Release 18.05.02
diff --git a/ModelToINetworkConverter.cpp b/ModelToINetworkConverter.cpp
index bd2443e..fe4e8ac 100644
--- a/ModelToINetworkConverter.cpp
+++ b/ModelToINetworkConverter.cpp
@@ -115,7 +115,7 @@
outPadTail = boost::numeric_cast<uint32_t>(padTail);
}
-bool ValidateBroadcast(const Model& model, const Operation& operation, uint32_t numInputs)
+bool ValidateBroadcast(const V1_0::Model& model, const V1_0::Operation& operation, uint32_t numInputs)
{
assert(operation.inputs.size() > 0); // This should have been validated by the caller
// validateModel() has been called already so we know the operation.inputs indexes are valid within model.operands.
@@ -334,7 +334,7 @@
std::vector<uint8_t> m_SwizzledTensorData;
};
-ModelToINetworkConverter::ModelToINetworkConverter(armnn::Compute compute, const Model& model,
+ModelToINetworkConverter::ModelToINetworkConverter(armnn::Compute compute, const V1_0::Model& model,
const std::set<unsigned int>& forcedUnsupportedOperations)
: m_Compute(compute)
, m_Model(model)
@@ -471,37 +471,37 @@
}
}
-bool ModelToINetworkConverter::ConvertOperation(const Operation& operation)
+bool ModelToINetworkConverter::ConvertOperation(const V1_0::Operation& operation)
{
switch (operation.type)
{
- case OperationType::ADD: return ConvertAdd(operation);
- case OperationType::AVERAGE_POOL_2D: return ConvertAveragePool2d(operation);
- case OperationType::CONCATENATION: return ConvertConcatenation(operation);
- case OperationType::CONV_2D: return ConvertConv2d(operation);
- case OperationType::DEPTHWISE_CONV_2D: return ConvertDepthwiseConv2d(operation);
- case OperationType::FLOOR: return ConvertFloor(operation);
- case OperationType::FULLY_CONNECTED: return ConvertFullyConnected(operation);
- case OperationType::LOCAL_RESPONSE_NORMALIZATION: return ConvertLocalResponseNormalization(operation);
- case OperationType::LOGISTIC: return ConvertLogistic(operation);
- case OperationType::L2_NORMALIZATION: return ConvertL2Normalization(operation);
- case OperationType::L2_POOL_2D: return ConvertL2Pool2d(operation);
- case OperationType::MAX_POOL_2D: return ConvertMaxPool2d(operation);
- case OperationType::MUL: return ConvertMul(operation);
- case OperationType::RELU: return ConvertReLu(operation);
- case OperationType::RELU1: return ConvertReLu1(operation);
- case OperationType::RELU6: return ConvertReLu6(operation);
- case OperationType::SOFTMAX: return ConvertSoftmax(operation);
- case OperationType::TANH: return ConvertTanH(operation);
- case OperationType::RESHAPE: return ConvertReshape(operation);
- case OperationType::RESIZE_BILINEAR: return ConvertResizeBilinear(operation);
+ case V1_0::OperationType::ADD: return ConvertAdd(operation);
+ case V1_0::OperationType::AVERAGE_POOL_2D: return ConvertAveragePool2d(operation);
+ case V1_0::OperationType::CONCATENATION: return ConvertConcatenation(operation);
+ case V1_0::OperationType::CONV_2D: return ConvertConv2d(operation);
+ case V1_0::OperationType::DEPTHWISE_CONV_2D: return ConvertDepthwiseConv2d(operation);
+ case V1_0::OperationType::FLOOR: return ConvertFloor(operation);
+ case V1_0::OperationType::FULLY_CONNECTED: return ConvertFullyConnected(operation);
+ case V1_0::OperationType::LOCAL_RESPONSE_NORMALIZATION: return ConvertLocalResponseNormalization(operation);
+ case V1_0::OperationType::LOGISTIC: return ConvertLogistic(operation);
+ case V1_0::OperationType::L2_NORMALIZATION: return ConvertL2Normalization(operation);
+ case V1_0::OperationType::L2_POOL_2D: return ConvertL2Pool2d(operation);
+ case V1_0::OperationType::MAX_POOL_2D: return ConvertMaxPool2d(operation);
