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-rw-r--r--ConversionUtils.hpp750
1 files changed, 353 insertions, 397 deletions
diff --git a/ConversionUtils.hpp b/ConversionUtils.hpp
index 439d4a4a..2e3a0424 100644
--- a/ConversionUtils.hpp
+++ b/ConversionUtils.hpp
@@ -1,5 +1,5 @@
//
-// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
+// Copyright © 2017-2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
@@ -8,9 +8,7 @@
#include "Utils.hpp"
#include <armnn/ArmNN.hpp>
-#include <armnn/ILayerSupport.hpp>
#include <armnn/BackendHelper.hpp>
-#include <armnn/utility/Assert.hpp>
#include <armnn/utility/IgnoreUnused.hpp>
#include <armnn/utility/NumericCast.hpp>
@@ -73,6 +71,9 @@ public:
const armnn::TensorInfo& GetTensorInfo() const;
+ void SanitizeQuantizationScale(LayerInputHandle& weight,
+ LayerInputHandle& input);
+
private:
armnn::IOutputSlot* m_OutputSlot;
bool m_Valid;
@@ -90,7 +91,7 @@ public:
// @param valueStart Start address of tensor data. Belongs to one of the memory pools associated with
// the model being converted.
// @param numBytes Number of bytes for the tensor data.
- ConstTensorPin(const armnn::TensorInfo& tensorInfo, const void* valueStart, uint32_t numBytes,
+ ConstTensorPin(armnn::TensorInfo& tensorInfo, const void* valueStart, uint32_t numBytes,
const armnn::PermutationVector& mappings);
ConstTensorPin(const ConstTensorPin& other) = delete;
@@ -137,7 +138,7 @@ static bool Fail(const char* formatStr, Args&&... args)
// Convenience macro to call an Is*Supported function and log caller name together with reason for lack of support.
// Called as: FORWARD_LAYER_SUPPORT_FUNC(__func__, Is*Supported, backends, a, b, c, d, e)
-#define FORWARD_LAYER_SUPPORT_FUNC(funcName, func, backends, supported, ...) \
+#define FORWARD_LAYER_SUPPORT_FUNC(funcName, func, backends, supported, setBackend, ...) \
try \
{ \
for (auto&& backendId : backends) \
@@ -150,6 +151,7 @@ try \
layerSupportObject.func(__VA_ARGS__, armnn::Optional<std::string&>(reasonIfUnsupported)); \
if (supported) \
{ \
+ setBackend = backendId; \
break; \
} \
else \
@@ -278,7 +280,10 @@ armnn::IConnectableLayer& AddReshapeLayer(armnn::INetwork& network,
reshapeDescriptor.m_TargetShape = reshapeInfo.GetShape();
armnn::IConnectableLayer* reshapeLayer = network.AddReshapeLayer(reshapeDescriptor);
- ARMNN_ASSERT(reshapeLayer != nullptr);
+ if (!reshapeLayer)
+ {
+ throw armnn::RuntimeException("ReshapeLayer is null");
+ }
// Attach the input layer to the reshape layer
inputLayer.Connect(reshapeLayer->GetInputSlot(0));
@@ -292,7 +297,10 @@ bool BroadcastTensor(LayerInputHandle& input0,
armnn::IConnectableLayer* startLayer,
ConversionData& data)
{
- ARMNN_ASSERT(startLayer != nullptr);
+ if (!startLayer)
+ {
+ throw armnn::RuntimeException("StartLayer is null");
+ }
const armnn::TensorInfo& inputInfo0 = input0.GetTensorInfo();
const armnn::TensorInfo& inputInfo1 = input1.GetTensorInfo();
@@ -335,10 +343,12 @@ bool BroadcastTensor(LayerInputHandle& input0,
armnn::ReshapeDescriptor reshapeDescriptor;
bool isSupported = false;
+ armnn::BackendId setBackend;
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsReshapeSupported,
data.m_Backends,
isSupported,
+ setBackend,
smallInfo,
reshapedInfo,
reshapeDescriptor);
@@ -347,8 +357,13 @@ bool BroadcastTensor(LayerInputHandle& input0,
return false;
}
- ARMNN_ASSERT(data.m_Network != nullptr);
+ if (!data.m_Network)
+ {
+ throw armnn::RuntimeException("Network is null");
+ }
+
armnn::IConnectableLayer& reshapeLayer = AddReshapeLayer(*data.m_Network, smallInputHandle, reshapedInfo);
+ reshapeLayer.SetBackendId(setBackend);
if (input0IsSmaller)
{
@@ -473,7 +488,8 @@ void SanitizeBiasQuantizationScale(armnn::TensorInfo& biasInfo,
std::transform(biasScales.begin(), biasScales.end(), biasScales.begin(), UpdateBiasScaleValue);
biasInfo.SetQuantizationScales(biasScales);
- biasInfo.SetQuantizationDim(weightInfo.GetQuantizationDim());
+ // bias is expected to be a 1d tensor, set qdim=0
+ biasInfo.SetQuantizationDim(0);
ALOGV("Bias quantization params have been updated for per-axis quantization");
}
@@ -494,7 +510,7 @@ void SanitizeBiasQuantizationScale(armnn::TensorInfo& biasInfo,
// 4D Tensor Permutations
const armnn::PermutationVector IdentityPermutation4D({ 0U, 1U, 2U, 3U });
const armnn::PermutationVector IdentityPermutation3D({ 0U, 1U, 2U });
-const armnn::PermutationVector SwapDim1And2({ 0U, 2U, 1U, 3U });
+const armnn::PermutationVector SwapDim2And3({ 0U, 1U, 3U, 2U });
// 3D Permutation Vectors
const armnn::PermutationVector RotateTensorLeft({ 1U, 2U, 0U });
@@ -506,9 +522,10 @@ armnn::IConnectableLayer& AddTransposeLayer(armnn::INetwork& network, OSlot& inp
{
// Add swizzle layer
armnn::IConnectableLayer* const layer = network.AddTransposeLayer(mappings);
-
- ARMNN_ASSERT(layer != nullptr);
-
+ if (!layer)
+ {
+ throw armnn::RuntimeException("TransposeLayer is null");
+ }
// Connect input to swizzle layer
input.Connect(layer->GetInputSlot(0));
@@ -570,7 +587,8 @@ bool RequiresReshape(armnn::TensorShape & inputShape)
void SwizzleInputs(armnn::INetwork& network,
std::vector<LayerInputHandle>& inputs,
std::vector<armnn::TensorShape>& inputShapes,
- const armnn::PermutationVector& mapping)
+ const armnn::PermutationVector& mapping,
+ std::vector<armnn::BackendId>& setBackends)
{
if (!mapping.IsEqual(IdentityPermutation4D))
{
@@ -579,6 +597,7 @@ void SwizzleInputs(armnn::INetwork& network,
{
// add swizzle layer
armnn::IConnectableLayer& swizzleLayer = AddTransposeLayer(network, inputs[i], mapping);
+ swizzleLayer.SetBackendId(setBackends[i]);
auto& outputSlot = swizzleLayer.GetOutputSlot(0);
auto& outputInfo = outputSlot.GetTensorInfo();
// replace inputs with the swizzled ones
@@ -596,6 +615,7 @@ bool TransposeInputTensors(ConversionData& data,
// If we have a IdentityPermutation4D or IdentityPermutation3D then we are not permuting
if (!mapping.IsEqual(IdentityPermutation4D) && !mapping.IsEqual(IdentityPermutation3D))
{
+ std::vector<armnn::BackendId> setBackendsVec;
armnn::TensorInfo outputTransposeInfo;
size_t nInputs = inputs.size();
for (size_t i=0; i<nInputs; ++i)
@@ -606,20 +626,23 @@ bool TransposeInputTensors(ConversionData& data,
outputTransposeInfo = armnnUtils::TransposeTensorShape(inputs[i].GetTensorInfo(), mapping);
bool isSupported = false;
+ armnn::BackendId setBackend;
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsTransposeSupported,
data.m_Backends,
isSupported,
+ setBackend,
inputs[i].GetTensorInfo(),
outputTransposeInfo,
transposeDesc);
+ setBackendsVec.push_back(setBackend);
if (!isSupported)
{
return false;
}
}
- SwizzleInputs(*data.m_Network, inputs, inputShapes, mapping);
+ SwizzleInputs(*data.m_Network, inputs, inputShapes, mapping, setBackendsVec);
}
return true;
}
@@ -630,15 +653,19 @@ bool CreateConcatPermutationParameters(const unsigned int numberOfDimensions,
std::pair<armnn::PermutationVector, armnn::PermutationVector> & permutationPair)
{
bool needPermute = false;
- ARMNN_ASSERT(numberOfDimensions >= 3);
+
+ if (numberOfDimensions < 3)
+ {
+ return Fail("%s: Invalid numberOfDimensions: %i < 3", __func__, numberOfDimensions);
+ }
// ArmNN uses Compute Library subtensors to perform concatenation
// This only works when concatenating along dimension 0, 1 or 3 for a 4-D tensor,
// or along dimension 0 or 2 for a 3-D tensor.
if (numberOfDimensions == 4 && concatDimension == 2)
{
- concatDimension = 1;
- permutationPair = std::make_pair(SwapDim1And2, SwapDim1And2);
+ concatDimension = 3;
+ permutationPair = std::make_pair(SwapDim2And3, SwapDim2And3);
needPermute = true;
}
else if (numberOfDimensions == 3 && concatDimension == 1)
@@ -696,13 +723,18 @@ const HalOperand* GetInputOperand(const HalOperation& operation,
{
if (failOnIndexOutOfBounds)
{
- Fail("%s: invalid input index: %i out of %i", __func__, inputIndex, operation.inputs.size());
+ Fail("%s: Invalid input index: %i out of %i", __func__, inputIndex, operation.inputs.size());
}
return nullptr;
}
// Model should have been validated beforehand
- ARMNN_ASSERT(operation.inputs[inputIndex] < getMainModel(model).operands.size());
+ if (operation.inputs[inputIndex] >= getMainModel(model).operands.size())
+ {
+ Fail("%s: invalid model index: %i >= %i", __func__, inputIndex, getMainModel(model).operands.size());
+ return nullptr;
+ }
+
return &getMainModel(model).operands[operation.inputs[inputIndex]];
}
@@ -721,8 +753,11 @@ const HalOperand* GetOutputOperand(const HalOperation& operation,
}
// Model should have been validated beforehand
- ARMNN_ASSERT(operation.outputs[outputIndex] < getMainModel(model).operands.size());
-
+ if (operation.inputs[outputIndex] >= getMainModel(model).operands.size())
+ {
+ Fail("%s: invalid model index: %i >= %i", __func__, outputIndex, getMainModel(model).operands.size());
+ return nullptr;
+ }
return &getMainModel(model).operands[operation.outputs[outputIndex]];
}
@@ -843,11 +878,9 @@ ConstTensorPin ConvertOperandToConstTensorPin(const HalOperand& operand,
}
armnn::TensorInfo tensorInfo = GetTensorInfoForOperand(operand);
- // Android datalayout might be different than armnn datalayout, e.g. the kernel for the depthwise convolution.
- if (tensorInfo.HasPerAxisQuantization())
- {
- tensorInfo.SetQuantizationDim(dimensionMappings[tensorInfo.GetQuantizationDim().value()]);
- }
+
+ // Make sure isConstant flag is set.
+ tensorInfo.SetConstant();
if (overrideTensorShape != nullptr)
{
@@ -1166,7 +1199,8 @@ template<typename HalPolicy,
LayerInputHandle ConvertToLayerInputHandle(const HalOperation& operation,
uint32_t inputIndex,
const HalModel& model,
- ConversionData& data)
+ ConversionData& data,
+ const armnn::PermutationVector& dimensionMappings = g_DontPermute)
{
using HalOperand = typename HalPolicy::Operand;
using HalOperandType = typename HalPolicy::OperandType;
@@ -1205,6 +1239,7 @@ LayerInputHandle ConvertToLayerInputHandle(const HalOperation& operation,
IsInputSupported,
data.m_Backends,
isInputSupported,
+ armnn::BackendId(),
operandTensorInfo);
if (!isInputSupported)
@@ -1229,14 +1264,18 @@ LayerInputHandle ConvertToLayerInputHandle(const HalOperation& operation,
case HalOperandLifeTime::CONSTANT_REFERENCE:
{
// The tensor has an already known constant value, and can be converted into an ArmNN Constant layer.
- ConstTensorPin tensorPin = ConvertOperandToConstTensorPin<HalPolicy>(*operand, model, data);
+ ConstTensorPin tensorPin =
+ ConvertOperandToConstTensorPin<HalPolicy>(*operand, model, data, dimensionMappings);
+
if (tensorPin.IsValid())
{
bool isSupported = false;
+ armnn::BackendId setBackend;
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsConstantSupported,
data.m_Backends,
isSupported,
+ setBackend,
tensorPin.GetConstTensor().GetInfo());
if (!isSupported)
{
@@ -1245,17 +1284,18 @@ LayerInputHandle ConvertToLayerInputHandle(const HalOperation& operation,
armnn::IConnectableLayer* constantLayer =
data.m_Network->AddConstantLayer(tensorPin.GetConstTensor());
+ constantLayer->SetBackendId(setBackend);
armnn::IOutputSlot& outputSlot = constantLayer->GetOutputSlot(0);
- outputSlot.SetTensorInfo(tensorPin.GetConstTensor().GetInfo());
+ armnn::TensorInfo constantTensorInfo = tensorPin.GetConstTensor().GetInfo();
+ outputSlot.SetTensorInfo(constantTensorInfo);
- return LayerInputHandle(true, &outputSlot, operandTensorInfo);
+ return LayerInputHandle(true, &outputSlot, constantTensorInfo);
}
else
{
Fail("%s: invalid operand tensor", __func__);
return LayerInputHandle();
}
- break;
}
default:
{
@@ -1279,7 +1319,8 @@ template<typename HalPolicy>
LayerInputHandle ConvertToLayerInputHandle(const ::android::hardware::neuralnetworks::V1_3::Operation& operation,
uint32_t inputIndex,
const::android::hardware::neuralnetworks::V1_3::Model& model,
- ConversionData& data)
+ ConversionData& data,
+ const armnn::PermutationVector& dimensionMappings = g_DontPermute)
{
using HalOperand = typename HalPolicy::Operand;
using HalOperandType = typename HalPolicy::OperandType;
@@ -1332,6 +1373,7 @@ LayerInputHandle ConvertToLayerInputHandle(const ::android::hardware::neuralnetw
IsInputSupported,
data.m_Backends,
isInputSupported,
+ armnn::BackendId(),
operandTensorInfo);
if (!isInputSupported)
@@ -1356,14 +1398,18 @@ LayerInputHandle ConvertToLayerInputHandle(const ::android::hardware::neuralnetw
case HalOperandLifeTime::CONSTANT_REFERENCE:
{
// The tensor has an already known constant value, and can be converted into an ArmNN Constant layer.
