
- outputInfo.SetShape(outShape);
-
- armnn::ReshapeDescriptor reshapeDesc;
- reshapeDesc.m_TargetShape = outputInfo.GetShape();
-
- bool isSupported = false;
- FORWARD_LAYER_SUPPORT_FUNC(__func__,
- IsReshapeSupported,
- data.m_Backends,
- isSupported,
- inputInfo,
- reshapeDesc);
- if (!isSupported)
- {
- return false;
- }
-
- armnn::IConnectableLayer* const layer = data.m_Network->AddReshapeLayer(reshapeDesc);
- assert(layer != nullptr);
- input.Connect(layer->GetInputSlot(0));
-
- return SetupAndTrackLayerOutputSlot<hal_1_1::HalPolicy>(operation, 0, *layer, model, data);
+ return ::ConvertSqueeze<hal_1_1::HalPolicy>(operation, model, data);
}
bool HalPolicy::ConvertStridedSlice(const Operation& operation, const Model& model, ConversionData& data)
{
ALOGV("hal_1_1::HalPolicy::ConvertStridedSlice()");
-
- LayerInputHandle input = ConvertToLayerInputHandle<hal_1_1::HalPolicy>(operation, 0, model, data);
- if (!input.IsValid())
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- const armnn::TensorInfo& inputInfo = input.GetTensorInfo();
- unsigned int rank = inputInfo.GetNumDimensions();
- if (rank > 4)
- {
- Fail("%s: Inputs with rank greater than 4 are not supported", __func__);
- }
-
- const Operand* output = GetOutputOperand<hal_1_1::HalPolicy>(operation, 0, model);
- if (!output)
- {
- return Fail("%s: Could not read output 0", __func__);
- }
-
- const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
- if (IsDynamicTensor(outputInfo))
- {
- return Fail("%s: Dynamic output tensors are not supported", __func__);
- }
-
- const Operand* beginOperand = GetInputOperand<hal_1_1::HalPolicy>(operation, 1, model);
- const Operand* endOperand = GetInputOperand<hal_1_1::HalPolicy>(operation, 2, model);
- const Operand* stridesOperand = GetInputOperand<hal_1_1::HalPolicy>(operation, 3, model);
-
- std::vector<int32_t> beginValues;
- std::vector<int32_t> endValues;
- std::vector<int32_t> stridesValues;
-
- // The length of the beginOperand, endOperand and stridesOperand must be of a rank(input)
- auto ValidateInputOperands = [&] (const Operand& operand, std::vector<int32_t>& operandValues)
- {
- if (!GetTensorInt32Values<hal_1_1::HalPolicy>(operand, operandValues, model, data))
- {
- return false;
- }
-
- if (operandValues.size() != rank)
- {
- return false;
- }
-
- return true;
- };
-
- if (!ValidateInputOperands(*beginOperand, beginValues)
- || !ValidateInputOperands(*endOperand, endValues)
- || !ValidateInputOperands(*stridesOperand, stridesValues))
- {
- return Fail("%s: Operation has invalid input operand", __func__);
- }
-
- // Stride cannot have value '0'
- if (std::any_of(stridesValues.cbegin(), stridesValues.cend(), [](int32_t i){ return i == 0; }))
- {
- return Fail("%s: Stride must be non-zero value.", __func__);
- }
-
- armnn::StridedSliceDescriptor descriptor;
- descriptor.m_Begin.assign(beginValues.cbegin(), beginValues.cend());
- descriptor.m_End.assign(endValues.cbegin(), endValues.cend());
- descriptor.m_Stride.assign(stridesValues.cbegin(), stridesValues.cend());
- descriptor.m_DataLayout = armnn::DataLayout::NHWC;
-
- // Get the "begin_mask", "end_mask", and "shrink_axis_mask" flags
- if (!GetInputInt32<hal_1_1::HalPolicy>(operation, 4, descriptor.m_BeginMask, model, data) ||
- !GetInputInt32<hal_1_1::HalPolicy>(operation, 5, descriptor.m_EndMask, model, data) ||
- !GetInputInt32<hal_1_1::HalPolicy>(operation, 6, descriptor.m_ShrinkAxisMask, model, data))
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- bool isSupported = false;
- FORWARD_LAYER_SUPPORT_FUNC(__func__,
- IsStridedSliceSupported,
- data.m_Backends,
- isSupported,
- inputInfo,
- outputInfo,
- descriptor);
- if (!isSupported)
- {
- return false;
- }
-
- armnn::IConnectableLayer* const layer = data.m_Network->AddStridedSliceLayer(descriptor);
- assert(layer != nullptr);
- input.Connect(layer->GetInputSlot(0));
-
- return SetupAndTrackLayerOutputSlot<hal_1_1::HalPolicy>(operation, 0, *layer, model, data);
+ return ::ConvertStridedSlice<hal_1_1::HalPolicy>(operation, model, data);
}
bool HalPolicy::ConvertTranspose(const Operation& operation, const Model& model, ConversionData& data)
{
ALOGV("hal_1_1::HalPolicy::ConvertTranspose()");
-
- LayerInputHandle input = ConvertToLayerInputHandle<hal_1_1::HalPolicy>(operation, 0, model, data);
- if (!input.IsValid())
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- const armnn::TensorInfo& inputInfo = input.GetTensorInfo();
- unsigned int rank = inputInfo.GetNumDimensions();
- if (rank > 4)
- {
- Fail("%s: Inputs with rank greater than 4 are not supported", __func__);
- }
-
- // NOTE: Axis is an optional parameter to TRANSPOSE, therefore we do not want to generate a failure
- // if the operand index is out of bounds.
