Add ConstTensorsAsInput support for Conv3d
* Constant weights and biases are now stored as Constant layers.
* Updated Serializer, Deserializer and unit tests to reflect this.
* Updated TfLiteParser.
* Updated Ref backend to handle constant weights and
bias as inputs rather than reading from member variables.
* Added Conv3d EndToEnd test.
* Added NCDHW DataLayout and unit tests.
Signed-off-by: Matthew Sloyan <matthew.sloyan@arm.com>
Change-Id: I10cdd354ca5f1c748730f92ffdb36bf810f83c8e
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index 81d491a..7db5d85 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -1099,36 +1099,29 @@
auto filterTensorAndData = CreateConstTensorNonPermuted(inputs[1], filterTensorInfo);
- armnn::IConnectableLayer* layer = nullptr;
auto layerName = fmt::format("Conv3D:{}:{}", subgraphIndex, operatorIndex);
+ auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
+ // Add the first input and weights tensor to the registration list.
+ // The constant weights will be added by SetupConstantLayers.
+ std::vector<unsigned int> tensorIndexesToRegister = {inputTensorIndexes[0], inputTensorIndexes[1]};
+
if (inputs.size() == 3)
{
desc.m_BiasEnabled = true;
- armnn::TensorInfo biasTensorInfo = ToTensorInfo(inputs[2]);
- auto biasTensorAndData = CreateConstTensorNonPermuted(inputs[2], biasTensorInfo);
- layer = m_Network->AddConvolution3dLayer(desc,
- filterTensorAndData,
- Optional<ConstTensor>(biasTensorAndData),
- layerName.c_str());
- }
- else
- {
- layer = m_Network->AddConvolution3dLayer(desc,
- filterTensorAndData,
- EmptyOptional(),
- layerName.c_str());
+
+ // Add the biases input to the registration list, a constant layer will be added by SetupConstantLayers.
+ tensorIndexesToRegister.emplace_back(inputTensorIndexes[2]);
}
+ armnn::IConnectableLayer* layer = m_Network->AddConvolution3dLayer(desc, layerName.c_str());
ARMNN_ASSERT(layer != nullptr);
armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0], true);
layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
// Register the input connection slots for the layer, connections are made after all layers have been created
- // only the tensors for the inputs are relevant, exclude the const tensors
- auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
- RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0]});
+ RegisterInputSlots(subgraphIndex, operatorIndex, layer, tensorIndexesToRegister);
layer = AddFusedActivationLayer(layer, 0, options->fused_activation_function);
// Register the output connection slots for the layer, connections are made after all layers have been created