- ConstTensorPin tensorPin = ConvertOperandToConstTensorPin<HalPolicy>(*operand, model, data);
+ ConstTensorPin tensorPin =
+ ConvertOperandToConstTensorPin<HalPolicy>(*operand, model, data, dimensionMappings);
+
if (tensorPin.IsValid())
{
bool isSupported = false;
+ armnn::BackendId setBackend;
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsConstantSupported,
data.m_Backends,
isSupported,
+ setBackend,
tensorPin.GetConstTensor().GetInfo());
if (!isSupported)
{
@@ -1372,10 +1418,12 @@ LayerInputHandle ConvertToLayerInputHandle(const ::android::hardware::neuralnetw
armnn::IConnectableLayer* constantLayer =
data.m_Network->AddConstantLayer(tensorPin.GetConstTensor());
+ constantLayer->SetBackendId(setBackend);
armnn::IOutputSlot& outputSlot = constantLayer->GetOutputSlot(0);
- outputSlot.SetTensorInfo(tensorPin.GetConstTensor().GetInfo());
+ armnn::TensorInfo constantTensorInfo = tensorPin.GetConstTensor().GetInfo();
+ outputSlot.SetTensorInfo(constantTensorInfo);
- return LayerInputHandle(true, &outputSlot, operandTensorInfo);
+ return LayerInputHandle(true, &outputSlot, constantTensorInfo);
}
else
{
@@ -1439,7 +1487,7 @@ bool SetupAndTrackLayerOutputSlot(const HalOperation& operation,
// Type one dynamic tensors require the previous layer's output shape for inference
for (unsigned int inputSlotIndex = 0; inputSlotIndex < layer.GetNumInputSlots(); ++inputSlotIndex)
{
- if(!layer.GetInputSlot(inputSlotIndex).GetConnection())
+ if (!layer.GetInputSlot(inputSlotIndex).GetConnection())
{
return false;
}
@@ -1569,13 +1617,14 @@ bool ConvertToActivation(const HalOperation& operation,
const armnn::TensorInfo& outInfo = GetTensorInfoForOperand(*outputOperand);
bool isSupported = false;
-
+ armnn::BackendId setBackend;
auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported)
{
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsActivationSupported,
data.m_Backends,
isSupported,
+ setBackend,
input.GetTensorInfo(),
outInfo,
activationDesc);
@@ -1596,7 +1645,11 @@ bool ConvertToActivation(const HalOperation& operation,
}
armnn::IConnectableLayer* layer = data.m_Network->AddActivationLayer(activationDesc);
- ARMNN_ASSERT(layer != nullptr);
+ layer->SetBackendId(setBackend);
+ if (!layer)
+ {
+ return Fail("%s: Could not add the ActivationLayer", __func__);
+ }
input.Connect(layer->GetInputSlot(0));
return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data, nullptr, validateFunc);
@@ -1782,13 +1835,14 @@ bool ConvertPooling2d(const HalOperation& operation,
}
bool isSupported = false;
-
+ armnn::BackendId setBackend;
auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
{
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsPooling2dSupported,
data.m_Backends,
isSupported,
+ setBackend,
inputInfo,
outputInfo,
desc);
@@ -1810,6 +1864,7 @@ bool ConvertPooling2d(const HalOperation& operation,
}
armnn::IConnectableLayer* pooling2dLayer = data.m_Network->AddPooling2dLayer(desc);
+ pooling2dLayer->SetBackendId(setBackend);
if (!pooling2dLayer)
{
return Fail("%s: AddPooling2dLayer failed", __func__);
@@ -1829,79 +1884,6 @@ bool ConvertPooling2d(const HalOperation& operation,
template<typename HalPolicy,
typename HalOperation = typename HalPolicy::Operation,
typename HalModel = typename HalPolicy::Model>
-bool ConvertAdd(const HalOperation& operation, const HalModel& model, ConversionData& data)
-{
- using HalOperand = 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 HalOperand* 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);
-
- bool isSupported = false;
- auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
- {
- FORWARD_LAYER_SUPPORT_FUNC(__func__,
- IsAdditionSupported,
- data.m_Backends,
- isSupported,
- inputInfo0,
- inputInfo1,
- outputInfo);
- };
-
- if(!IsDynamicTensor(outputInfo))
- {
- validateFunc(outputInfo, isSupported);
- }
- else
- {
- isSupported = AreDynamicTensorsSupported();
- }
-
- if (!isSupported)
- {
- return false;
- }
-
- armnn::IConnectableLayer* const startLayer = data.m_Network->AddAdditionLayer();
-
- bool isReshapeSupported = BroadcastTensor(input0, input1, startLayer, data);
- if (!isReshapeSupported)
- {
- return false;
- }
-
- return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *startLayer, model,
- data, nullptr, validateFunc, activationFunction);
-
-}
-
-template<typename HalPolicy,
- typename HalOperation = typename HalPolicy::Operation,
- typename HalModel = typename HalPolicy::Model>
bool ConvertArgMinMax(const HalOperation& operation,
const HalModel& model,
ConversionData& data,
@@ -1951,13 +1933,14 @@ bool ConvertArgMinMax(const HalOperation& operation,
descriptor.m_Axis = axis;
bool isSupported = false;
-
+ armnn::BackendId setBackend;
auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
{
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsArgMinMaxSupported,
data.m_Backends,
isSupported,
+ setBackend,
inputInfo0,
outputInfo,
descriptor);
@@ -1978,8 +1961,11 @@ bool ConvertArgMinMax(const HalOperation& operation,
}
armnn::IConnectableLayer* layer = data.m_Network->AddArgMinMaxLayer(descriptor);
- assert(layer != nullptr);
-
+ layer->SetBackendId(setBackend);
+ if (!layer)
+ {
+ return Fail("%s: Could not add the ArgMinMaxLayer", __func__);
+ }
input0.Connect(layer->GetInputSlot(0));
return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data, nullptr, validateFunc);
@@ -2082,10 +2068,12 @@ bool ConvertConcatenation(const HalOperation& operation, const HalModel& model,
reshapeDescriptor.m_TargetShape = reshapeInfo.GetShape();
bool isSupported = false;
+ armnn::BackendId setBackendReshape;
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsReshapeSupported,
data.m_Backends,
isSupported,
+ setBackendReshape,
operandInputHandle.GetTensorInfo(),
reshapeInfo,
reshapeDescriptor);
@@ -2095,6 +2083,7 @@ bool ConvertConcatenation(const HalOperation& operation, const HalModel& model,
return false;
}
armnn::IConnectableLayer& newReshape = AddReshapeLayer(*data.m_Network, operandInputHandle, reshapeInfo);
+ newReshape.SetBackendId(setBackendReshape);
// Point to the reshape operation rather then the input operation
operandShape = reshapeInfo.GetShape();
@@ -2110,7 +2099,11 @@ bool ConvertConcatenation(const HalOperation& operation, const HalModel& model,
}
}
- ARMNN_ASSERT(inputShapes.size() == inputHandles.size());
+ if (inputShapes.size() != inputHandles.size())
+ {
+ return Fail("%s: invalid model input shapes size doesn't match input handles size: %i != %i", __func__,
+ inputShapes.size(), inputHandles.size());
+ }
if (inputsHaveBeenReshaped)
{
@@ -2197,9 +2190,16 @@ bool ConvertConcatenation(const HalOperation& operation, const HalModel& model,
[](const LayerInputHandle& h)->const armnn::TensorInfo*{ return &h.GetTensorInfo(); });
bool isSupported = false;
+ armnn::BackendId setBackendConcat;
auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported){
- FORWARD_LAYER_SUPPORT_FUNC(__func__, IsConcatSupported, data.m_Backends, isSupported, inputTensorInfos,
- outputInfo, concatDescriptor);
+ FORWARD_LAYER_SUPPORT_FUNC(__func__,
+ IsConcatSupported,
+ data.m_Backends,
+ isSupported,
+ setBackendConcat,
+ inputTensorInfos,
+ outputInfo,
+ concatDescriptor);
};
if (!isDynamicTensor)
@@ -2217,15 +2217,24 @@ bool ConvertConcatenation(const HalOperation& operation, const HalModel& model,
}
armnn::IConnectableLayer* layer = data.m_Network->AddConcatLayer(concatDescriptor);
- assert(layer != nullptr);
+ layer->SetBackendId(setBackendConcat);
+ if (!layer)
+ {
+ return Fail("%s: Could not add the ConcatLayer", __func__);
+ }
layer->GetOutputSlot(0).SetTensorInfo(outputInfo);
// Connect inputs to the layer
const int numInputSlots = layer->GetNumInputSlots();
- assert(static_cast<std::size_t>(numInputSlots) == inputHandles.size());
+
+ if (static_cast<std::size_t>(numInputSlots) != inputHandles.size())