+ case V1_0::OperationType::MUL: return ConvertMul(operation);
+ case V1_0::OperationType::RELU: return ConvertReLu(operation);
+ case V1_0::OperationType::RELU1: return ConvertReLu1(operation);
+ case V1_0::OperationType::RELU6: return ConvertReLu6(operation);
+ case V1_0::OperationType::SOFTMAX: return ConvertSoftmax(operation);
+ case V1_0::OperationType::TANH: return ConvertTanH(operation);
+ case V1_0::OperationType::RESHAPE: return ConvertReshape(operation);
+ case V1_0::OperationType::RESIZE_BILINEAR: return ConvertResizeBilinear(operation);
default: return Fail("%s: Operation type %s not supported in ArmnnDriver",
__func__, toString(operation.type).c_str());
}
}
-bool ModelToINetworkConverter::ConvertAdd(const Operation& operation)
+bool ModelToINetworkConverter::ConvertAdd(const V1_0::Operation& operation)
{
LayerInputHandle input0 = ConvertToLayerInputHandle(operation, 0);
LayerInputHandle input1 = ConvertToLayerInputHandle(operation, 1);
@@ -594,12 +594,12 @@
}
}
-bool ModelToINetworkConverter::ConvertAveragePool2d(const Operation& operation)
+bool ModelToINetworkConverter::ConvertAveragePool2d(const V1_0::Operation& operation)
{
return ConvertPooling2d(operation, __func__, armnn::PoolingAlgorithm::Average);
}
-bool ModelToINetworkConverter::ConvertConcatenation(const Operation& operation)
+bool ModelToINetworkConverter::ConvertConcatenation(const V1_0::Operation& operation)
{
// The first N (0..N-1) inputs are tensors. The Nth input is the concatenation axis.
if (operation.inputs.size() <= 1)
@@ -758,7 +758,7 @@
return SetupAndTrackLayerOutputSlot(operation, 0, *layer);
}
-bool ModelToINetworkConverter::ConvertConv2d(const Operation& operation)
+bool ModelToINetworkConverter::ConvertConv2d(const V1_0::Operation& operation)
{
LayerInputHandle input = ConvertToLayerInputHandle(operation, 0);
if (!input.IsValid())
@@ -860,7 +860,7 @@
}
}
-bool ModelToINetworkConverter::ConvertDepthwiseConv2d(const Operation& operation)
+bool ModelToINetworkConverter::ConvertDepthwiseConv2d(const V1_0::Operation& operation)
{
LayerInputHandle input = ConvertToLayerInputHandle(operation, 0);
if (!input.IsValid())
@@ -979,7 +979,7 @@
}
}
-bool ModelToINetworkConverter::ConvertFloor(const Operation& operation)
+bool ModelToINetworkConverter::ConvertFloor(const V1_0::Operation& operation)
{
LayerInputHandle input = ConvertToLayerInputHandle(operation, 0);
if (!input.IsValid())
@@ -1009,7 +1009,7 @@
return SetupAndTrackLayerOutputSlot(operation, 0, *layer);
}
-bool ModelToINetworkConverter::ConvertFullyConnected(const Operation& operation)
+bool ModelToINetworkConverter::ConvertFullyConnected(const V1_0::Operation& operation)
{
LayerInputHandle input = ConvertToLayerInputHandle(operation, 0);
if (!input.IsValid())
@@ -1100,7 +1100,7 @@
}
}
-bool ModelToINetworkConverter::ConvertLocalResponseNormalization(const Operation& operation)
+bool ModelToINetworkConverter::ConvertLocalResponseNormalization(const V1_0::Operation& operation)
{
LayerInputHandle input = ConvertToLayerInputHandle(operation, 0);
if (!input.IsValid())
@@ -1158,7 +1158,7 @@
return SetupAndTrackLayerOutputSlot(operation, 0, outSwizzleLayer);
}
-bool ModelToINetworkConverter::ConvertLogistic(const Operation& operation)
+bool ModelToINetworkConverter::ConvertLogistic(const V1_0::Operation& operation)
{
armnn::ActivationDescriptor desc;
desc.m_Function = armnn::ActivationFunction::Sigmoid;
@@ -1166,7 +1166,7 @@
return ConvertToActivation(operation, __func__, desc);
}
-bool ModelToINetworkConverter::ConvertL2Normalization(const Operation& operation)