- const Operand* permOperand = GetInputOperand<hal_1_1::HalPolicy>(operation, 1, model, false);
-
- std::vector<int32_t> perm(rank);
- if (!permOperand)
- {
- // NOTE: If perm is not given, it is set to (n-1...0), where n is the rank of the tensor
- for (unsigned int i = rank; i > 0; i--)
- {
- perm[rank - i] = boost::numeric_cast<int> (i - 1);
- }
- }
- else
- {
- GetTensorInt32Values<hal_1_1::HalPolicy>(*permOperand, perm, model, data);
- }
-
- std::vector<uint32_t> outputDims(perm.begin(), perm.begin() + rank);
-
- auto permutationVector = armnn::PermutationVector(outputDims.data(), outputDims.size());
- if (!permutationVector.IsEqual(NHWCToArmNN)
- && !permutationVector.IsEqual(ArmNNToNHWC)
- && !permutationVector.IsEqual({ 3, 2, 0, 1 }))
- {
- return Fail("%s: Only [0, 3, 1, 2], [0, 2, 3, 1] and [3, 2, 0, 1] permutations are supported.", __func__);
- }
-
- armnn::PermuteDescriptor permuteDesc;
- permuteDesc.m_DimMappings = permutationVector;
-
- const Operand* output = GetOutputOperand<hal_1_1::HalPolicy>(operation, 0, model);
- if (!output)
- {
- return Fail("%s: Could not read output 0", __func__);
- }
-
- const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
-
- bool isSupported = false;
- FORWARD_LAYER_SUPPORT_FUNC(__func__,
- IsPermuteSupported,
- data.m_Backends,
- isSupported,
- inputInfo,
- outputInfo,
- permuteDesc);
- if (!isSupported)
- {
- return false;
- }
-
- armnn::IConnectableLayer* const layer = data.m_Network->AddPermuteLayer(permuteDesc);
- assert(layer != nullptr);
- input.Connect(layer->GetInputSlot(0));
-
- return SetupAndTrackLayerOutputSlot<hal_1_1::HalPolicy>(operation, 0, *layer, model, data);
+ return ::ConvertTranspose<hal_1_1::HalPolicy>(operation, model, data);
}
bool HalPolicy::ConvertBatchToSpaceNd(const Operation& operation, const Model& model, ConversionData& data)
diff --git a/1.2/HalPolicy.cpp b/1.2/HalPolicy.cpp
index c8e242e..7fe5f88 100644
--- a/1.2/HalPolicy.cpp
+++ b/1.2/HalPolicy.cpp
@@ -7,9 +7,6 @@
#include "Utils.hpp"
-#include "../1.0/HalPolicy.hpp"
-#include "../1.1/HalPolicy.hpp"
-
#include <DataLayoutIndexed.hpp>
#include <Half.hpp>
@@ -20,109 +17,12 @@
namespace hal_1_2
{
-bool HandledByV1_0(V1_2::OperationType operationType)
-{
- switch (static_cast<V1_0::OperationType>(operationType))
- {
- case V1_0::OperationType::ADD:
- case V1_0::OperationType::DEPTH_TO_SPACE:
- case V1_0::OperationType::DEQUANTIZE:
- case V1_0::OperationType::EMBEDDING_LOOKUP:
- case V1_0::OperationType::FLOOR:
- case V1_0::OperationType::FULLY_CONNECTED:
- case V1_0::OperationType::HASHTABLE_LOOKUP:
- case V1_0::OperationType::L2_NORMALIZATION:
- case V1_0::OperationType::LOCAL_RESPONSE_NORMALIZATION:
- case V1_0::OperationType::LOGISTIC:
- case V1_0::OperationType::LSH_PROJECTION:
- case V1_0::OperationType::MUL:
- case V1_0::OperationType::RESHAPE:
- case V1_0::OperationType::RNN:
- case V1_0::OperationType::SVDF:
- case V1_0::OperationType::OEM_OPERATION:
- return true;
- default:
- return false;
- }
-}
-
-bool HandledByV1_1(V1_2::OperationType operationType)
-{
- if (HandledByV1_0(operationType))
- {
- return true;
- }
- switch (static_cast<V1_1::OperationType>(operationType))
- {
- case V1_1::OperationType::DIV:
- case V1_1::OperationType::MEAN:
- case V1_1::OperationType::SQUEEZE:
- case V1_1::OperationType::STRIDED_SLICE:
- case V1_1::OperationType::TRANSPOSE:
- return true;
- default:
- return false;
- }
-}
-
-bool HandledByV1_0(const V1_2::Operation& operation)
-{
- return HandledByV1_0(operation.type);
-}
-
-bool HandledByV1_1(const V1_2::Operation& operation)
-{
- return HandledByV1_1(operation.type);
-}
-
-V1_0::OperationType CastToV1_0(V1_2::OperationType type)
-{
- return static_cast<V1_0::OperationType>(type);
-}
-
-V1_1::OperationType CastToV1_1(V1_2::OperationType type)
-{
- return static_cast<V1_1::OperationType>(type);
-}
-
-V1_0::Operation ConvertToV1_0(const V1_2::Operation& operation)
-{
- V1_0::Operation op;
- op.type = CastToV1_0(operation.type);
- op.inputs = operation.inputs;
- op.outputs = operation.outputs;
- return op;
-}
-
-V1_1::Operation ConvertToV1_1(const V1_2::Operation& operation)
-{
- V1_1::Operation op;
- op.type = CastToV1_1(operation.type);
- op.inputs = operation.inputs;
- op.outputs = operation.outputs;
- return op;
-}
-
bool HalPolicy::ConvertOperation(const Operation& operation, const Model& model, ConversionData& data)
{
- if (HandledByV1_0(operation) && compliantWithV1_0(model))
- {
- hal_1_0::HalPolicy::Operation v10Operation = ConvertToV1_0(operation);
- hal_1_0::HalPolicy::Model v10Model = convertToV1_0(model);
-
- return hal_1_0::HalPolicy::ConvertOperation(v10Operation, v10Model, data);
- }
-
- if (HandledByV1_1(operation) && compliantWithV1_1(model))
- {
- hal_1_1::HalPolicy::Operation v11Operation = ConvertToV1_1(operation);
- hal_1_1::HalPolicy::Model v11Model = convertToV1_1(model);
-
- return hal_1_1::HalPolicy::ConvertOperation(v11Operation, v11Model, data);
- }
-
switch (operation.type)
{
+ case V1_2::OperationType::ADD:
+ return ConvertAdd(operation, model, data);
case V1_2::OperationType::AVERAGE_POOL_2D:
return ConvertAveragePool2d(operation, model, data);
case V1_2::OperationType::BATCH_TO_SPACE_ND:
@@ -133,14 +33,34 @@
return ConvertConv2d(operation, model, data);
case V1_2::OperationType::DEPTHWISE_CONV_2D:
return ConvertDepthwiseConv2d(operation, model, data);
+ case V1_2::OperationType::DEQUANTIZE:
+ return ConvertDequantize(operation, model, data);
+ case V1_2::OperationType::DIV:
+ return ConvertDiv(operation, model, data);
+ case V1_2::OperationType::FLOOR:
+ return ConvertFloor(operation, model, data);
+ case V1_2::OperationType::FULLY_CONNECTED:
+ return ConvertFullyConnected(operation, model, data);
+ case V1_2::OperationType::L2_NORMALIZATION:
+ return ConvertL2Normalization(operation, model, data);
case V1_2::OperationType::L2_POOL_2D:
return ConvertL2Pool2d(operation, model, data);
+ case V1_2::OperationType::LOCAL_RESPONSE_NORMALIZATION:
+ return ConvertLocalResponseNormalization(operation, model, data);
+ case V1_2::OperationType::LOGISTIC:
+ return ConvertLogistic(operation, model, data);
+ case V1_2::OperationType::LSTM:
+ return ConvertLstm(operation, model, data);
case V1_2::OperationType::MAX_POOL_2D:
return ConvertMaxPool2d(operation, model, data);
case V1_2::OperationType::MAXIMUM:
return ConvertMaximum(operation, model, data);
+ case V1_2::OperationType::MEAN:
+ return ConvertMean(operation, model, data);
case V1_2::OperationType::MINIMUM:
return ConvertMinimum(operation, model, data);
+ case V1_2::OperationType::MUL:
+ return ConvertMul(operation, model, data);
case V1_2::OperationType::PAD:
return ConvertPad(operation, model, data);
case V1_2::OperationType::PAD_V2:
@@ -157,10 +77,18 @@
return ConvertReLu1(operation, model, data);
case V1_2::OperationType::RELU6:
return ConvertReLu6(operation, model, data);
+ case V1_2::OperationType::RESHAPE:
+ return ConvertReshape(operation, model, data);
case V1_2::OperationType::RESIZE_BILINEAR:
return ConvertResize(operation, model, data, armnn::ResizeMethod::Bilinear);
case V1_2::OperationType::RESIZE_NEAREST_NEIGHBOR:
return ConvertResize(operation, model, data, armnn::ResizeMethod::NearestNeighbor);
+ case V1_2::OperationType::SQUEEZE:
+ return ConvertSqueeze(operation, model, data);
+ case V1_2::OperationType::STRIDED_SLICE:
+ return ConvertStridedSlice(operation, model, data);
+ case V1_2::OperationType::TRANSPOSE:
+ return ConvertTranspose(operation, model, data);
case V1_2::OperationType::TRANSPOSE_CONV_2D:
return ConvertTransposeConv2d(operation, model, data);
case V1_2::OperationType::SOFTMAX:
@@ -173,14 +101,18 @@
return ConvertSub(operation, model, data);
case V1_2::OperationType::TANH:
return ConvertTanH(operation, model, data);
- case V1_2::OperationType::LSTM:
- return ConvertLstm(operation, model, data);
default:
return Fail("%s: Operation type %s not supported in ArmnnDriver",
__func__, toString(operation.type).c_str());
}
}
+bool HalPolicy::ConvertAdd(const Operation& operation, const Model& model, ConversionData& data)
+{
+ ALOGV("hal_1_2::HalPolicy::ConvertAdd()");
+ return ::ConvertAdd<hal_1_2::HalPolicy>(operation, model, data);
+}
+
bool HalPolicy::ConvertAveragePool2d(const Operation& operation, const Model& model, ConversionData& data)
{
ALOGV("hal_1_2::HalPolicy::ConvertAveragePool2d()");
@@ -517,12 +449,56 @@
return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, 0, *endLayer, model, data);
}
+bool HalPolicy::ConvertDequantize(const Operation& operation, const Model& model, ConversionData& data)
+{
+ ALOGV("hal_1_2::HalPolicy::ConvertDequantize()");
+ return ::ConvertDequantize<hal_1_2::HalPolicy>(operation, model, data);
+}
+
+bool HalPolicy::ConvertDiv(const Operation& operation, const Model& model, ConversionData& data)
+{
+ ALOGV("hal_1_2::HalPolicy::ConvertDiv()");
+ return ::ConvertDiv<hal_1_2::HalPolicy>(operation, model, data);
+}
+
+bool HalPolicy::ConvertFloor(const Operation& operation, const Model& model, ConversionData& data)
+{
+ ALOGV("hal_1_2::HalPolicy::ConvertFloor()");
+ return ::ConvertFloor<hal_1_2::HalPolicy>(operation, model, data);
+}
+
+bool HalPolicy::ConvertFullyConnected(const Operation& operation, const Model& model, ConversionData& data)
+{
+ ALOGV("hal_1_2::HalPolicy::ConvertFullyConnected()");
+ return ::ConvertFullyConnected<hal_1_2::HalPolicy>(operation, model, data);
+}
+
+bool HalPolicy::ConvertL2Normalization(const Operation& operation, const Model& model, ConversionData& data)
+{
+ ALOGV("hal_1_2::HalPolicy::ConvertL2Normalization()");
+ return ::ConvertL2Normalization<hal_1_2::HalPolicy>(operation, model, data);
+}
+
bool HalPolicy::ConvertL2Pool2d(const Operation& operation, const Model& model, ConversionData& data)
{
ALOGV("hal_1_2::HalPolicy::ConvertL2Pool2d()");
return ConvertPooling2d<hal_1_2::HalPolicy>(operation, __func__, armnn::PoolingAlgorithm::L2, model, data);
}
+bool HalPolicy::ConvertLocalResponseNormalization(const Operation& operation,
+ const Model& model,
+ ConversionData& data)
+{
+ ALOGV("hal_1_2::HalPolicy::ConvertLocalResponseNormalization()");
+ return ::ConvertLocalResponseNormalization<hal_1_2::HalPolicy>(operation, model, data);
+}
+
+bool HalPolicy::ConvertLogistic(const Operation& operation, const Model& model, ConversionData& data)
+{
+ ALOGV("hal_1_2::HalPolicy::ConvertLogistic()");
+ return ::ConvertLogistic<hal_1_2::HalPolicy>(operation, model, data);
+}
+
bool HalPolicy::ConvertMaxPool2d(const Operation& operation, const Model& model, ConversionData& data)
{
ALOGV("hal_1_2::HalPolicy::ConvertMaxPool2d()");
@@ -574,6 +550,12 @@
return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, 0, *layer, model, data);
}
+bool HalPolicy::ConvertMean(const Operation& operation, const Model& model, ConversionData& data)
+{
+ ALOGV("hal_1_2::HalPolicy::ConvertMean()");
+ return ::ConvertMean<hal_1_2::HalPolicy>(operation, model, data);
+}
+
bool HalPolicy::ConvertMinimum(const Operation& operation, const Model& model, ConversionData& data)
{
ALOGV("hal_1_2::HalPolicy::ConvertMinimum()");
@@ -619,6 +601,12 @@
return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, 0, *layer, model, data);
}
+bool HalPolicy::ConvertMul(const Operation& operation, const Model& model, ConversionData& data)
+{
+ ALOGV("hal_1_2::HalPolicy::ConvertMul()");
+ return ::ConvertMul<hal_1_2::HalPolicy>(operation, model, data);
+}
+
bool HalPolicy::ConvertPad(const Operation& operation, const Model& model, ConversionData& data)
{
ALOGV("hal_1_2::HalPolicy::ConvertPad()");
@@ -1039,6 +1027,12 @@
return ::ConvertReLu6<hal_1_2::HalPolicy>(operation, model, data);
}
+bool HalPolicy::ConvertReshape(const Operation& operation, const Model& model, ConversionData& data)
+{
+ ALOGV("hal_1_2::HalPolicy::ConvertReshape()");
+ return ::ConvertReshape<hal_1_2::HalPolicy>(operation, model, data);
+}
+
bool HalPolicy::ConvertResize(const Operation& operation,
const Model& model,
ConversionData& data,
@@ -1733,6 +1727,24 @@
SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, 3, *layer, 3, model, data));
}
+bool HalPolicy::ConvertSqueeze(const Operation& operation, const Model& model, ConversionData& data)
+{
+ ALOGV("hal_1_1::HalPolicy::ConvertSqueeze()");
+ return ::ConvertSqueeze<hal_1_2::HalPolicy>(operation, model, data);
+}
+
+bool HalPolicy::ConvertStridedSlice(const Operation& operation, const Model& model, ConversionData& data)
+{
+ ALOGV("hal_1_1::HalPolicy::ConvertStridedSlice()");
+ return ::ConvertStridedSlice<hal_1_2::HalPolicy>(operation, model, data);
+}
+
+bool HalPolicy::ConvertTranspose(const Operation& operation, const Model& model, ConversionData& data)
+{
+ ALOGV("hal_1_1::HalPolicy::ConvertTranspose()");
+ return ::ConvertTranspose<hal_1_2::HalPolicy>(operation, model, data);
+}
+
bool HalPolicy::ConvertTransposeConv2d(const Operation& operation, const Model& model, ConversionData& data)
{
LayerInputHandle input = ConvertToLayerInputHandle<hal_1_2::HalPolicy>(operation, 0, model, data);
diff --git a/1.2/HalPolicy.hpp b/1.2/HalPolicy.hpp
index a268b3d..4a785d9 100644
--- a/1.2/HalPolicy.hpp
+++ b/1.2/HalPolicy.hpp
@@ -31,6 +31,8 @@
static bool ConvertOperation(const Operation& operation, const Model& model, ConversionData& data);
private:
+ static bool ConvertAdd(const Operation& operation, const Model& model, ConversionData& data);
+
static bool ConvertAveragePool2d(const Operation& operation, const Model& model, ConversionData& data);