+ {
+ return Fail("%s: invalid model input slots size doesn't match input handles size: %i != %i", __func__,
+ static_cast<std::size_t>(numInputSlots), inputHandles.size());
+ }
for (int i = 0; i < numInputSlots; ++i)
{
// connect the input directly to the merge (concat) layer
- inputHandles[static_cast<unsigned int>(i)].Connect(layer->GetInputSlot(i));
+ inputHandles[static_cast<unsigned int>(i)].Connect(layer->GetInputSlot(static_cast<unsigned int>(i)));
}
// Transpose the output shape
@@ -2236,10 +2245,12 @@ bool ConvertConcatenation(const HalOperation& operation, const HalModel& model,
armnn::TensorInfo outputTransposeInfo = armnnUtils::TransposeTensorShape(inputTransposeInfo,
permutationPair.second);
isSupported = false;
+ armnn::BackendId setBackendTranspose;
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsTransposeSupported,
data.m_Backends,
isSupported,
+ setBackendTranspose,
inputTransposeInfo,
outputTransposeInfo,
transposeDesc);
@@ -2250,6 +2261,7 @@ bool ConvertConcatenation(const HalOperation& operation, const HalModel& model,
// Add permutation layer and connect the output to it, the permutation becomes the output layer
armnn::IConnectableLayer& deswizzleLayer = AddTransposeLayer(*data.m_Network, layer->GetOutputSlot(0),
permutationPair.second);
+ deswizzleLayer.SetBackendId(setBackendTranspose);
layer = &deswizzleLayer;
return true;
@@ -2265,7 +2277,10 @@ bool ConvertConcatenation(const HalOperation& operation, const HalModel& model,
if (isDynamicTensor)
{
// Infer the output shapes of concat if outputs are type 1 dynamic
- ARMNN_ASSERT(layer->GetOutputSlot(0).IsTensorInfoSet());
+ if (!layer->GetOutputSlot(0).IsTensorInfoSet())
+ {
+ return Fail("%s: TensorInfo is not set", __func__);
+ }
if (!ValidateConcatOutputShape(inputShapes,
layer->GetOutputSlot(0).GetTensorInfo().GetShape(),
concatDim))
@@ -2292,11 +2307,13 @@ bool ConvertConcatenation(const HalOperation& operation, const HalModel& model,
armnn::TensorInfo concatInfo = layer->GetOutputSlot(0).GetTensorInfo();
isSupported = false;
+ armnn::BackendId setBackendReshape2;
auto validateReshapeFunc = [&](const armnn::TensorInfo& afterConcatInfo, bool& isSupported){
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsReshapeSupported,
data.m_Backends,
isSupported,
+ setBackendReshape2,
concatInfo,
afterConcatInfo,
reshapeDescriptor);
@@ -2316,6 +2333,7 @@ bool ConvertConcatenation(const HalOperation& operation, const HalModel& model,
return false;
}
layer = &AddReshapeLayer(*data.m_Network, layer->GetOutputSlot(0), afterConcatInfo);
+ layer->SetBackendId(setBackendReshape2);
return SetupAndTrackLayerOutputSlot<HalPolicy>(operation,
0,
*layer,
@@ -2351,18 +2369,21 @@ bool ConvertConv2d(const HalOperation& operation, const HalModel& model, Convers
const armnn::TensorInfo& inputInfo = input.GetTensorInfo();
const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
- // ArmNN does not currently support non-fixed weights or bias
- const ConstTensorPin weightsPin = ConvertOperationInputToConstTensorPin<HalPolicy>(operation, 1, model, data);
- const ConstTensorPin biasPin = ConvertOperationInputToConstTensorPin<HalPolicy>(operation, 2, model, data);
+ LayerInputHandle weightsInput = ConvertToLayerInputHandle<HalPolicy>(operation, 1, model, data);
+ if (!weightsInput.IsValid())
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
- if (!weightsPin.IsValid() || !biasPin.IsValid())
+ LayerInputHandle biasInput = ConvertToLayerInputHandle<HalPolicy>(operation, 2, model, data); // 1D
+ if (!biasInput.IsValid())
{
return Fail("%s: Operation has invalid inputs", __func__);
}
- armnn::ConstTensor weights = weightsPin.GetConstTensor();
- armnn::ConstTensor bias = biasPin.GetConstTensor();
- SanitizeBiasQuantizationScale(bias.GetInfo(), weights.GetInfo(), inputInfo);
+ biasInput.SanitizeQuantizationScale(weightsInput, input);
+ armnn::TensorInfo weightsInfo = weightsInput.GetTensorInfo();
+ armnn::TensorInfo biasInfo = biasInput.GetTensorInfo();
armnn::Convolution2dDescriptor desc;
desc.m_DataLayout = armnn::DataLayout::NHWC;
@@ -2392,8 +2413,8 @@ bool ConvertConv2d(const HalOperation& operation, const HalModel& model, Convers
return Fail("%s: Operation has invalid inputs", __func__);
}
- const uint32_t kernelX = weights.GetShape()[2];
- const uint32_t kernelY = weights.GetShape()[1];
+ const uint32_t kernelX = weightsInfo.GetShape()[2];
+ const uint32_t kernelY = weightsInfo.GetShape()[1];
const uint32_t inputX = inputInfo.GetShape()[2];
const uint32_t inputY = inputInfo.GetShape()[1];
@@ -2406,19 +2427,21 @@ bool ConvertConv2d(const HalOperation& operation, const HalModel& model, Convers
}
desc.m_BiasEnabled = true;
- armnn::Optional<armnn::TensorInfo> biases(bias.GetInfo());
+ armnn::Optional<armnn::TensorInfo> biases(biasInfo);
bool isSupported = false;
+ armnn::BackendId setBackend;
auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
{
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsConvolution2dSupported,
data.m_Backends,
isSupported,
+ setBackend,
inputInfo,
outputInfo,
desc,
- weights.GetInfo(),
+ weightsInfo,
biases);
};
@@ -2436,8 +2459,8 @@ bool ConvertConv2d(const HalOperation& operation, const HalModel& model, Convers
return false;
}
- armnn::IConnectableLayer* startLayer =
- data.m_Network->AddConvolution2dLayer(desc, weights, armnn::Optional<armnn::ConstTensor>(bias));
+ armnn::IConnectableLayer* startLayer = data.m_Network->AddConvolution2dLayer(desc);
+ startLayer->SetBackendId(setBackend);
if (!startLayer)
{
@@ -2446,6 +2469,10 @@ bool ConvertConv2d(const HalOperation& operation, const HalModel& model, Convers
input.Connect(startLayer->GetInputSlot(0));
+ // Connect weights and bias inputs
+ weightsInput.Connect(startLayer->GetInputSlot(1));
+ biasInput.Connect(startLayer->GetInputSlot(2));
+
return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *startLayer, model,
data, nullptr, validateFunc, activation);
}
@@ -2484,7 +2511,7 @@ bool ConvertDepthToSpace(const HalOperation& operation, const HalModel& model, C
GetInputScalar<HalPolicy>(operation, 1, HalOperandType::INT32, descriptor.m_BlockSize, model, data);
if (descriptor.m_BlockSize <= 1)
{
- return Fail("%s: Block size must be at least 1 in all dimensions");
+ return Fail("%s: Block size must be at least 1 in all dimensions", __func__);
}
descriptor.m_DataLayout = armnn::DataLayout::NHWC;
@@ -2494,12 +2521,14 @@ bool ConvertDepthToSpace(const HalOperation& operation, const HalModel& model, C
}
bool isSupported = false;
+ armnn::BackendId setBackend;
auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
{
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsDepthToSpaceSupported,
data.m_Backends,
isSupported,
+ setBackend,
inputInfo,
outputInfo,
descriptor);
@@ -2520,7 +2549,11 @@ bool ConvertDepthToSpace(const HalOperation& operation, const HalModel& model, C
}
armnn::IConnectableLayer* const layer = data.m_Network->AddDepthToSpaceLayer(descriptor);
- assert(layer != nullptr);
+ layer->SetBackendId(setBackend);
+ if (!layer)
+ {
+ return Fail("%s: Could not add the DepthToSpaceLayer", __func__);
+ }
input.Connect(layer->GetInputSlot(0));
return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data, nullptr, validateFunc);
@@ -2554,10 +2587,9 @@ bool ConvertDepthwiseConv2d(const HalOperation& operation, const HalModel& model
// ArmNN does not currently support non-fixed weights or bias
// Find the shape of the weights tensor. In AndroidNN this will be [ 1, H, W, I * M ]
const HalOperand* weightsOperand = GetInputOperand<HalPolicy>(operation, 1, model);
-
- if (weightsOperand == nullptr)
+ if (!weightsOperand)
{
- return Fail("%s: Operand is invalid", __func__);
+ return Fail("%s: Could not read weights", __func__);
}
// Basic sanity check on the weights shape.
