From 7cf0eaa26c1fb29ca9df97e4734ec7c1e10f81c4 Mon Sep 17 00:00:00 2001
From: Aron Virginas-Tar <Aron.Virginas-Tar@arm.com>
Date: Thu, 24 Jan 2019 17:05:36 +0000
Subject: IVGCVSW-2564 Add support for multiple input and output bindings in
 InferenceModel

Change-Id: I64d724367d42dca4b768b6c6e42acda714985950
---
 .../MultipleNetworksCifar10/MultipleNetworksCifar10.cpp | 17 +++++++++++++----
 1 file changed, 13 insertions(+), 4 deletions(-)

(limited to 'tests/MultipleNetworksCifar10/MultipleNetworksCifar10.cpp')

diff --git a/tests/MultipleNetworksCifar10/MultipleNetworksCifar10.cpp b/tests/MultipleNetworksCifar10/MultipleNetworksCifar10.cpp
index f31e0c95a9..44b8890fc2 100644
--- a/tests/MultipleNetworksCifar10/MultipleNetworksCifar10.cpp
+++ b/tests/MultipleNetworksCifar10/MultipleNetworksCifar10.cpp
@@ -173,14 +173,23 @@ int main(int argc, char* argv[])
             // Loads test case data (including image data).
             std::unique_ptr<Cifar10Database::TTestCaseData> testCaseData = cifar10.GetTestCaseData(i);
 
-            // Tests inference.
-            std::vector<std::array<float, 10>> outputs(networksCount);
+            using TInputContainer  = std::vector<float>;
+            using TOutputContainer = std::array<float, 10>;
 
+            // Tests inference.
+            std::vector<TOutputContainer> outputs(networksCount);
             for (unsigned int k = 0; k < networksCount; ++k)
             {
+                using BindingPointInfo = InferenceModelInternal::BindingPointInfo;
+                std::vector<BindingPointInfo> inputBindings  = { networks[k].m_InputBindingInfo  };
+                std::vector<BindingPointInfo> outputBindings = { networks[k].m_OutputBindingInfo };
+
+                std::vector<TInputContainer> inputData   = { testCaseData->m_InputImage };
+                std::vector<TOutputContainer> outputData = { outputs[k] };
+
                 status = runtime->EnqueueWorkload(networks[k].m_Network,
-                    MakeInputTensors(networks[k].m_InputBindingInfo, testCaseData->m_InputImage),
-                    MakeOutputTensors(networks[k].m_OutputBindingInfo, outputs[k]));
+                    MakeInputTensors(inputBindings, inputData),
+                    MakeOutputTensors(outputBindings, outputData));
                 if (status == armnn::Status::Failure)
                 {
                     BOOST_LOG_TRIVIAL(fatal) << "armnn::IRuntime: Failed to enqueue workload";
-- 
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