static bool ConvertBatchToSpaceNd(const Operation& operation, const Model& model, ConversionData& data);
@@ -41,14 +43,36 @@
static bool ConvertDepthwiseConv2d(const Operation& operation, const Model& model, ConversionData& data);
+ static bool ConvertDequantize(const Operation& operation, const Model& model, ConversionData& data);
+
+ static bool ConvertDiv(const Operation& operation, const Model& model, ConversionData& data);
+
+ static bool ConvertFloor(const Operation& operation, const Model& model, ConversionData& data);
+
+ static bool ConvertFullyConnected(const Operation& operation, const Model& model, ConversionData& data);
+
+ static bool ConvertL2Normalization(const Operation& operation, const Model& model, ConversionData& data);
+
static bool ConvertL2Pool2d(const Operation& operation, const Model& model, ConversionData& data);
+ static bool ConvertLocalResponseNormalization(const Operation& operation,
+ const Model& model,
+ ConversionData& data);
+
+ static bool ConvertLogistic(const Operation& operation, const Model& model, ConversionData& data);
+
+ static bool ConvertLstm(const Operation& operation, const Model& model, ConversionData& data);
+
static bool ConvertMaxPool2d(const Operation& operation, const Model& model, ConversionData& data);
static bool ConvertMaximum(const Operation& operation, const Model& model, ConversionData& data);
+ static bool ConvertMean(const Operation& operation, const Model& model, ConversionData& data);
+
static bool ConvertMinimum(const Operation& operation, const Model& model, ConversionData& data);
+ static bool ConvertMul(const Operation& operation, const Model& model, ConversionData& data);
+
static bool ConvertPad(const Operation& operation, const Model& model, ConversionData& data);
static bool ConvertPadV2(const Operation& operation, const Model& model, ConversionData& data);
@@ -65,6 +89,8 @@
static bool ConvertReLu6(const Operation& operation, const Model& model, ConversionData& data);
+ static bool ConvertReshape(const Operation& operation, const Model& model, ConversionData& data);
+
static bool ConvertResize(const Operation& operation,
const Model& model,
ConversionData& data,
@@ -76,11 +102,15 @@
static bool ConvertSpaceToDepth(const Operation& operation, const Model& model, ConversionData& data);
+ static bool ConvertSqueeze(const Operation& operation, const Model& model, ConversionData& data);
+
+ static bool ConvertStridedSlice(const Operation& operation, const Model& model, ConversionData& data);
+
static bool ConvertSub(const Operation& operation, const Model& model, ConversionData& data);
static bool ConvertTanH(const Operation& operation, const Model& model, ConversionData& data);
- static bool ConvertLstm(const Operation& operation, const Model& model, ConversionData& data);
+ static bool ConvertTranspose(const Operation& operation, const Model& model, ConversionData& data);
static bool ConvertTransposeConv2d(const Operation& operation, const Model& model, ConversionData& data);
};
diff --git a/ConversionUtils.hpp b/ConversionUtils.hpp
index 32efa54..cfbef5a 100644
--- a/ConversionUtils.hpp
+++ b/ConversionUtils.hpp
@@ -14,6 +14,8 @@
#include "armnn/src/armnnUtils/DataLayoutIndexed.hpp"
#include "armnn/src/armnnUtils/Permute.hpp"
+#include "1.0/FullyConnected.hpp"
+
#include <ActivationFunctor.h>
#include <CpuExecutor.h>
#include <OperationsUtils.h>
@@ -341,6 +343,20 @@
return shape;
}
+#ifdef ARMNN_ANDROID_NN_V1_2
+
+Shape GetOperandShape(const V1_2::Operand& operand)
+{
+ Shape shape;
+ shape.type = OperandType(operand.type);
+ shape.dimensions = operand.dimensions;
+ shape.scale = operand.scale;
+ shape.offset = operand.zeroPoint;
+ return shape;
+}
+
+#endif
+
// ArmNN requires the bias scale to be equal to the product of the weight and input scales, which is also
// what AndroidNN requires. However for some of the AndroidNN tests the values don't exactly match so
// we accept some tolerance. We don't want ArmNN itself to accept these inconsistencies as it is up to the
@@ -1420,6 +1436,71 @@
template<typename HalPolicy,
typename Operation = typename HalPolicy::Operation,
typename Model = typename HalPolicy::Model>
+bool ConvertAdd(const Operation& operation, const Model& model, ConversionData& data)
+{
+ using Operand = typename HalPolicy::Operand;
+
+ LayerInputHandle input0 = ConvertToLayerInputHandle<HalPolicy>(operation, 0, model, data);
+ LayerInputHandle input1 = ConvertToLayerInputHandle<HalPolicy>(operation, 1, model, data);
+
+ if (!input0.IsValid() || !input1.IsValid())
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
+
+ // The FuseActivation parameter is always the input index 2
+ // and it should be optional
+ ActivationFn activationFunction;
+ if (!GetOptionalInputActivation<HalPolicy>(operation, 2, activationFunction, model, data))
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
+
+ const Operand* outputOperand = GetOutputOperand<HalPolicy>(operation, 0, model);
+ if (!outputOperand)
+ {
+ return false;
+ }
+
+ const armnn::TensorInfo& inputInfo0 = input0.GetTensorInfo();
+ const armnn::TensorInfo& inputInfo1 = input1.GetTensorInfo();
+
+ const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*outputOperand);
+ if (IsDynamicTensor(outputInfo))
+ {
+ return Fail("%s: Dynamic output tensors are not supported", __func__);
+ }
+
+ bool isSupported = false;
+ FORWARD_LAYER_SUPPORT_FUNC(__func__,
+ IsAdditionSupported,
+ data.m_Backends,
+ isSupported,
+ inputInfo0,
+ inputInfo1,
+ outputInfo);
+ if (!isSupported)
+ {
+ return false;
+ }
+
+ armnn::IConnectableLayer* const startLayer = data.m_Network->AddAdditionLayer();
+ armnn::IConnectableLayer* const endLayer = ProcessActivation(outputInfo, activationFunction, startLayer, data);
+
+ if (endLayer != nullptr)
+ {
+ BroadcastTensor(input0, input1, startLayer, *data.m_Network);
+ return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *endLayer, model, data);
+ }
+ else
+ {
+ return Fail("%s: ProcessActivation failed", __func__);
+ }
+}
+
+template<typename HalPolicy,
+ typename Operation = typename HalPolicy::Operation,
+ typename Model = typename HalPolicy::Model>
bool ConvertConcatenation(const Operation& operation, const Model& model, ConversionData& data)
{
using HalOperand = typename HalPolicy::Operand;
@@ -1918,11 +1999,549 @@
}
template<typename HalPolicy,
- typename HalOperation = typename HalPolicy::Operation,
- typename HalOperand = typename HalPolicy::Operand,
- typename HalModel = typename HalPolicy::Model>
-bool ConvertPad(HalOperation& operation, const HalModel& model, ConversionData& data)
+ typename Operation = typename HalPolicy::Operation,
+ typename Model = typename HalPolicy::Model>