// ANEURALNETWORKS_DEPTHWISE_CONV_2D specifies a 4-D tensor, of shape
@@ -2570,34 +2602,27 @@ bool ConvertDepthwiseConv2d(const HalOperation& operation, const HalModel& model
armnn::DepthwiseConvolution2dDescriptor desc;
desc.m_DataLayout = armnn::DataLayout::NHWC;
- // Reinterpret weight data as [ H, W, I, M ]
- armnn::TensorShape weightsShape({ weightsOperand->dimensions[1],
- weightsOperand->dimensions[2],
- inputInfo.GetShape()[3],
- weightsOperand->dimensions[3] / inputInfo.GetShape()[3] });
-
- // Swizzle weight data [ H, W, I, M ] -> [ M, I, H, W ]
- const armnn::PermutationVector HWIMToMIHW = { 2U, 3U, 1U, 0U };
-
- const ConstTensorPin weightsPin =
- ConvertOperationInputToConstTensorPin<HalPolicy>(operation,
- 1,
- model,
- data,
- HWIMToMIHW,
- &weightsShape);
+ LayerInputHandle weightsInput = ConvertToLayerInputHandle<HalPolicy>(operation, 1, model, data);
+ if (!weightsInput.IsValid())
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
- // Bias is a 1D tensor
- const ConstTensorPin biasPin = ConvertOperationInputToConstTensorPin<HalPolicy>(operation, 2, model, data);
+ const HalOperand* biasOperand = GetInputOperand<HalPolicy>(operation, 2, model);
+ if (!biasOperand)
+ {
+ return Fail("%s: Could not read bias", __func__);
+ }
- if (!weightsPin.IsValid() || !biasPin.IsValid())
+ LayerInputHandle biasInput = ConvertToLayerInputHandle<HalPolicy>(operation, 2, model, data); // 1D
+ if (!biasInput.IsValid())
{
return Fail("%s: Operation has invalid inputs", __func__);
}
- armnn::ConstTensor weights = weightsPin.GetConstTensor();
- armnn::ConstTensor bias = biasPin.GetConstTensor();
- SanitizeBiasQuantizationScale(bias.GetInfo(), weights.GetInfo(), inputInfo);
+ biasInput.SanitizeQuantizationScale(weightsInput, input);
+ armnn::TensorInfo weightsInfo = weightsInput.GetTensorInfo();
+ armnn::TensorInfo biasInfo = biasInput.GetTensorInfo();
ActivationFn activation;
@@ -2625,8 +2650,8 @@ bool ConvertDepthwiseConv2d(const HalOperation& operation, const HalModel& model
return Fail("%s: Operation has invalid inputs", __func__);
}
- const uint32_t kernelX = weights.GetShape()[3];
- const uint32_t kernelY = weights.GetShape()[2];
+ const uint32_t kernelX = weightsInfo.GetShape()[2];
+ const uint32_t kernelY = weightsInfo.GetShape()[1];
const uint32_t inputX = inputInfo.GetShape()[2];
const uint32_t inputY = inputInfo.GetShape()[1];
@@ -2639,19 +2664,21 @@ bool ConvertDepthwiseConv2d(const HalOperation& operation, const HalModel& model
}
desc.m_BiasEnabled = true;
- armnn::Optional<armnn::TensorInfo> biases(bias.GetInfo());
+ armnn::Optional<armnn::TensorInfo> biases(biasInfo);
bool isSupported = false;
+ armnn::BackendId setBackend;
auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
{
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsDepthwiseConvolutionSupported,
data.m_Backends,
isSupported,
+ setBackend,
inputInfo,
outputInfo,
desc,
- weights.GetInfo(),
+ weightsInfo,
biases);
};
@@ -2670,8 +2697,8 @@ bool ConvertDepthwiseConv2d(const HalOperation& operation, const HalModel& model
return false;
}
- armnn::IConnectableLayer* startLayer =
- data.m_Network->AddDepthwiseConvolution2dLayer(desc, weights, armnn::Optional<armnn::ConstTensor>(bias));
+ armnn::IConnectableLayer* startLayer = data.m_Network->AddDepthwiseConvolution2dLayer(desc);
+ startLayer->SetBackendId(setBackend);
if (!startLayer)
{
return Fail("%s: AddDepthwiseConvolution2dLayer failed", __func__);
@@ -2679,6 +2706,10 @@ bool ConvertDepthwiseConv2d(const HalOperation& operation, const HalModel& model
input.Connect(startLayer->GetInputSlot(0));
+ // Connect weights and bias inputs
+ weightsInput.Connect(startLayer->GetInputSlot(1));
+ biasInput.Connect(startLayer->GetInputSlot(2));
+
return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *startLayer, model,
data, nullptr, validateFunc, activation);
}
@@ -2712,12 +2743,14 @@ bool ConvertDequantize(const HalOperation& operation, const HalModel& model, Con
const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*outputOperand);
bool isSupported = false;
+ armnn::BackendId setBackend;
auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
{
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsDequantizeSupported,
data.m_Backends,
isSupported,
+ setBackend,
inputInfo,
outputInfo);
};
@@ -2737,7 +2770,11 @@ bool ConvertDequantize(const HalOperation& operation, const HalModel& model, Con
}
armnn::IConnectableLayer* const layer = data.m_Network->AddDequantizeLayer();
- assert(layer != nullptr);
+ layer->SetBackendId(setBackend);
+ if (!layer)
+ {
+ return Fail("%s: Could not add the DequantizeLayer", __func__);
+ }
input.Connect(layer->GetInputSlot(0));
return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data, nullptr, validateFunc);
@@ -2746,10 +2783,16 @@ bool ConvertDequantize(const HalOperation& operation, const HalModel& model, Con
template<typename HalPolicy,
typename HalOperation = typename HalPolicy::Operation,
typename HalModel = typename HalPolicy::Model>
-bool ConvertDiv(const HalOperation& operation, const HalModel& model, ConversionData& data)
+bool ConvertElementwiseBinary(const HalOperation& operation,
+ const HalModel& model,
+ ConversionData& data,
+ armnn::BinaryOperation binaryOperation)
{
using HalOperand = typename HalPolicy::Operand;
+ ALOGV("HalPolicy::ConvertElementwiseBinary()");
+ ALOGV("binaryOperation = %s", GetBinaryOperationAsCString(binaryOperation));
+
LayerInputHandle input0 = ConvertToLayerInputHandle<HalPolicy>(operation, 0, model, data);
LayerInputHandle input1 = ConvertToLayerInputHandle<HalPolicy>(operation, 1, model, data);
@@ -2758,35 +2801,38 @@ bool ConvertDiv(const HalOperation& operation, const HalModel& model, Conversion
return Fail("%s: Operation has invalid inputs", __func__);
}
- // The FuseActivation parameter is always the input index 2
- // and it should be optional
+ // 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__);
+ return Fail("%s: Operation has invalid optional input: activation function", __func__);
}
const HalOperand* output = GetOutputOperand<HalPolicy>(operation, 0, model);
if (!output)
{
- return Fail("%s: Could not read output 0", __func__);
+ return Fail("%s: Could not read output", __func__);
}
const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
+ armnn::ElementwiseBinaryDescriptor descriptor(binaryOperation);
+
bool isSupported = false;
auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
{
FORWARD_LAYER_SUPPORT_FUNC(__func__,
- IsDivisionSupported,
+ IsElementwiseBinarySupported,
data.m_Backends,
isSupported,
+ armnn::BackendId(),
input0.GetTensorInfo(),
input1.GetTensorInfo(),
- outputInfo);
+ outputInfo,
+ binaryOperation);
};
- if(!IsDynamicTensor(outputInfo))
+ if (!IsDynamicTensor(outputInfo))
{
validateFunc(outputInfo, isSupported);
}
@@ -2800,19 +2846,22 @@ bool ConvertDiv(const HalOperation& operation, const HalModel& model, Conversion
