IVGCVSW-5305 AddBroadcastReshapeLayer as optimizer
* Remove AddBroadcastReshapeLayer from TfLiteParser
* Add AddBroadcastReshapeLayer as optimizer
* AddBroadcastReshapeLayer optimizer unit tests
* Load-scope dynamic tensor broadcasting unit tests
Signed-off-by: Narumol Prangnawarat <narumol.prangnawarat@arm.com>
Change-Id: I3549e85b71b41cbd4d96c0f1ece7887acbca76d1
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index 109c2c2..6143f4a 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -443,7 +443,7 @@
}
}
-armnn::TensorInfo ToTensorInfo(TfLiteParser::TensorRawPtr tensorPtr,
+armnn::TensorInfo ToTensorInfo(TfLiteParser::TensorRawPtr tensorPtr,
const armnn::PermutationVector& dimensionMappings = {0, 1, 2, 3})
{
auto const & dimensions = AsUnsignedVector(tensorPtr->shape);
@@ -609,69 +609,6 @@
m_SubgraphConnections.clear();
}
-void TfLiteParser::AddBroadcastReshapeLayer(size_t subgraphIndex,
- size_t operatorIndex,
- IConnectableLayer *layer)
-{
- CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
- ARMNN_ASSERT(layer != nullptr);
-
- const auto & subgraphPtr = m_Model->subgraphs[subgraphIndex];
- const auto & operatorPtr = subgraphPtr->operators[operatorIndex];
-
- ARMNN_ASSERT(operatorPtr->inputs.size() > 1);
-
- uint32_t reshapedInputId = CHECKED_NON_NEGATIVE(operatorPtr->inputs[0]);
- TensorRawPtr tensorPtr = subgraphPtr->tensors[reshapedInputId].get();
- uint32_t inputId = CHECKED_NON_NEGATIVE(operatorPtr->inputs[1]);
- TensorRawPtr tensorPtr1 = subgraphPtr->tensors[inputId].get();
-
- armnn::TensorInfo reshapedTensorInfo = ToTensorInfo(tensorPtr);
- armnn::TensorInfo inputTensorInfo = ToTensorInfo(tensorPtr1);
-
- uint32_t inputSlotId = 1;
- uint32_t reshapeSlotId = 0;
-
- if (inputTensorInfo.GetNumDimensions() < reshapedTensorInfo.GetNumDimensions())
- {
- uint32_t id = reshapedInputId;
- reshapedInputId = inputId;
- inputId = id;
-
- reshapedTensorInfo = ToTensorInfo(tensorPtr1);
- inputTensorInfo = ToTensorInfo(tensorPtr);
-
- inputSlotId = 0;
- reshapeSlotId = 1;
- }
-
- uint32_t numDimensions = inputTensorInfo.GetNumDimensions();
-
- std::vector<unsigned> reshapedDim;
- for (unsigned int i = 0; i < reshapedTensorInfo.GetNumDimensions(); ++i)
- {
- reshapedDim.push_back(reshapedTensorInfo.GetShape()[i]);
- }
-
- std::vector<unsigned int> reshapedDimensions(numDimensions, 1);
- std::copy_backward (reshapedDim.begin(), reshapedDim.end(), reshapedDimensions.end());
-
- reshapedTensorInfo.SetShape(armnn::TensorShape{ numDimensions, reshapedDimensions.data() });
-
- std::string layerName = boost::str(boost::format("Reshape_for:%1%") % layer->GetName());
- armnn::ReshapeDescriptor desc;
- desc.m_TargetShape = reshapedTensorInfo.GetShape();
- armnn::IConnectableLayer* reshapeLayer = m_Network->AddReshapeLayer(desc, layerName.c_str());
-
- reshapeLayer->GetOutputSlot(0).SetTensorInfo(reshapedTensorInfo);
- reshapeLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(reshapeSlotId));
-
- RegisterInputSlots(subgraphIndex, operatorIndex, reshapeLayer, {reshapedInputId});
-
- armnn::IInputSlot* input1Slot = &(layer->GetInputSlot(inputSlotId));
- RegisterConsumerOfTensor(subgraphIndex, inputId, input1Slot);
-}
-
INetworkPtr TfLiteParser::CreateNetworkFromBinaryFile(const char* graphFile)
{
ResetParser();
@@ -995,7 +932,7 @@
// Mappings from TensorflowLite filter tensors to the ArmNN filter tensors (ArmNN weights have to be [M, I, H, W])
PermutationVector permutationVector{ 2, 3, 1, 0 }; // [H, W, I, M] -> [M, I, H, W]
-
+
armnn::TensorInfo inputTensorInfo = ToTensorInfo(inputs[0]);
armnn::TensorInfo filterTensorInfo = ToTensorInfo(inputs[1], permutationVector);
@@ -1353,14 +1290,7 @@
layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
- if (inputTensorInfo.GetNumDimensions() != input1TensorInfo.GetNumDimensions())
- {
- AddBroadcastReshapeLayer(subgraphIndex, operatorIndex, layer);
- }
- else
- {
- RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0], inputTensorIndexes[1]});
- }
+ RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0], inputTensorIndexes[1]});
auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex));
RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]});
@@ -1390,14 +1320,7 @@
layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
- if (inputTensorInfo.GetNumDimensions() != input1TensorInfo.GetNumDimensions())
- {
- AddBroadcastReshapeLayer(subgraphIndex, operatorIndex, layer);
- }
- else
- {
- RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0], inputTensorIndexes[1]});
- }
+ RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0], inputTensorIndexes[1]});
auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex));
RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]});
@@ -1768,14 +1691,7 @@
layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
- if (inputTensorInfo.GetNumDimensions() != input1TensorInfo.GetNumDimensions())
- {
- AddBroadcastReshapeLayer(subgraphIndex, operatorIndex, layer);
- }
- else
- {
- RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0], inputTensorIndexes[1]});
- }
+ RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0], inputTensorIndexes[1]});
layer = AddFusedActivationLayer(layer, 0, options->fused_activation_function);
@@ -1807,15 +1723,7 @@
layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
- if (inputTensorInfo.GetNumDimensions() != input1TensorInfo.GetNumDimensions())
- {
- AddBroadcastReshapeLayer(subgraphIndex, operatorIndex, layer);
- }
- else
- {
- RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0], inputTensorIndexes[1]});
- }
-
+ RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0], inputTensorIndexes[1]});
layer = AddFusedActivationLayer(layer, 0, options->fused_activation_function);
auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex));
@@ -1846,15 +1754,7 @@
layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
- if (inputTensorInfo.GetNumDimensions() != input1TensorInfo.GetNumDimensions())
- {
- AddBroadcastReshapeLayer(subgraphIndex, operatorIndex, layer);
- }
- else
- {
- RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0], inputTensorIndexes[1]});
- }
-
+ RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0], inputTensorIndexes[1]});
layer = AddFusedActivationLayer(layer, 0, options->fused_activation_function);
auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex));
@@ -1885,15 +1785,7 @@
layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
- if (inputTensorInfo.GetNumDimensions() != input1TensorInfo.GetNumDimensions())
- {
- AddBroadcastReshapeLayer(subgraphIndex, operatorIndex, layer);
- }
- else
- {
- RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0], inputTensorIndexes[1]});
- }
-
+ RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0], inputTensorIndexes[1]});
layer = AddFusedActivationLayer(layer, 0, options->fused_activation_function);
auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex));