IVGCVSW-7204 Add TransposeConv2d support to TOSA Reference Backend
Signed-off-by: Matthew Sloyan <matthew.sloyan@arm.com>
Change-Id: I9bfd597afd41468f304edfbe5d7141378ce60d4f
diff --git a/src/backends/backendsCommon/test/TransposeConvolution2dEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/TransposeConvolution2dEndToEndTestImpl.hpp
index e12813a..47d6c28 100644
--- a/src/backends/backendsCommon/test/TransposeConvolution2dEndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/TransposeConvolution2dEndToEndTestImpl.hpp
@@ -1,5 +1,5 @@
//
-// Copyright © 2017 Arm Ltd. All rights reserved.
+// Copyright © 2017,2022 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
@@ -147,3 +147,71 @@
{ { 0, qExpectedOutputData } },
backends);
}
+
+template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType>
+void SimpleTransposeConvolution2dEndToEnd(const std::vector<armnn::BackendId>& backends,
+ armnn::DataLayout dataLayout)
+{
+ using namespace armnn;
+ using T = ResolveType<ArmnnType>;
+
+ const float qScale = IsQuantizedType<T>() ? 0.25f : 1.0f;
+ const int32_t qOffset = IsQuantizedType<T>() ? 50 : 0;
+
+ TensorInfo inputInfo({1, 2, 2, 1}, ArmnnType, qScale, qOffset, true);
+ TensorInfo outputInfo({1, 3, 3, 1}, ArmnnType, qScale, qOffset);
+ TensorInfo weightsInfo({1, 2, 2, 1}, ArmnnType, qScale, qOffset, true);
+ TensorInfo biasesInfo({ 1 }, ArmnnBType, qScale * qScale, 0, true);
+
+ std::vector<float> inputData =
+ {
+ 1, 2, 3, 4
+ };
+
+ std::vector<float> weightsData =
+ {
+ 0, 1, 2, 4
+ };
+ std::vector<float> biasesData = { 0.f };
+
+ std::vector<float> expectedOutputData =
+ {
+ 0, 1, 2,
+ 2, 11, 12,
+ 6, 20, 16
+ };
+
+ TransposeConvolution2dDescriptor descriptor;
+ descriptor.m_PadLeft = 0;
+ descriptor.m_PadRight = 0;
+ descriptor.m_PadTop = 0;
+ descriptor.m_PadBottom = 0;
+ descriptor.m_StrideX = 1;
+ descriptor.m_StrideY = 1;
+ descriptor.m_BiasEnabled = true;
+ descriptor.m_DataLayout = dataLayout;
+ descriptor.m_OutputShapeEnabled = true;
+ descriptor.m_OutputShape = { 1, 3, 3, 1 };
+
+ // quantize data
+ std::vector<T> qInputData = armnnUtils::QuantizedVector<T>(inputData, qScale, qOffset);
+ std::vector<T> qWeightsData = armnnUtils::QuantizedVector<T>(weightsData, qScale, qOffset);
+ std::vector<T> qExpectedOutputData = armnnUtils::QuantizedVector<T>(expectedOutputData, qScale, qOffset);
+
+ using BT = ResolveType<ArmnnBType>;
+ std::vector<BT> qBiasesData = armnnUtils::QuantizedVector<BT>(biasesData, qScale * qScale, 0);
+
+ ConstTensor weights(weightsInfo, qWeightsData);
+ ConstTensor biases(biasesInfo, qBiasesData);
+
+ INetworkPtr network = CreateTransposeConvolution2dNetwork(descriptor,
+ inputInfo,
+ outputInfo,
+ weights,
+ Optional<ConstTensor>(biases));
+
+ EndToEndLayerTestImpl<ArmnnType, ArmnnType>(std::move(network),
+ { { 0, qInputData } },
+ { { 0, qExpectedOutputData } },
+ backends);
+}