return false;
}
- armnn::IConnectableLayer* const startLayer = data.m_Network->AddDivisionLayer();
-
- bool isReshapeSupported = BroadcastTensor(input0, input1, startLayer, data);
+ armnn::IConnectableLayer* layer = data.m_Network->AddElementwiseBinaryLayer(descriptor);
+ if (!layer)
+ {
+ return Fail("%s: Could not add the ElementwiseBinaryLayer", __func__);
+ }
+ bool isReshapeSupported = BroadcastTensor(input0, input1, layer, data);
if (!isReshapeSupported)
{
return false;
}
- return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *startLayer, model,
- data, nullptr, validateFunc, activationFunction);
-
+ return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data, nullptr, validateFunc,
+ activationFunction);
}
+
template<typename HalPolicy,
typename HalOperation = typename HalPolicy::Operation,
typename HalModel = typename HalPolicy::Model>
@@ -2835,12 +2884,14 @@ bool ConvertFloor(const HalOperation& operation, const HalModel& model, Conversi
const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*outputOperand);
bool isSupported = false;
+ armnn::BackendId setBackend;
auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
{
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsFloorSupported,
data.m_Backends,
isSupported,
+ setBackend,
input.GetTensorInfo(),
outputInfo);
};
@@ -2860,7 +2911,11 @@ bool ConvertFloor(const HalOperation& operation, const HalModel& model, Conversi
}
armnn::IConnectableLayer* layer = data.m_Network->AddFloorLayer();
- assert(layer != nullptr);
+ layer->SetBackendId(setBackend);
+ if (!layer)
+ {
+ return Fail("%s: Could not add the FloorLayer", __func__);
+ }
input.Connect(layer->GetInputSlot(0));
return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data, nullptr, validateFunc);
@@ -2945,7 +3000,11 @@ DequantizeResult DequantizeIfRequired(size_t operand_index,
}
const HalOperand* operand = GetInputOperand<HalPolicy>(operationIt, 0, model);
- ARMNN_ASSERT(operand);
+
+ if (!operand)
+ {
+ return { nullptr, 0, armnn::TensorInfo(), DequantizeStatus::INVALID_OPERAND };
+ }
if (!IsQSymm8(*operand))
{
@@ -2969,8 +3028,12 @@ DequantizeResult DequantizeIfRequired(size_t operand_index,
for (size_t i = 0; i < dequantizedBufferLength; ++i)
{
float* dstPtr = dequantizedBuffer.get();
- ARMNN_ASSERT(dstPtr);
- *dstPtr++ = quantizedBuffer[i] * quantizationScale;
+
+ if (!dstPtr)
+ {
+ return { nullptr, 0, armnn::TensorInfo(), DequantizeStatus::INVALID_OPERAND };
+ }
+ *dstPtr = quantizedBuffer[i] * quantizationScale;
}
// Construct tensor info for dequantized ConstTensor
@@ -3049,26 +3112,12 @@ bool ConvertFullyConnected(const HalOperation& operation, const HalModel& model,
return Fail("%s: Could not read weights", __func__);
}
- const armnn::TensorInfo& weightsInfo = GetTensorInfoForOperand(*weightsOperand);
- bool constantWeights = IsOperandConstant<HalPolicy>(*weightsOperand);
-
- armnn::Optional<armnn::ConstTensor> optionalWeights = armnn::EmptyOptional();
- if (!constantWeights)
- {
- weightsInput = ConvertToLayerInputHandle<HalPolicy>(operation, 1, model, data);
- if (!weightsInput.IsValid())
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
- }
- else
+ // If weights are constant a separate constant layer will be created to store data.
+ // Otherwise handle non const weights as inputs.
+ weightsInput = ConvertToLayerInputHandle<HalPolicy>(operation, 1, model, data);
+ if (!weightsInput.IsValid())
{
- ConstTensorPin weightsPin = DequantizeAndMakeConstTensorPin<HalPolicy>(operation, model, data, 1);
- if (!weightsPin.IsValid())
- {
- return Fail("%s: Operation has invalid weights", __func__);
- }
- optionalWeights = armnn::Optional<armnn::ConstTensor>(weightsPin.GetConstTensor());
+ return Fail("%s: Operation has invalid inputs", __func__);
}
LayerInputHandle biasInput = LayerInputHandle();
@@ -3077,33 +3126,16 @@ bool ConvertFullyConnected(const HalOperation& operation, const HalModel& model,
{
return Fail("%s: Could not read bias", __func__);
}
- armnn::TensorInfo biasInfo = GetTensorInfoForOperand(*biasOperand);
- bool constantBias = IsOperandConstant<HalPolicy>(*biasOperand);
-
- armnn::Optional<armnn::ConstTensor> optionalBias = armnn::EmptyOptional();
- if (!constantBias)
- {
- biasInput = ConvertToLayerInputHandle<HalPolicy>(operation, 2, model, data);
- if (!biasInput.IsValid())
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
- }
- else
- {
- ConstTensorPin biasPin = ConvertOperationInputToConstTensorPin<HalPolicy>(operation, 2, model, data); // 1D
- if (!biasPin.IsValid())
- {
- return Fail("%s: Operation has invalid bias", __func__);
- }
- optionalBias = armnn::Optional<armnn::ConstTensor>(biasPin.GetConstTensor());
- }
- if ((constantWeights && !constantBias) || (!constantWeights && constantBias))
+ // If bias are constant a separate constant layer will be created to store data.
+ // Otherwise handle non const bias as inputs.
+ biasInput = ConvertToLayerInputHandle<HalPolicy>(operation, 2, model, data); // 1D
+ if (!biasInput.IsValid())
{
- return Fail("%s: Non-compatible weights and bias", __func__);
+ return Fail("%s: Operation has invalid inputs", __func__);
}
+ armnn::TensorInfo weightsInfo = weightsInput.GetTensorInfo();
armnn::TensorInfo reshapedInfo = inputInfo;
try
{
@@ -3114,7 +3146,8 @@ bool ConvertFullyConnected(const HalOperation& operation, const HalModel& model,
return Fail("%s: %s", __func__, e.what());
}
- // ensuring that the bias value is within 1% of the weights input (small float differences can exist)
+ // Ensuring that the bias value is within 1% of the weights input (small float differences can exist)
+ armnn::TensorInfo biasInfo = biasInput.GetTensorInfo();
SanitizeBiasQuantizationScale(biasInfo, weightsInfo, reshapedInfo);
ActivationFn activationFunction;
@@ -3126,9 +3159,10 @@ bool ConvertFullyConnected(const HalOperation& operation, const HalModel& model,
armnn::FullyConnectedDescriptor desc;
desc.m_TransposeWeightMatrix = true;
desc.m_BiasEnabled = true;
- desc.m_ConstantWeights = constantWeights;
+ desc.m_ConstantWeights = IsOperandConstant<HalPolicy>(*weightsOperand);
bool isSupported = false;
+ armnn::BackendId setBackend;
auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
{
if (!VerifyFullyConnectedShapes(reshapedInfo.GetShape(),
@@ -3145,6 +3179,7 @@ bool ConvertFullyConnected(const HalOperation& operation, const HalModel& model,
IsFullyConnectedSupported,
data.m_Backends,
isSupported,
+ setBackend,
reshapedInfo,
outputInfo,
weightsInfo,
@@ -3166,10 +3201,9 @@ bool ConvertFullyConnected(const HalOperation& operation, const HalModel& model,
return false;
}
- armnn::IConnectableLayer* startLayer =
- data.m_Network->AddFullyConnectedLayer(desc,
- optionalWeights,
- optionalBias);
+ // Add FullyConnected layer. Weights and bias will be connected as constant layers or non const inputs.
+ armnn::IConnectableLayer* startLayer = data.m_Network->AddFullyConnectedLayer(desc);
+ startLayer->SetBackendId(setBackend);
if (inputInfo.GetNumDimensions() > 2U)
{
@@ -3177,7 +3211,10 @@ bool ConvertFullyConnected(const HalOperation& operation, const HalModel& model,
reshapeDescriptor.m_TargetShape = reshapedInfo.GetShape();
armnn::IConnectableLayer* reshapeLayer = data.m_Network->AddReshapeLayer(reshapeDescriptor);
- assert(reshapeLayer != nullptr);
+ if (!reshapeLayer)
+ {
+ return Fail("%s: could not add the reshapeLayer", __func__);
+ }
input.Connect(reshapeLayer->GetInputSlot(0));
reshapeLayer->GetOutputSlot(0).SetTensorInfo(reshapedInfo);
reshapeLayer->GetOutputSlot(0).Connect(startLayer->GetInputSlot(0));
@@ -3187,12 +3224,9 @@ bool ConvertFullyConnected(const HalOperation& operation, const HalModel& model,
input.Connect(startLayer->GetInputSlot(0));
}
- // connect weights input
- if (!desc.m_ConstantWeights)
- {
- weightsInput.Connect(startLayer->GetInputSlot(1));
- biasInput.Connect(startLayer->GetInputSlot(2));
- }
+ // Connect weights and bias inputs
+ weightsInput.Connect(startLayer->GetInputSlot(1));
+ biasInput.Connect(startLayer->GetInputSlot(2));
return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *startLayer, model,
data, nullptr, validateFunc, activationFunction);
@@ -3234,12 +3268,14 @@ bool ConvertL2Normalization(const HalOperation& operation, const HalModel& model
desc.m_DataLayout = armnn::DataLayout::NHWC;
bool isSupported = false;
+ armnn::BackendId setBackend;
auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
{
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsL2NormalizationSupported,
data.m_Backends,
isSupported,
+ setBackend,
inputInfo,
outputInfo,
desc);
@@ -3260,7 +3296,11 @@ bool ConvertL2Normalization(const HalOperation& operation, const HalModel& model
}
armnn::IConnectableLayer* layer = data.m_Network->AddL2NormalizationLayer(desc);
- assert(layer != nullptr);
+ layer->SetBackendId(setBackend);
+ if (!layer)
+ {
+ return Fail("%s: Could not add the L2NormalizationLayer", __func__);
+ }
input.Connect(layer->GetInputSlot(0));
return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data, nullptr, validateFunc);
@@ -3320,12 +3360,14 @@ bool ConvertLocalResponseNormalization(const HalOperation& operation,
descriptor.m_NormSize = 1 + (2 * descriptor.m_NormSize);
bool isSupported = false;
+ armnn::BackendId setBackend;
auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
{
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsNormalizationSupported,
data.m_Backends,
isSupported,
+ setBackend,
inputInfo,
outputInfo,
descriptor);
@@ -3345,9 +3387,12 @@ bool ConvertLocalResponseNormalization(const HalOperation& operation,
return false;
}
-
armnn::IConnectableLayer* layer = data.m_Network->AddNormalizationLayer(descriptor);
- assert(layer != nullptr);
+ layer->SetBackendId(setBackend);
+ if (!layer)
+ {
+ return Fail("%s: Could not add the NormalizationLayer", __func__);
+ }
input.Connect(layer->GetInputSlot(0));
return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data, nullptr, validateFunc);
@@ -3418,12 +3463,14 @@ bool ConvertMean(const HalOperation& operation, const HalModel& model, Conversio
descriptor.m_KeepDims = keepDims > 0;
bool isSupported = false;
+ armnn::BackendId setBackend;
auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
{
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsMeanSupported,
data.m_Backends,
isSupported,
+ setBackend,
inputInfo,
outputInfo,
descriptor);
@@ -3444,80 +3491,14 @@ bool ConvertMean(const HalOperation& operation, const HalModel& model, Conversio
}
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, nullptr, validateFunc);
-}
-
-template<typename HalPolicy,
- typename HalOperation = typename HalPolicy::Operation,
- typename HalModel = typename HalPolicy::Model>
-bool ConvertMul(const HalOperation& operation, const HalModel& model, ConversionData& data)
-{
- using HalOperand = 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 HalOperand* outputOperand = GetOutputOperand<HalPolicy>(operation, 0, model);
-
- if (outputOperand == nullptr)
+ layer->SetBackendId(setBackend);
+ if (!layer)
{
- return false;
- }
-
- const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*outputOperand);
-
- bool isSupported = false;
- auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
- {
- FORWARD_LAYER_SUPPORT_FUNC(__func__,
- IsMultiplicationSupported,
- data.m_Backends,
- isSupported,
- input0.GetTensorInfo(),
- input1.GetTensorInfo(),
- outputInfo);
- };
-
- if(!IsDynamicTensor(outputInfo))
- {
- validateFunc(outputInfo, isSupported);
- }
- else
- {
- isSupported = AreDynamicTensorsSupported();
- }
-
- if (!isSupported)
- {
- return false;
- }
-
- armnn::IConnectableLayer* const startLayer = data.m_Network->AddMultiplicationLayer();
-
- bool isReshapeSupported = BroadcastTensor(input0, input1, startLayer, data);
- if (!isReshapeSupported)
- {
- return false;
+ return Fail("%s: Could not add the MeanLayer", __func__);
}
+ input.Connect(layer->GetInputSlot(0));
- return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *startLayer, model,
- data, nullptr, validateFunc, activationFunction);
+ return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data, nullptr, validateFunc);
}
template<typename HalPolicy,
@@ -3561,12 +3542,14 @@ bool ConvertPad(HalOperation& operation, const HalModel& model, ConversionData&
const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
bool isSupported = false;
+ armnn::BackendId setBackend;
auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
{
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsPadSupported,
data.m_Backends,
isSupported,
+ setBackend,
inputInfo,
outputInfo,
descriptor);
@@ -3587,7 +3570,11 @@ bool ConvertPad(HalOperation& operation, const HalModel& model, ConversionData&
}
armnn::IConnectableLayer* const layer = data.m_Network->AddPadLayer(descriptor);
- assert(layer != nullptr);
+ layer->SetBackendId(setBackend);
+ if (!layer)
+ {
+ return Fail("%s: Could not add the PadLayer", __func__);
+ }
input.Connect(layer->GetInputSlot(0));
return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data, nullptr, validateFunc);
@@ -3646,12 +3633,14 @@ bool ConvertReshape(const HalOperation& operation, const HalModel& model, Conver
const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*outputOperand);
bool isSupported = false;
+ armnn::BackendId setBackend;
auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
{
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsReshapeSupported,
data.m_Backends,
isSupported,
+ setBackend,
input.GetTensorInfo(),
outputInfo,
reshapeDescriptor);
@@ -3672,78 +3661,14 @@ bool ConvertReshape(const HalOperation& operation, const HalModel& model, Conver
}
armnn::IConnectableLayer* layer = data.m_Network->AddReshapeLayer(reshapeDescriptor);
- assert(layer != nullptr);
- input.Connect(layer->GetInputSlot(0));
-
- return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data, nullptr, validateFunc);