+bool ConvertDequantize(const Operation& operation, const Model& model, ConversionData& data)
{
+ using Operand = typename HalPolicy::Operand;
+
+ LayerInputHandle input = ConvertToLayerInputHandle<HalPolicy>(operation, 0, model, data);
+ if (!input.IsValid())
+ {
+ return Fail("%s: Operation has invalid input", __func__);
+ }
+
+ const Operand* const outputOperand = GetOutputOperand<HalPolicy>(operation, 0, model);
+ if (!outputOperand)
+ {
+ return Fail("%s: Operation has invalid outputs", __func__);
+ }
+
+ const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*outputOperand);
+ if (IsDynamicTensor(outputInfo))
+ {
+ return Fail("%s: Dynamic output tensors are not supported", __func__);
+ }
+
+ bool isSupported = false;
+ FORWARD_LAYER_SUPPORT_FUNC(__func__,
+ IsDequantizeSupported,
+ data.m_Backends,
+ isSupported,
+ input.GetTensorInfo(),
+ GetTensorInfoForOperand(*outputOperand));
+ if (!isSupported)
+ {
+ return false;
+ }
+
+ armnn::IConnectableLayer* const layer = data.m_Network->AddDequantizeLayer();
+ assert(layer != nullptr);
+ input.Connect(layer->GetInputSlot(0));
+
+ return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data);
+}
+
+template<typename HalPolicy,
+ typename Operation = typename HalPolicy::Operation,
+ typename Model = typename HalPolicy::Model>
+bool ConvertDiv(const Operation& operation, const Model& model, ConversionData& data)
+{
+ using Operand = typename HalPolicy::Operand;
+
+ LayerInputHandle input0 = ConvertToLayerInputHandle<HalPolicy>(operation, 0, model, data);
+ LayerInputHandle input1 = ConvertToLayerInputHandle<HalPolicy>(operation, 1, model, data);
+
+ if (!input0.IsValid() || !input1.IsValid())
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
+
+ // The FuseActivation parameter is always the input index 2
+ // and it should be optional
+ ActivationFn activationFunction;
+ if (!GetOptionalInputActivation<HalPolicy>(operation, 2, activationFunction, model, data))
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
+
+ const Operand* output = GetOutputOperand<HalPolicy>(operation, 0, model);
+ if (!output)
+ {
+ return Fail("%s: Could not read output 0", __func__);
+ }
+
+ const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
+ if (IsDynamicTensor(outputInfo))
+ {
+ return Fail("%s: Dynamic output tensors are not supported", __func__);
+ }
+
+ bool isSupported = false;
+ FORWARD_LAYER_SUPPORT_FUNC(__func__,
+ IsDivisionSupported,
+ data.m_Backends,
+ isSupported,
+ input0.GetTensorInfo(),
+ input1.GetTensorInfo(),
+ outputInfo);
+ if (!isSupported)
+ {
+ return false;
+ }
+
+ armnn::IConnectableLayer* const startLayer = data.m_Network->AddDivisionLayer();
+ armnn::IConnectableLayer* const endLayer = ProcessActivation(outputInfo, activationFunction, startLayer, data);
+
+ if (endLayer)
+ {
+ BroadcastTensor(input0, input1, startLayer, *data.m_Network);
+ return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *endLayer, model, data);
+ }
+ return Fail("%s: ProcessActivation failed", __func__);
+}
+
+template<typename HalPolicy,
+ typename Operation = typename HalPolicy::Operation,
+ typename Model = typename HalPolicy::Model>
+bool ConvertFloor(const Operation& operation, const Model& model, ConversionData& data)
+{
+ using Operand = typename HalPolicy::Operand;
+
+ LayerInputHandle input = ConvertToLayerInputHandle<HalPolicy>(operation, 0, model, data);
+ if (!input.IsValid())
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
+
+ const Operand* const outputOperand = GetOutputOperand<HalPolicy>(operation, 0, model);
+ if (!outputOperand)
+ {
+ return Fail("%s: Operation has invalid outputs", __func__);
+ }
+
+ const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*outputOperand);
+ if (IsDynamicTensor(outputInfo))
+ {
+ return Fail("%s: Dynamic output tensors are not supported", __func__);
+ }
+
+ bool isSupported = false;
+ FORWARD_LAYER_SUPPORT_FUNC(__func__,
+ IsFloorSupported,
+ data.m_Backends,
+ isSupported,
+ input.GetTensorInfo(),
+ outputInfo);
+ if (!isSupported)
+ {
+ return false;
+ }
+
+ armnn::IConnectableLayer* layer = data.m_Network->AddFloorLayer();
+ assert(layer != nullptr);
+ input.Connect(layer->GetInputSlot(0));
+
+ return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data);
+}
+
+template<typename HalPolicy,
+ typename Operation = typename HalPolicy::Operation,
+ typename Model = typename HalPolicy::Model>
+bool ConvertFullyConnected(const Operation& operation, const Model& model, ConversionData& data)
+{
+ using Operand = typename HalPolicy::Operand;
+
+ LayerInputHandle input = ConvertToLayerInputHandle<HalPolicy>(operation, 0, model, data);
+ if (!input.IsValid())
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
+
+ const Operand* output = GetOutputOperand<HalPolicy>(operation, 0, model);
+ if (!output)
+ {
+ return Fail("%s: Could not read output 0", __func__);
+ }
+
+ const armnn::TensorInfo& inputInfo = input.GetTensorInfo();
+ const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
+
+ if (IsDynamicTensor(outputInfo))
+ {
+ return Fail("%s: Dynamic output tensors are not supported", __func__);
+ }
+
+ // ArmNN does not currently support non-fixed weights or bias
+ ConstTensorPin weightsPin =
+ ConvertOperationInputToConstTensorPin<HalPolicy>(operation, 1, model, data); // 2D
+ ConstTensorPin biasPin =
+ ConvertOperationInputToConstTensorPin<HalPolicy>(operation, 2, model, data); // 1D
+
+ if (!weightsPin.IsValid() || !biasPin.IsValid())
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
+
+ armnn::ConstTensor weights = weightsPin.GetConstTensor();
+ armnn::ConstTensor bias = biasPin.GetConstTensor();
+ armnn::TensorInfo reshapedInfo = inputInfo;
+
+ try
+ {
+ reshapedInfo.SetShape(FlattenFullyConnectedInput(inputInfo.GetShape(), weights.GetInfo().GetShape()));
+ } catch (const std::exception &e) {
+ return Fail("%s: %s", __func__, e.what());
+ }
+
+ // ensuring that the bias value is within 1% of the weights input (small float differences can exist)
+ SanitizeBiasQuantizationScale(bias.GetInfo(), weights.GetInfo(), reshapedInfo);
+
+ ActivationFn activationFunction;
+ if (!GetInputActivationFunction<HalPolicy>(operation, 3, activationFunction, model, data))
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
+
+ armnn::FullyConnectedDescriptor desc;
+ desc.m_TransposeWeightMatrix = true;
+ desc.m_BiasEnabled = true;
+
+ bool isSupported = false;
+ FORWARD_LAYER_SUPPORT_FUNC(__func__,
+ IsFullyConnectedSupported,
+ data.m_Backends,
+ isSupported,
+ reshapedInfo,
+ outputInfo,
+ weights.GetInfo(),
+ bias.GetInfo(),
+ desc);
+ if (!isSupported)
+ {
+ return false;
+ }
+
+ armnn::IConnectableLayer* startLayer =
+ data.m_Network->AddFullyConnectedLayer(desc, weights, armnn::Optional<armnn::ConstTensor>(bias));
