IVGCVSW-5736 and IVGCVSW-5743 'NonConstWeights: Update front-end and TfLiteDelegate support for FullyConnected Operator'
* Added front-end support for non-const weights for FULLY_CONNECTED operator
* Added FULLY_CONNECTED end-to-end test
* Updated FULLY_CONNECTED operator support in TfLite Arm NN Delegate for non-const weights
* Updated the version numbers
Signed-off-by: Sadik Armagan <sadik.armagan@arm.com>
Change-Id: Iffa5b9aa9297aca4c02d923cce4636c88ac21faa
diff --git a/src/backends/backendsCommon/test/FullyConnectedEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/FullyConnectedEndToEndTestImpl.hpp
new file mode 100644
index 0000000..5a618c3
--- /dev/null
+++ b/src/backends/backendsCommon/test/FullyConnectedEndToEndTestImpl.hpp
@@ -0,0 +1,97 @@
+//
+// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#pragma once
+
+#include "CommonTestUtils.hpp"
+
+#include <ResolveType.hpp>
+
+#include <armnn/INetwork.hpp>
+
+#include <armnn/utility/NumericCast.hpp>
+
+#include <boost/test/unit_test.hpp>
+
+#include <vector>
+
+namespace
+{
+
+armnn::INetworkPtr CreateFullyConnectedNetworkNonConstWeights(const armnn::TensorInfo& inputTensorInfo,
+ const armnn::TensorInfo& outputTensorInfo,
+ const armnn::TensorInfo& weightsTensorInfo,
+ armnn::FullyConnectedDescriptor descriptor)
+{
+ armnn::INetworkPtr network(armnn::INetwork::Create());
+
+ armnn::IConnectableLayer* inputLayer = network->AddInputLayer(0, "Input");
+ armnn::IConnectableLayer* weightsInputLayer = network->AddInputLayer(1, "Weights_Input");
+ armnn::IConnectableLayer* fullyConnectedLayer = network->AddFullyConnectedLayer(descriptor,
+ armnn::EmptyOptional(),
+ armnn::EmptyOptional(),
+ "Fully_Connected");
+ armnn::IConnectableLayer* outputLayer = network->AddOutputLayer(0, "Output");
+
+ Connect(inputLayer, fullyConnectedLayer, inputTensorInfo, 0, 0);
+ Connect(weightsInputLayer, fullyConnectedLayer, weightsTensorInfo, 0, 1);
+ Connect(fullyConnectedLayer, outputLayer, outputTensorInfo, 0, 0);
+
+ return network;
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+void FullyConnectedWithDynamicWeightsEndToEnd(const std::vector<armnn::BackendId>& backends)
+{
+ using namespace armnn;
+
+ armnn::TensorInfo inputTensorInfo({ 1, 1, 2, 3 }, ArmnnType);
+ inputTensorInfo.SetQuantizationScale(0.1f);
+ inputTensorInfo.SetQuantizationOffset(63);
+
+ armnn::TensorInfo outputTensorInfo({ 1, 2 }, ArmnnType);
+ outputTensorInfo.SetQuantizationScale(5.f);
+ outputTensorInfo.SetQuantizationOffset(10);
+
+ armnn::TensorInfo weightsTensorInfo({ 2, 6 }, ArmnnType);
+ weightsTensorInfo.SetQuantizationScale(0.2f);
+ weightsTensorInfo.SetQuantizationOffset(93);
+
+ FullyConnectedDescriptor descriptor;
+ descriptor.m_ConstantWeights = false;
+ descriptor.m_BiasEnabled = false;
+ descriptor.m_TransposeWeightMatrix = true;
+
+ std::vector<T> inputData {
+ -1.2f, 6.1f, -3.5f,
+ 18.8f, -5.5f, 2.9f
+ };
+
+ std::vector<T> weightsData {
+ -8.4f, 20.0f, -10.4f, -8, 16.4f, -11.8f,
+ 23.4f, 10.4f, -14.0f, -3.8f, -11.8f, 11.4f
+ };
+
+ std::vector<T> floatExpectedOutputData {
+ -107.04f, 110.f
+ };
+ std::vector<T> expectedOutputData = armnnUtils::QuantizedVector<T>(floatExpectedOutputData);
+
+ armnn::INetworkPtr network = CreateFullyConnectedNetworkNonConstWeights(inputTensorInfo,
+ outputTensorInfo,
+ weightsTensorInfo,
+ descriptor);
+
+ BOOST_TEST_CHECKPOINT("create a network");
+
+ std::map<int, std::vector<T>> inputTensorData = {{ 0, inputData }, {1, weightsData}};
+ std::map<int, std::vector<T>> expectedOutputTensorData = {{ 0, expectedOutputData }};
+
+ EndToEndLayerTestImpl<ArmnnType, ArmnnType>(move(network),
+ inputTensorData,
+ expectedOutputTensorData,
+ backends,
+ 1.0f);
+}
+} // anonymous namespace