-}
-
-template<typename HalPolicy,
- typename HalOperation = typename HalPolicy::Operation,
- typename HalModel = typename HalPolicy::Model>
-bool ConvertSub(const HalOperation& operation, const HalModel& model, ConversionData& data)
-{
- using HalOperand = typename HalPolicy::Operand;
-
- LayerInputHandle input0 = ConvertToLayerInputHandle<HalPolicy>(operation, 0, model, data);
- LayerInputHandle input1 = ConvertToLayerInputHandle<HalPolicy>(operation, 1, model, data);
-
- if (!input0.IsValid() || !input1.IsValid())
+ layer->SetBackendId(setBackend);
+ if (!layer)
{
- return Fail("%s: Operation has invalid inputs", __func__);
+ return Fail("%s: Could not add the ReshapeLayer", __func__);
}
+ input.Connect(layer->GetInputSlot(0));
- // 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 HalOperand* 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;
- auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
- {
- FORWARD_LAYER_SUPPORT_FUNC(__func__,
- IsSubtractionSupported,
- data.m_Backends,
- isSupported,
- input0.GetTensorInfo(),
- input1.GetTensorInfo(),
- outputInfo);
- };
-
- if(IsDynamicTensor(outputInfo))
- {
- isSupported = AreDynamicTensorsSupported();
- }
- else
- {
- validateFunc(outputInfo, isSupported);
- }
-
- if (!isSupported)
- {
- return false;
- }
-
- armnn::IConnectableLayer* const startLayer = data.m_Network->AddSubtractionLayer();
-
- bool isReshapeSupported = BroadcastTensor(input0, input1, startLayer, data);
- if (!isReshapeSupported)
- {
- return false;
- }
- return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *startLayer, model,
- data, nullptr, validateFunc, activationFunction);
+ return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data, nullptr, validateFunc);
}
template<typename HalPolicy,
@@ -3781,13 +3706,13 @@ bool ConvertSqueeze(const HalOperation& operation, const HalModel& model, Conver
// if the operand index is out of bounds.
const HalOperand* 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);
+ for (unsigned int i = 0; i < rank; ++i)
+ {
+ axis.push_back(static_cast<unsigned int>(i));
+ }
}
else if (!GetTensorInt32Values<HalPolicy>(*axisOperand, axis, model, data))
{
@@ -3814,10 +3739,12 @@ bool ConvertSqueeze(const HalOperation& operation, const HalModel& model, Conver
reshapeDesc.m_TargetShape = outputInfo.GetShape();
bool isSupported = false;
+ armnn::BackendId setBackend;
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsReshapeSupported,
data.m_Backends,
isSupported,
+ setBackend,
inputInfo,
outputInfo,
reshapeDesc);
@@ -3828,7 +3755,11 @@ bool ConvertSqueeze(const HalOperation& operation, const HalModel& model, Conver
}
armnn::IConnectableLayer* const layer = data.m_Network->AddReshapeLayer(reshapeDesc);
- assert(layer != nullptr);
+ layer->SetBackendId(setBackend);
+ if (!layer)
+ {
+ return Fail("%s: Could not add the ReshapeLayer", __func__);
+ }
input.Connect(layer->GetInputSlot(0));
return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data);
@@ -3914,12 +3845,14 @@ bool ConvertStridedSlice(const HalOperation& operation, const HalModel& model, C
}
bool isSupported = false;
+ armnn::BackendId setBackend;
auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
{
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsStridedSliceSupported,
data.m_Backends,
isSupported,
+ setBackend,
inputInfo,
outputInfo,
descriptor);
@@ -3963,7 +3896,11 @@ bool ConvertStridedSlice(const HalOperation& operation, const HalModel& model, C
}
armnn::IConnectableLayer* const layer = data.m_Network->AddStridedSliceLayer(descriptor);
- assert(layer != nullptr);
+ layer->SetBackendId(setBackend);
+ if (!layer)
+ {
+ return Fail("%s: Could not add the StridedSliceLayer", __func__);
+ }
input.Connect(layer->GetInputSlot(0));
return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data, nullptr, validateFunc);
@@ -4021,12 +3958,14 @@ bool ConvertTranspose(const HalOperation& operation, const HalModel& model, Conv
const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
bool isSupported = false;
+ armnn::BackendId setBackend;
auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
{
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsTransposeSupported,
data.m_Backends,
isSupported,
+ setBackend,
inputInfo,
outputInfo,
transposeDesc);
@@ -4047,7 +3986,11 @@ bool ConvertTranspose(const HalOperation& operation, const HalModel& model, Conv
}
armnn::IConnectableLayer* const layer = data.m_Network->AddTransposeLayer(transposeDesc);
- assert(layer != nullptr);
+ layer->SetBackendId(setBackend);
+ if (!layer)
+ {
+ return Fail("%s: Could not add the TransposeLayer", __func__);
+ }
input.Connect(layer->GetInputSlot(0));
return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data, nullptr, validateFunc);
@@ -4115,12 +4058,14 @@ bool ConvertBatchToSpaceNd(const HalOperation& operation,
batchToSpaceNdDesc.m_Crops = {{0, 0}, {0, 0}};
bool isSupported = false;
+ armnn::BackendId setBackend;
auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
{
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsBatchToSpaceNdSupported,
data.m_Backends,
isSupported,
+ setBackend,
inputInfo,
outputInfo,
batchToSpaceNdDesc);
@@ -4142,7 +4087,11 @@ bool ConvertBatchToSpaceNd(const HalOperation& operation,
}
armnn::IConnectableLayer* const layer = data.m_Network->AddBatchToSpaceNdLayer(batchToSpaceNdDesc);
- assert(layer != nullptr);
+ layer->SetBackendId(setBackend);
+ if (!layer)
+ {
+ return Fail("%s: Could not add the BatchToSpaceNdLayer", __func__);
+ }
input.Connect(layer->GetInputSlot(0));
return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data, nullptr, validateFunc);
@@ -4217,7 +4166,8 @@ bool ConvertSpaceToBatchNd(const HalOperation& operation, const HalModel& model,
return Fail("%s: Operation has invalid paddings operand, invalid padding values.", __func__);
}
- paddingList.emplace_back((unsigned int) paddingBeforeInput, (unsigned int) paddingAfterInput);
+ paddingList.emplace_back(static_cast<unsigned int>(paddingBeforeInput),
+ static_cast<unsigned int>(paddingAfterInput));
}
armnn::SpaceToBatchNdDescriptor descriptor;
@@ -4231,12 +4181,14 @@ bool ConvertSpaceToBatchNd(const HalOperation& operation, const HalModel& model,
}
bool isSupported = false;
+ armnn::BackendId setBackend;
auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
{
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsSpaceToBatchNdSupported,
data.m_Backends,
isSupported,
+ setBackend,
inputInfo,
outputInfo,
descriptor);
@@ -4257,7 +4209,11 @@ bool ConvertSpaceToBatchNd(const HalOperation& operation, const HalModel& model,
}
armnn::IConnectableLayer* const layer = data.m_Network->AddSpaceToBatchNdLayer(descriptor);
- assert(layer != nullptr);
+ layer->SetBackendId(setBackend);
+ if (!layer)
+ {
+ return Fail("%s: Could not add the BatchToSpaceLayer", __func__);
+ }
input.Connect(layer->GetInputSlot(0));
return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data, nullptr, validateFunc);
generated by cgit v1.2.1 (git 2.23.0) at 2024-04-29 19:52:27 +0000