+ armnn::IConnectableLayer* endLayer = ProcessActivation(outputInfo, activationFunction, startLayer, data);
+
+ if (endLayer != nullptr)
+ {
+ if (inputInfo.GetNumDimensions() > 2U)
+ {
+ armnn::ReshapeDescriptor reshapeDescriptor;
+ reshapeDescriptor.m_TargetShape = reshapedInfo.GetShape();
+
+ armnn::IConnectableLayer* reshapeLayer = data.m_Network->AddReshapeLayer(reshapeDescriptor);
+ assert(reshapeLayer != nullptr);
+ input.Connect(reshapeLayer->GetInputSlot(0));
+ reshapeLayer->GetOutputSlot(0).SetTensorInfo(reshapedInfo);
+ reshapeLayer->GetOutputSlot(0).Connect(startLayer->GetInputSlot(0));
+ }
+ else
+ {
+ input.Connect(startLayer->GetInputSlot(0));
+ }
+
+ return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *endLayer, model, data);
+ }
+ else
+ {
+ return Fail("%s: ProcessActivation failed", __func__);
+ }
+}
+
+template<typename HalPolicy,
+ typename Operation = typename HalPolicy::Operation,
+ typename Model = typename HalPolicy::Model>
+bool ConvertL2Normalization(const Operation& operation, const Model& model, ConversionData& data)
+{
+ using Operand = typename HalPolicy::Operand;
+
+ LayerInputHandle input = ConvertToLayerInputHandle<HalPolicy>(operation, 0, model, data);
+ if (!input.IsValid())
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
+
+ const Operand* output = GetOutputOperand<HalPolicy>(operation, 0, model);
+ if (!output)
+ {
+ return Fail("%s: Could not read output 0", __func__);
+ }
+
+ const armnn::TensorInfo& inputInfo = input.GetTensorInfo();
+ const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
+
+ if (IsDynamicTensor(outputInfo))
+ {
+ return Fail("%s: Dynamic output tensors are not supported", __func__);
+ }
+ if (outputInfo.GetNumDimensions() != 4u)
+ {
+ return Fail("%s: Tensor Rank other than 4 is not supported", __func__);
+ }
+
+ armnn::L2NormalizationDescriptor desc;
+ desc.m_DataLayout = armnn::DataLayout::NHWC;
+
+ bool isSupported = false;
+ FORWARD_LAYER_SUPPORT_FUNC(__func__,
+ IsL2NormalizationSupported,
+ data.m_Backends,
+ isSupported,
+ inputInfo,
+ outputInfo,
+ desc);
+ if (!isSupported)
+ {
+ return false;
+ }
+
+ armnn::IConnectableLayer* layer = data.m_Network->AddL2NormalizationLayer(desc);
+ assert(layer != nullptr);
+ input.Connect(layer->GetInputSlot(0));
+
+ return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data);
+}
+
+template<typename HalPolicy,
+ typename Operation = typename HalPolicy::Operation,
+ typename Model = typename HalPolicy::Model>
+bool ConvertLocalResponseNormalization(const Operation& operation,
+ const Model& model,
+ ConversionData& data)
+{
+ using Operand = typename HalPolicy::Operand;
+ using OperandType = typename HalPolicy::OperandType;
+
+ LayerInputHandle input = ConvertToLayerInputHandle<HalPolicy>(operation, 0, model, data);
+ if (!input.IsValid())
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
+
+ const Operand* output = GetOutputOperand<HalPolicy>(operation, 0, model);
+ if (!output)
+ {
+ return Fail("%s: Could not read output 0", __func__);
+ }
+
+ const armnn::TensorInfo& inputInfo = input.GetTensorInfo();
+ const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
+
+ if (IsDynamicTensor(outputInfo))
+ {
+ return Fail("%s: Dynamic output tensors are not supported", __func__);
+ }
+ if (outputInfo.GetNumDimensions() != 4u)
+ {
+ return Fail("%s: Tensor Rank other than 4 is not supported", __func__);
+ }
+
+ armnn::NormalizationDescriptor descriptor;
+ descriptor.m_DataLayout = armnn::DataLayout::NHWC;
+ descriptor.m_NormChannelType = armnn::NormalizationAlgorithmChannel::Across;
+ descriptor.m_NormMethodType = armnn::NormalizationAlgorithmMethod::LocalBrightness;
+
+ if (!input.IsValid() ||
+ !GetInputScalar<HalPolicy>(operation, 1, OperandType::INT32, descriptor.m_NormSize, model, data) ||
+ !GetInputFloat32<HalPolicy>(operation, 2, descriptor.m_K, model, data) ||
+ !GetInputFloat32<HalPolicy>(operation, 3, descriptor.m_Alpha, model, data) ||
+ !GetInputFloat32<HalPolicy>(operation, 4, descriptor.m_Beta, model, data))
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
+
+ // ArmNN expects normSize to be the full size of the normalization
+ // window rather than the radius as in AndroidNN.
+ descriptor.m_NormSize = 1 + (2 * descriptor.m_NormSize);
+
+ bool isSupported = false;
+ FORWARD_LAYER_SUPPORT_FUNC(__func__,
+ IsNormalizationSupported,
+ data.m_Backends,
+ isSupported,
+ inputInfo,
+ outputInfo,
+ descriptor);
+ if (!isSupported)
+ {
+ return false;
+ }
+
+
+ armnn::IConnectableLayer* layer = data.m_Network->AddNormalizationLayer(descriptor);
+ assert(layer != nullptr);
+ input.Connect(layer->GetInputSlot(0));
+
+ return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data);
+}
+
+template<typename HalPolicy,
+ typename Operation = typename HalPolicy::Operation,
+ typename Model = typename HalPolicy::Model>
+bool ConvertLogistic(const Operation& operation, const Model& model, ConversionData& data)
+{
+ using Operand = typename HalPolicy::Operand;
+
+ armnn::ActivationDescriptor desc;
+ desc.m_Function = armnn::ActivationFunction::Sigmoid;
+
+ return ConvertToActivation<HalPolicy>(operation, __func__, desc, model, data);
+}
+
+template<typename HalPolicy,
+ typename Operation = typename HalPolicy::Operation,
+ typename Model = typename HalPolicy::Model>
+bool ConvertMean(const Operation& operation, const Model& model, ConversionData& data)
+{
+ using Operand = typename HalPolicy::Operand;
+
+ LayerInputHandle input = ConvertToLayerInputHandle<HalPolicy>(operation, 0, model, data);
+ if (!input.IsValid())
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
+
+ const Operand* output = GetOutputOperand<HalPolicy>(operation, 0, model);
+ if (!output)
+ {
+ return Fail("%s: Could not read output 0", __func__);
+ }
+
+ const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
+ if (IsDynamicTensor(outputInfo))
+ {
+ return Fail("%s: Dynamic output tensors are not supported", __func__);
+ }
+
+ const Operand* axisOperand = GetInputOperand<HalPolicy>(operation, 1, model);
+ if (!axisOperand)
+ {
+ return Fail("%s: Could not read input 1", __func__);
+ }
+
+ std::vector<int32_t> axis;
+ if (!GetTensorInt32Values<HalPolicy>(*axisOperand, axis, model, data))
+ {
+ return Fail("%s: Input 1 has invalid values", __func__);
+ }
+
+ const armnn::TensorInfo& inputInfo = input.GetTensorInfo();
+
+ // Convert the axis to unsigned int and remove duplicates.
+ unsigned int rank = inputInfo.GetNumDimensions();
+ std::set<unsigned int> uniqueAxis;
+ std::transform(axis.begin(), axis.end(),
+ std::inserter(uniqueAxis, uniqueAxis.begin()),
+ [rank](int i) -> unsigned int { return (i + rank) % rank; });
+
+ // Get the "keep dims" flag.