+bool ModelToINetworkConverter::ConvertL2Normalization(const V1_0::Operation& operation)
{
LayerInputHandle input = ConvertToLayerInputHandle(operation, 0);
if (!input.IsValid())
@@ -1203,17 +1203,17 @@
return SetupAndTrackLayerOutputSlot(operation, 0, outSwizzleLayer);
}
-bool ModelToINetworkConverter::ConvertL2Pool2d(const Operation& operation)
+bool ModelToINetworkConverter::ConvertL2Pool2d(const V1_0::Operation& operation)
{
return ConvertPooling2d(operation, __func__, armnn::PoolingAlgorithm::L2);
}
-bool ModelToINetworkConverter::ConvertMaxPool2d(const Operation& operation)
+bool ModelToINetworkConverter::ConvertMaxPool2d(const V1_0::Operation& operation)
{
return ConvertPooling2d(operation, __func__, armnn::PoolingAlgorithm::Max);
}
-bool ModelToINetworkConverter::ConvertMul(const Operation& operation)
+bool ModelToINetworkConverter::ConvertMul(const V1_0::Operation& operation)
{
LayerInputHandle input0 = ConvertToLayerInputHandle(operation, 0);
LayerInputHandle input1 = ConvertToLayerInputHandle(operation, 1);
@@ -1268,7 +1268,7 @@
}
}
-bool ModelToINetworkConverter::ConvertReLu(const Operation& operation)
+bool ModelToINetworkConverter::ConvertReLu(const V1_0::Operation& operation)
{
armnn::ActivationDescriptor desc;
desc.m_Function = armnn::ActivationFunction::ReLu;
@@ -1276,7 +1276,7 @@
return ConvertToActivation(operation, __func__, desc);
}
-bool ModelToINetworkConverter::ConvertReLu1(const Operation& operation)
+bool ModelToINetworkConverter::ConvertReLu1(const V1_0::Operation& operation)
{
armnn::ActivationDescriptor desc;
desc.m_Function = armnn::ActivationFunction::BoundedReLu;
@@ -1286,7 +1286,7 @@
return ConvertToActivation(operation, __func__, desc);
}
-bool ModelToINetworkConverter::ConvertReLu6(const Operation& operation)
+bool ModelToINetworkConverter::ConvertReLu6(const V1_0::Operation& operation)
{
armnn::ActivationDescriptor desc;
desc.m_Function = armnn::ActivationFunction::BoundedReLu;
@@ -1295,7 +1295,7 @@
return ConvertToActivation(operation, __func__, desc);
}
-bool ModelToINetworkConverter::ConvertSoftmax(const Operation& operation)
+bool ModelToINetworkConverter::ConvertSoftmax(const V1_0::Operation& operation)
{
LayerInputHandle input = ConvertToLayerInputHandle(operation, 0);
if (!input.IsValid())
@@ -1325,7 +1325,7 @@
return SetupAndTrackLayerOutputSlot(operation, 0, *layer);
}
-bool ModelToINetworkConverter::ConvertTanH(const Operation& operation)
+bool ModelToINetworkConverter::ConvertTanH(const V1_0::Operation& operation)
{
armnn::ActivationDescriptor desc;
desc.m_Function = armnn::ActivationFunction::TanH;
@@ -1335,7 +1335,7 @@
return ConvertToActivation(operation, __func__, desc);
}
-bool ModelToINetworkConverter::ConvertReshape(const Operation& operation)
+bool ModelToINetworkConverter::ConvertReshape(const V1_0::Operation& operation)
{
const Operand* inputOperand = GetInputOperand(operation, 0);
const Operand* requestedShapeOperand = GetInputOperand(operation, 1);
@@ -1403,7 +1403,7 @@
return SetupAndTrackLayerOutputSlot(operation, 0, *layer);
}
-bool ModelToINetworkConverter::ConvertResizeBilinear(const Operation& operation)
+bool ModelToINetworkConverter::ConvertResizeBilinear(const V1_0::Operation& operation)
{
LayerInputHandle input = ConvertToLayerInputHandle(operation, 0);
if (!input.IsValid())
@@ -1449,7 +1449,7 @@
}
-bool ModelToINetworkConverter::ConvertToActivation(const Operation& operation,
+bool ModelToINetworkConverter::ConvertToActivation(const V1_0::Operation& operation,
const char* operationName,
const armnn::ActivationDescriptor& activationDesc)
