From a38da5989dc51fe2665480d18a9dd9dff6bb1115 Mon Sep 17 00:00:00 2001
From: Teresa Charlin <teresa.charlinreyes@arm.com>
Date: Mon, 31 Oct 2022 22:09:23 +0000
Subject: IVGCVSW-6496 Add EndToEnd Layer test for Batch MatMul Workload

Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: I6a541db9a602609282cc6f33af930ca141b83c41
---
 .../test/BatchMatMulEndToEndTestImpl.hpp           | 84 ++++++++++++++++++++++
 1 file changed, 84 insertions(+)
 create mode 100644 src/backends/backendsCommon/test/BatchMatMulEndToEndTestImpl.hpp

(limited to 'src/backends/backendsCommon')

diff --git a/src/backends/backendsCommon/test/BatchMatMulEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/BatchMatMulEndToEndTestImpl.hpp
new file mode 100644
index 0000000000..905a56d53a
--- /dev/null
+++ b/src/backends/backendsCommon/test/BatchMatMulEndToEndTestImpl.hpp
@@ -0,0 +1,84 @@
+//
+// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#pragma once
+
+#include <ResolveType.hpp>
+
+#include <armnn/INetwork.hpp>
+
+#include <doctest/doctest.h>
+#include <CommonTestUtils.hpp>
+
+namespace
+{
+
+template<typename armnn::DataType DataType>
+armnn::INetworkPtr CreateBatchMatMulNetwork(const armnn::TensorShape& inputXShape,
+                                     const armnn::TensorShape& inputYShape,
+                                     const armnn::TensorShape& outputShape,
+                                     const float qScale = 1.0f,
+                                     const int32_t qOffset = 0)
+{
+    using namespace armnn;
+
+    INetworkPtr network(INetwork::Create());
+
+    TensorInfo inputXTensorInfo(inputXShape, DataType, qScale, qOffset, true);
+    TensorInfo inputYTensorInfo(inputYShape, DataType, qScale, qOffset, true);
+
+    TensorInfo outputTensorInfo(outputShape, DataType, qScale, qOffset);
+
+    BatchMatMulDescriptor batchMatMulDesc;
+    batchMatMulDesc.m_TransposeX = false;
+    batchMatMulDesc.m_TransposeY = true;
+
+    IConnectableLayer* batchMatMul = network->AddBatchMatMulLayer(batchMatMulDesc, "batchMatMul");
+    IConnectableLayer* inputX = network->AddInputLayer(0, "inputX");
+    IConnectableLayer* inputY = network->AddInputLayer(1, "inputY");
+    IConnectableLayer* output = network->AddOutputLayer(0, "output");
+
+    Connect(inputX, batchMatMul, inputXTensorInfo, 0, 0);
+    Connect(inputY, batchMatMul, inputYTensorInfo, 0, 1);
+    Connect(batchMatMul, output, outputTensorInfo, 0, 0);
+
+    return network;
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+void BatchMatMulEndToEnd(const std::vector<armnn::BackendId>& backends)
+{
+    using namespace armnn;
+
+    const TensorShape& inputXShape = { 2, 2, 2 };
+    const TensorShape& inputYShape = { 2, 2, 2 };
+    const TensorShape& outputShape = { 2, 2, 2 };
+
+    INetworkPtr network = CreateBatchMatMulNetwork<ArmnnType>(inputXShape, inputYShape, outputShape);
+
+    CHECK(network);
+
+    std::vector<T> inputXData{ 1, 2,
+                               3, 4,
+
+                               9, 10,
+                               11, 12 };
+    std::vector<T> inputYData{ 5, 7,
+                               6, 8,
+
+                               13, 15,
+                               14, 16 };
+    std::vector<T> expectedOutput{ 19, 22,
+                                   43, 50,
+
+                                   267, 286,
+                                   323, 346 };
+
+    std::map<int, std::vector<T>> inputTensorData = {{ 0, inputXData }, {1, inputYData}};
+    std::map<int, std::vector<T>> expectedOutputData = { { 0, expectedOutput } };
+
+    EndToEndLayerTestImpl<ArmnnType, ArmnnType>(std::move(network), inputTensorData, expectedOutputData, backends);
+}
+
+} // anonymous namespace
\ No newline at end of file
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