+ int32_t keepDims = 0;
+ if (!GetInputInt32<HalPolicy>(operation, 2, keepDims, model, data))
+ {
+ return Fail("%s: Could not read input 2", __func__);
+ }
+
+ armnn::MeanDescriptor descriptor;
+ descriptor.m_Axis.assign(uniqueAxis.begin(), uniqueAxis.end());
+ descriptor.m_KeepDims = keepDims > 0;
+
+ bool isSupported = false;
+ FORWARD_LAYER_SUPPORT_FUNC(__func__,
+ IsMeanSupported,
+ data.m_Backends,
+ isSupported,
+ inputInfo,
+ outputInfo,
+ descriptor);
+ if (!isSupported)
+ {
+ return false;
+ }
+
+ armnn::IConnectableLayer* const layer = data.m_Network->AddMeanLayer(descriptor);
+ assert(layer != nullptr);
+ input.Connect(layer->GetInputSlot(0));
+
+ return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data);
+}
+
+template<typename HalPolicy,
+ typename Operation = typename HalPolicy::Operation,
+ typename Model = typename HalPolicy::Model>
+bool ConvertMul(const Operation& operation, const Model& model, ConversionData& data)
+{
+ using Operand = typename HalPolicy::Operand;
+
+ LayerInputHandle input0 = ConvertToLayerInputHandle<HalPolicy>(operation, 0, model, data);
+ LayerInputHandle input1 = ConvertToLayerInputHandle<HalPolicy>(operation, 1, model, data);
+
+ if (!input0.IsValid() || !input1.IsValid())
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
+
+ // The FuseActivation parameter is always the input index 2
+ // and it should be optional
+ ActivationFn activationFunction;
+ if (!GetOptionalInputActivation<HalPolicy>(operation, 2, activationFunction, model, data))
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
+
+ const Operand* outputOperand = GetOutputOperand<HalPolicy>(operation, 0, model);
+
+ if (outputOperand == nullptr)
+ {
+ return false;
+ }
+
+ const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*outputOperand);
+ if (IsDynamicTensor(outputInfo))
+ {
+ return Fail("%s: Dynamic output tensors are not supported", __func__);
+ }
+
+ bool isSupported = false;
+ FORWARD_LAYER_SUPPORT_FUNC(__func__,
+ IsMultiplicationSupported,
+ data.m_Backends,
+ isSupported,
+ input0.GetTensorInfo(),
+ input1.GetTensorInfo(),
+ outputInfo);
+ if (!isSupported)
+ {
+ return false;
+ }
+
+ armnn::IConnectableLayer* const startLayer = data.m_Network->AddMultiplicationLayer();
+ armnn::IConnectableLayer* const endLayer = ProcessActivation(outputInfo, activationFunction, startLayer, data);
+
+ const armnn::TensorInfo& inputTensorInfo0 = input0.GetTensorInfo();
+ const armnn::TensorInfo& inputTensorInfo1 = input1.GetTensorInfo();
+
+ if (endLayer != nullptr)
+ {
+ BroadcastTensor(input0, input1, startLayer, *data.m_Network);
+ return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *endLayer, model, data);
+ }
+ else
+ {
+ return Fail("%s: ProcessActivation failed", __func__);
+ }
+}
+
+template<typename HalPolicy,
+ typename Operation = typename HalPolicy::Operation,
+ typename Model = typename HalPolicy::Model>
+bool ConvertPad(Operation& operation, const Model& model, ConversionData& data)
+{
+ using Operand = typename HalPolicy::Operand;
+
LayerInputHandle input = ConvertToLayerInputHandle<HalPolicy>(operation, 0, model, data);
if (!input.IsValid())
{
@@ -1946,7 +2565,7 @@
descriptor.m_PadValue = inputInfo.GetQuantizationOffset();
}
- const HalOperand* output = GetOutputOperand<HalPolicy>(operation, 0, model);
+ const Operand* output = GetOutputOperand<HalPolicy>(operation, 0, model);
if (!output)
{
return Fail("%s: Could not read output", __func__);
@@ -1981,10 +2600,86 @@
template<typename HalPolicy,
typename Operation = typename HalPolicy::Operation,
- typename Operand = typename HalPolicy::Operand,
+ typename Model = typename HalPolicy::Model>
+bool ConvertReshape(const Operation& operation, const Model& model, ConversionData& data)
+{
+ using Operand = typename HalPolicy::Operand;
+
+ const Operand* inputOperand = GetInputOperand<HalPolicy>(operation, 0, model);
+ const Operand* requestedShapeOperand = GetInputOperand<HalPolicy>(operation, 1, model);
+ const Operand* outputOperand = GetOutputOperand<HalPolicy>(operation, 0, model);
+
+ if (inputOperand == nullptr
+ || requestedShapeOperand == nullptr
+ || outputOperand == nullptr)
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
+
+ if (requestedShapeOperand->dimensions.size() != 1)
+ {
+ return Fail("%s: Input 1 expected to be one-dimensional (found %i dimensions)",
+ __func__, requestedShapeOperand->dimensions.size());
+ }
+
+ std::vector<int32_t> targetDimensions;
+ if (!GetTensorInt32Values<HalPolicy>(*requestedShapeOperand, targetDimensions, model, data))
+ {
+ return Fail("%s: Could not read values of input 1", __func__);
+ }
+
+ const Shape inputOperandShape = GetOperandShape(*inputOperand);
+
+ Shape requestedShape;
+ // targetDimensions may contain special values (e.g. -1). reshapePrepare() is an AndroidNN provided utility
+ // function that resolves these values into a fully specified tensor shape.
+ if (!reshapePrepare(inputOperandShape, targetDimensions.data(), targetDimensions.size(), &requestedShape))
+ {
+ return Fail("%s: Failed to resolve the requested shape", __func__);
+ }
+
+ const Shape outputOperandShape = GetOperandShape(*outputOperand);
+ if (!SameShape(requestedShape, outputOperandShape))
+ {
+ return Fail("%s: Shape of output operand does not match resolved requested shape", __func__);
+ }
+
+ LayerInputHandle input = ConvertToLayerInputHandle<HalPolicy>(operation, 0, model, data);
+ if (!input.IsValid())
+ {
+ return Fail("%s: Could not read input 0", __func__);
+ }
+
+ armnn::ReshapeDescriptor reshapeDescriptor;
+ reshapeDescriptor.m_TargetShape = armnn::TensorShape(requestedShape.dimensions.size(),
+ requestedShape.dimensions.data());
+
+ bool isSupported = false;
+ FORWARD_LAYER_SUPPORT_FUNC(__func__,
+ IsReshapeSupported,
+ data.m_Backends,
+ isSupported,
+ input.GetTensorInfo(),
+ reshapeDescriptor);
+ if (!isSupported)
+ {
+ return false;
+ }
+
+ armnn::IConnectableLayer* layer = data.m_Network->AddReshapeLayer(reshapeDescriptor);
+ assert(layer != nullptr);
+ input.Connect(layer->GetInputSlot(0));
+
+ return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data);
+}
+
+template<typename HalPolicy,
+ typename Operation = typename HalPolicy::Operation,
typename Model = typename HalPolicy::Model>
bool ConvertSub(const Operation& operation, const Model& model, ConversionData& data)
{
+ using Operand = typename HalPolicy::Operand;
+
LayerInputHandle input0 = ConvertToLayerInputHandle<HalPolicy>(operation, 0, model, data);
LayerInputHandle input1 = ConvertToLayerInputHandle<HalPolicy>(operation, 1, model, data);
@@ -2042,6 +2737,274 @@
}
template<typename HalPolicy,
+ typename Operation = typename HalPolicy::Operation,
+ typename Model = typename HalPolicy::Model>
+bool ConvertSqueeze(const Operation& operation, const Model& model, ConversionData& data)
+{
+ using Operand = typename HalPolicy::Operand;
+
+ LayerInputHandle input = ConvertToLayerInputHandle<HalPolicy>(operation, 0, model, data);
+ if (!input.IsValid())
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
+
+ const armnn::TensorInfo& inputInfo = input.GetTensorInfo();
+ unsigned int rank = inputInfo.GetNumDimensions();
+ if (rank > 4)
+ {
+ Fail("%s: Inputs with rank greater than 4 are not supported", __func__);
+ }
+
+ const Operand* output = GetOutputOperand<HalPolicy>(operation, 0, model);
+ if (!output)
+ {
+ return Fail("%s: Could not read output 0", __func__);
+ }
+
+ if (IsDynamicTensor(GetTensorInfoForOperand(*output)))
+ {
+ return Fail("%s: Dynamic output tensors are not supported", __func__);
+ }
+
+ // NOTE: Axis is an optional parameter to SQUEEZE, therefore we do not want to generate a failure
+ // if the operand index is out of bounds.