{
@@ -1475,7 +1475,7 @@
return SetupAndTrackLayerOutputSlot(operation, 0, *layer);
}
-bool ModelToINetworkConverter::ConvertPooling2d(const Operation& operation,
+bool ModelToINetworkConverter::ConvertPooling2d(const V1_0::Operation& operation,
const char* operationName,
armnn::PoolingAlgorithm poolType)
{
@@ -1625,7 +1625,7 @@
return valueStart;
}
-const Operand* ModelToINetworkConverter::GetInputOperand(const Operation& operation, uint32_t inputIndex) const
+const Operand* ModelToINetworkConverter::GetInputOperand(const V1_0::Operation& operation, uint32_t inputIndex) const
{
if (inputIndex >= operation.inputs.size())
{
@@ -1637,7 +1637,7 @@
return &m_Model.operands[operation.inputs[inputIndex]];
}
-const Operand* ModelToINetworkConverter::GetOutputOperand(const Operation& operation, uint32_t outputIndex) const
+const Operand* ModelToINetworkConverter::GetOutputOperand(const V1_0::Operation& operation, uint32_t outputIndex) const
{
if (outputIndex >= operation.outputs.size())
{
@@ -1650,7 +1650,7 @@
}
template<typename T>
-bool ModelToINetworkConverter::GetInputScalar(const Operation& operation, uint32_t inputIndex,
+bool ModelToINetworkConverter::GetInputScalar(const V1_0::Operation& operation, uint32_t inputIndex,
OperandType type, T& outValue) const
{
const Operand* operand = GetInputOperand(operation, inputIndex);
@@ -1681,17 +1681,19 @@
return true;
}
-bool ModelToINetworkConverter::GetInputInt32(const Operation& operation, uint32_t inputIndex, int32_t& outValue) const
+bool ModelToINetworkConverter::GetInputInt32(const V1_0::Operation& operation,
+ uint32_t inputIndex, int32_t& outValue) const
{
return GetInputScalar(operation, inputIndex, OperandType::INT32, outValue);
}
-bool ModelToINetworkConverter::GetInputFloat32(const Operation& operation, uint32_t inputIndex, float& outValue) const
+bool ModelToINetworkConverter::GetInputFloat32(const V1_0::Operation& operation,
+ uint32_t inputIndex, float& outValue) const
{
return GetInputScalar(operation, inputIndex, OperandType::FLOAT32, outValue);
}
-bool ModelToINetworkConverter::GetInputActivationFunction(const Operation& operation,
+bool ModelToINetworkConverter::GetInputActivationFunction(const V1_0::Operation& operation,
uint32_t inputIndex,
ActivationFn& outActivationFunction) const
{
@@ -1705,7 +1707,7 @@
return true;
}
-bool ModelToINetworkConverter::GetInputPaddingScheme(const Operation& operation,
+bool ModelToINetworkConverter::GetInputPaddingScheme(const V1_0::Operation& operation,
uint32_t inputIndex,
android::nn::PaddingScheme& outPaddingScheme) const
{
@@ -1720,7 +1722,7 @@
}
LayerInputHandle ModelToINetworkConverter::ConvertToLayerInputHandle(
- const Operation& operation,
+ const V1_0::Operation& operation,
uint32_t inputIndex)
{
const Operand* operand = GetInputOperand(operation, inputIndex);
@@ -1789,7 +1791,7 @@
}
}
-ConstTensorPin ModelToINetworkConverter::ConvertOperationInputToConstTensorPin(const Operation& operation,
+ConstTensorPin ModelToINetworkConverter::ConvertOperationInputToConstTensorPin(const V1_0::Operation& operation,
uint32_t inputIndex, const armnn::PermutationVector& dimensionMappings,
const armnn::TensorShape* overrideTensorShape)
{
@@ -1931,7 +1933,7 @@
return activationLayer;
}
-bool ModelToINetworkConverter::SetupAndTrackLayerOutputSlot(const Operation& operation, uint32_t outputIndex,
+bool ModelToINetworkConverter::SetupAndTrackLayerOutputSlot(const V1_0::Operation& operation, uint32_t outputIndex,
armnn::IConnectableLayer& layer)
{
const Operand* outputOperand = GetOutputOperand(operation, outputIndex);