From 3b278e9261bd0de67c82f7d6c36731f118124f52 Mon Sep 17 00:00:00 2001
From: Aron Virginas-Tar <Aron.Virginas-Tar@arm.com>
Date: Fri, 12 Oct 2018 13:00:55 +0100
Subject: IVGCVSW-1938: Move backend-specific source files to the corresponding
 backend

Change-Id: I558a9a007604afc55e536d877f8da7d0215cc9c3
---
 src/armnn/test/FP16SupportTest.cpp | 115 -------------------------------------
 1 file changed, 115 deletions(-)
 delete mode 100644 src/armnn/test/FP16SupportTest.cpp

(limited to 'src/armnn/test/FP16SupportTest.cpp')

diff --git a/src/armnn/test/FP16SupportTest.cpp b/src/armnn/test/FP16SupportTest.cpp
deleted file mode 100644
index 2706d1f363..0000000000
--- a/src/armnn/test/FP16SupportTest.cpp
+++ /dev/null
@@ -1,115 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-#include <armnn/ArmNN.hpp>
-#include <armnn/Descriptors.hpp>
-#include <armnn/IRuntime.hpp>
-#include <armnn/INetwork.hpp>
-#include <armnnUtils/Half.hpp>
-
-#include <Graph.hpp>
-#include <Optimizer.hpp>
-#include <backends/CpuTensorHandle.hpp>
-#include <backends/test/QuantizeHelper.hpp>
-
-#include <boost/core/ignore_unused.hpp>
-#include <boost/test/unit_test.hpp>
-
-#include <set>
-
-using namespace armnn;
-
-BOOST_AUTO_TEST_SUITE(Fp16Support)
-
-BOOST_AUTO_TEST_CASE(Fp16DataTypeSupport)
-{
-    Graph graph;
-
-    Layer* const inputLayer1 = graph.AddLayer<InputLayer>(1, "input1");
-    Layer* const inputLayer2 = graph.AddLayer<InputLayer>(2, "input2");
-
-    Layer* const additionLayer = graph.AddLayer<AdditionLayer>("addition");
-    Layer* const outputLayer = graph.AddLayer<armnn::OutputLayer>(0, "output");
-
-    TensorInfo fp16TensorInfo({1, 2, 3, 5}, armnn::DataType::Float16);
-    inputLayer1->GetOutputSlot(0).Connect(additionLayer->GetInputSlot(0));
-    inputLayer2->GetOutputSlot(0).Connect(additionLayer->GetInputSlot(1));
-    additionLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
-
-    inputLayer1->GetOutputSlot().SetTensorInfo(fp16TensorInfo);
-    inputLayer2->GetOutputSlot().SetTensorInfo(fp16TensorInfo);
-    additionLayer->GetOutputSlot().SetTensorInfo(fp16TensorInfo);
-
-    BOOST_CHECK(inputLayer1->GetOutputSlot(0).GetTensorInfo().GetDataType() == armnn::DataType::Float16);
-    BOOST_CHECK(inputLayer2->GetOutputSlot(0).GetTensorInfo().GetDataType() == armnn::DataType::Float16);
-    BOOST_CHECK(additionLayer->GetOutputSlot(0).GetTensorInfo().GetDataType() == armnn::DataType::Float16);
-
-}
-
-BOOST_AUTO_TEST_CASE(Fp16AdditionTest)
-{
-   using namespace half_float::literal;
-   // Create runtime in which test will run
-   IRuntime::CreationOptions options;
-   IRuntimePtr  runtime(IRuntime::Create(options));
-
-   // Builds up the structure of the network.
-   INetworkPtr net(INetwork::Create());
-
-
-   IConnectableLayer* inputLayer1 = net->AddInputLayer(0);
-   IConnectableLayer* inputLayer2 = net->AddInputLayer(1);
-   IConnectableLayer* additionLayer = net->AddAdditionLayer();
-   IConnectableLayer* outputLayer = net->AddOutputLayer(0);
-
-   inputLayer1->GetOutputSlot(0).Connect(additionLayer->GetInputSlot(0));
-   inputLayer2->GetOutputSlot(0).Connect(additionLayer->GetInputSlot(1));
-   additionLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
-
-   //change to float16
-   TensorInfo fp16TensorInfo(TensorShape({4}), DataType::Float16);
-   inputLayer1->GetOutputSlot(0).SetTensorInfo(fp16TensorInfo);
-   inputLayer2->GetOutputSlot(0).SetTensorInfo(fp16TensorInfo);
-   additionLayer->GetOutputSlot(0).SetTensorInfo(fp16TensorInfo);
-
-   // optimize the network
-   std::vector<Compute> backends = {Compute::GpuAcc};
-   IOptimizedNetworkPtr optNet = Optimize(*net, backends, runtime->GetDeviceSpec());
-
-   // Loads it into the runtime.
-
-   NetworkId netId;
-   runtime->LoadNetwork(netId, std::move(optNet));
-
-   std::vector<Half> input1Data
-   {
-       1.0_h, 2.0_h, 3.0_h, 4.0_h
-   };
-
-   std::vector<Half> input2Data
-   {
-       100.0_h, 200.0_h, 300.0_h, 400.0_h
-   };
-
-   InputTensors inputTensors
-   {
-       {0,ConstTensor(runtime->GetInputTensorInfo(netId, 0), input1Data.data())},
-       {1,ConstTensor(runtime->GetInputTensorInfo(netId, 0), input2Data.data())}
-   };
-
-   std::vector<Half> outputData(input1Data.size());
-   OutputTensors outputTensors
-   {
-       {0,Tensor(runtime->GetOutputTensorInfo(netId, 0), outputData.data())}
-   };
-
-   // Does the inference.
-   runtime->EnqueueWorkload(netId, inputTensors, outputTensors);
-
-   // Checks the results.
-   BOOST_TEST(outputData == std::vector<Half>({ 101.0_h, 202.0_h, 303.0_h, 404.0_h})); // Add
-}
-
-BOOST_AUTO_TEST_SUITE_END()
-- 
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