+ const Operand* axisOperand = GetInputOperand<HalPolicy>(operation, 1, model, false);
+
+ const uint32_t dimensionSequence[] = { 0, 1, 2, 3 };
+
+ std::vector<int32_t> axis;
+ if (!axisOperand)
+ {
+ axis.assign(dimensionSequence,
+ dimensionSequence + rank);
+ }
+ else
+ {
+ GetTensorInt32Values<HalPolicy>(*axisOperand, axis, model, data);
+ }
+
+ std::vector<uint32_t> outputDims;
+ for (unsigned int i = 0; i < rank; i++)
+ {
+ bool skipSqueeze = (std::find(axis.begin(), axis.end(), i) == axis.end());
+ auto currentDimension = inputInfo.GetShape()[i];
+ if (skipSqueeze || currentDimension != 1)
+ {
+ outputDims.push_back(currentDimension);
+ }
+ }
+
+ armnn::TensorShape outShape = armnn::TensorShape(outputDims.size(), outputDims.data());
+
+ armnn::TensorInfo outputInfo = inputInfo;
+ outputInfo.SetShape(outShape);
+
+ armnn::ReshapeDescriptor reshapeDesc;
+ reshapeDesc.m_TargetShape = outputInfo.GetShape();
+
+ bool isSupported = false;
+ FORWARD_LAYER_SUPPORT_FUNC(__func__,
+ IsReshapeSupported,
+ data.m_Backends,
+ isSupported,
+ inputInfo,
+ reshapeDesc);
+ if (!isSupported)
+ {
+ return false;
+ }
+
+ armnn::IConnectableLayer* const layer = data.m_Network->AddReshapeLayer(reshapeDesc);
+ assert(layer != nullptr);
+ input.Connect(layer->GetInputSlot(0));
+
+ return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data);
+}
+
+template<typename HalPolicy,
+ typename Operation = typename HalPolicy::Operation,
+ typename Model = typename HalPolicy::Model>
+bool ConvertStridedSlice(const Operation& operation, const Model& model, ConversionData& data)
+{
+ using Operand = typename HalPolicy::Operand;
+
+ LayerInputHandle input = ConvertToLayerInputHandle<HalPolicy>(operation, 0, model, data);
+ if (!input.IsValid())
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
+
+ const armnn::TensorInfo& inputInfo = input.GetTensorInfo();
+ unsigned int rank = inputInfo.GetNumDimensions();
+ if (rank > 4)
+ {
+ Fail("%s: Inputs with rank greater than 4 are not supported", __func__);
+ }
+
+ const Operand* output = GetOutputOperand<HalPolicy>(operation, 0, model);
+ if (!output)
+ {
+ return Fail("%s: Could not read output 0", __func__);
+ }
+
+ const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
+ if (IsDynamicTensor(outputInfo))
+ {
+ return Fail("%s: Dynamic output tensors are not supported", __func__);
+ }
+
+ const Operand* beginOperand = GetInputOperand<HalPolicy>(operation, 1, model);
+ const Operand* endOperand = GetInputOperand<HalPolicy>(operation, 2, model);
+ const Operand* stridesOperand = GetInputOperand<HalPolicy>(operation, 3, model);
+
+ std::vector<int32_t> beginValues;
+ std::vector<int32_t> endValues;
+ std::vector<int32_t> stridesValues;
+
+ // The length of the beginOperand, endOperand and stridesOperand must be of a rank(input)
+ auto ValidateInputOperands = [&] (const Operand& operand, std::vector<int32_t>& operandValues)
+ {
+ if (!GetTensorInt32Values<HalPolicy>(operand, operandValues, model, data))
+ {
+ return false;
+ }
+
+ if (operandValues.size() != rank)
+ {
+ return false;
+ }
+
+ return true;
+ };
+
+ if (!ValidateInputOperands(*beginOperand, beginValues)
+ || !ValidateInputOperands(*endOperand, endValues)
+ || !ValidateInputOperands(*stridesOperand, stridesValues))
+ {
+ return Fail("%s: Operation has invalid input operand", __func__);
+ }
+
+ // Stride cannot have value '0'
+ if (std::any_of(stridesValues.cbegin(), stridesValues.cend(), [](int32_t i){ return i == 0; }))
+ {
+ return Fail("%s: Stride must be non-zero value.", __func__);
+ }
+
+ armnn::StridedSliceDescriptor descriptor;
+ descriptor.m_Begin.assign(beginValues.cbegin(), beginValues.cend());
+ descriptor.m_End.assign(endValues.cbegin(), endValues.cend());
+ descriptor.m_Stride.assign(stridesValues.cbegin(), stridesValues.cend());
+ descriptor.m_DataLayout = armnn::DataLayout::NHWC;
+
+ // Get the "begin_mask", "end_mask", and "shrink_axis_mask" flags
+ if (!GetInputInt32<HalPolicy>(operation, 4, descriptor.m_BeginMask, model, data) ||
+ !GetInputInt32<HalPolicy>(operation, 5, descriptor.m_EndMask, model, data) ||
+ !GetInputInt32<HalPolicy>(operation, 6, descriptor.m_ShrinkAxisMask, model, data))
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
+
+ bool isSupported = false;
+ FORWARD_LAYER_SUPPORT_FUNC(__func__,
+ IsStridedSliceSupported,
+ data.m_Backends,
+ isSupported,
+ inputInfo,
+ outputInfo,
+ descriptor);
+ if (!isSupported)
+ {
+ return false;
+ }
+
+ armnn::IConnectableLayer* const layer = data.m_Network->AddStridedSliceLayer(descriptor);
+ assert(layer != nullptr);
+ input.Connect(layer->GetInputSlot(0));
+
+ return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data);
+}
+
+template<typename HalPolicy,
+ typename Operation = typename HalPolicy::Operation,
+ typename Model = typename HalPolicy::Model>
+bool ConvertTranspose(const Operation& operation, const Model& model, ConversionData& data)
+{
+ using Operand = typename HalPolicy::Operand;
+
+ LayerInputHandle input = ConvertToLayerInputHandle<HalPolicy>(operation, 0, model, data);
+ if (!input.IsValid())
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
+
+ const armnn::TensorInfo& inputInfo = input.GetTensorInfo();
+ unsigned int rank = inputInfo.GetNumDimensions();
+ if (rank > 4)
+ {
+ Fail("%s: Inputs with rank greater than 4 are not supported", __func__);
+ }
+
+ // NOTE: Axis is an optional parameter to TRANSPOSE, therefore we do not want to generate a failure
+ // if the operand index is out of bounds.
+ const Operand* permOperand = GetInputOperand<HalPolicy>(operation, 1, model, false);
+
+ std::vector<int32_t> perm(rank);
+ if (!permOperand)
+ {
+ // NOTE: If perm is not given, it is set to (n-1...0), where n is the rank of the tensor
+ for (unsigned int i = rank; i > 0; i--)
+ {
+ perm[rank - i] = boost::numeric_cast<int> (i - 1);
+ }
+ }
+ else
+ {
+ GetTensorInt32Values<HalPolicy>(*permOperand, perm, model, data);
+ }
+
+ std::vector<uint32_t> outputDims(perm.begin(), perm.begin() + rank);
+
+ auto permutationVector = armnn::PermutationVector(outputDims.data(), outputDims.size());
+ if (!permutationVector.IsEqual(NHWCToArmNN)
+ && !permutationVector.IsEqual(ArmNNToNHWC)
+ && !permutationVector.IsEqual({ 3, 2, 0, 1 }))
+ {
+ return Fail("%s: Only [0, 3, 1, 2], [0, 2, 3, 1] and [3, 2, 0, 1] permutations are supported.", __func__);
+ }
+
+ armnn::PermuteDescriptor permuteDesc;
+ permuteDesc.m_DimMappings = permutationVector;
+
+ const Operand* output = GetOutputOperand<HalPolicy>(operation, 0, model);
+ if (!output)
+ {
+ return Fail("%s: Could not read output 0", __func__);
+ }
+
+ const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
+
+ bool isSupported = false;
+ FORWARD_LAYER_SUPPORT_FUNC(__func__,
+ IsPermuteSupported,
+ data.m_Backends,
+ isSupported,
+ inputInfo,
+ outputInfo,
+ permuteDesc);
+ if (!isSupported)
+ {
+ return false;
+ }
+
+ armnn::IConnectableLayer* const layer = data.m_Network->AddPermuteLayer(permuteDesc);
+ assert(layer != nullptr);
+ input.Connect(layer->GetInputSlot(0));
+
+ return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data);
+}
+
+template<typename HalPolicy,
typename HalOperation = typename HalPolicy::Operation,
typename HalOperand = typename HalPolicy::Operand,
typename HalModel = typename HalPolicy::Model>