Creating gh-pages documentation for ArmNN

Signed-off-by: Jim Flynn <jim.flynn@arm.com>

1 files changed, 0 insertions, 135 deletions

diff --git a/src/armnn/test/optimizations/PermuteAndBatchToSpaceAsDepthToSpaceTests.cpp b/src/armnn/test/optimizations/PermuteAndBatchToSpaceAsDepthToSpaceTests.cpp
deleted file mode 100644
index 74ee18b482..0000000000
--- a/src/armnn/test/optimizations/PermuteAndBatchToSpaceAsDepthToSpaceTests.cpp
+++ /dev/null
@@ -1,135 +0,0 @@
-//
-// Copyright © 2019 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-#include "../TestUtils.hpp"
-
-#include <Network.hpp>
-#include <Optimizer.hpp>
-
-#include <boost/test/unit_test.hpp>
-
-using namespace armnn;
-
-BOOST_AUTO_TEST_SUITE(Optimizer)
-using namespace armnn::optimizations;
-
-namespace
-{
-
-/// Shared function for the below tests, so that we test the same network in both cases.
-INetworkPtr CreateTestNetwork()
-{
-    // Create a network
-    INetworkPtr network = INetwork::Create();
-
-    auto input = network->AddInputLayer(0, "input");
-    const TensorInfo inputInfo({ 1, 2, 3, 4 }, DataType::Float32);
-    input->GetOutputSlot(0).SetTensorInfo(inputInfo);
-
-    // Insert Permute which swaps batches and channels dimensions
-    auto permute = network->AddPermuteLayer(PermuteDescriptor(PermutationVector{ 3, 1, 2, 0 }), "permute");
-    const TensorInfo permuteInfo({ 4, 2, 3, 1 }, DataType::Float32);
-    permute->GetOutputSlot(0).SetTensorInfo(permuteInfo);
-    input->GetOutputSlot(0).Connect(permute->GetInputSlot(0));
-
-    // Insert BatchToSpace
-    BatchToSpaceNdDescriptor batchToSpaceDesc;
-    batchToSpaceDesc.m_BlockShape = { 2, 2 };
-    batchToSpaceDesc.m_DataLayout = DataLayout::NHWC;
-    auto batchToSpace             = network->AddBatchToSpaceNdLayer(batchToSpaceDesc, "batchToSpace");
-    const TensorInfo batchToSpaceInfo({ 1, 4, 6, 1 }, DataType::Float32);
-    batchToSpace->GetOutputSlot(0).SetTensorInfo(batchToSpaceInfo);
-    permute->GetOutputSlot(0).Connect(batchToSpace->GetInputSlot(0));
-
-    auto output = network->AddOutputLayer(0, "output");
-    batchToSpace->GetOutputSlot(0).Connect(output->GetInputSlot(0));
-
-    return network;
-}
-
-}    // namespace
-
-/// Tests that the optimization performed by PermuteAndBatchToSpaceAsDepthToSpace is as expected.
-/// Note this does not ensure the correctness of the optimization - that is done in the below test.
-BOOST_AUTO_TEST_CASE(PermuteAndBatchToSpaceAsDepthToSpaceOptimizerTest)
-{
-    INetworkPtr network = CreateTestNetwork();
-    Graph graph         = static_cast<Network*>(network.get())->GetGraph();
-
-    // Confirm initial graph is as we expect
-    BOOST_TEST(CheckSequence(graph.cbegin(), graph.cend(), &IsLayerOfType<InputLayer>, &IsLayerOfType<PermuteLayer>,
-                             &IsLayerOfType<BatchToSpaceNdLayer>, &IsLayerOfType<OutputLayer>));
-
-    // Perform the optimization which should merge the two layers into a DepthToSpace
-    armnn::Optimizer::Pass(graph, MakeOptimizations(PermuteAndBatchToSpaceAsDepthToSpace()));
-
-    // Check that the replacement has been made as expected
-    auto checkDepthToSpace = [](const Layer* const layer) -> bool {
-        return IsLayerOfType<DepthToSpaceLayer>(layer) &&
-               static_cast<const DepthToSpaceLayer*>(layer)->GetParameters().m_BlockSize == 2 &&
-               static_cast<const DepthToSpaceLayer*>(layer)->GetParameters().m_DataLayout == DataLayout::NHWC &&
-               layer->GetOutputHandler().GetTensorInfo() == TensorInfo({ 1, 4, 6, 1 }, DataType::Float32);
-    };
-
-    BOOST_TEST(CheckSequence(graph.cbegin(), graph.cend(), &IsLayerOfType<InputLayer>, checkDepthToSpace,
-                             &IsLayerOfType<OutputLayer>));
-
-    // Check the new layer has the two merged layers listed as related layers
-    std::list<std::string> testRelatedLayers = { "batchToSpace", "permute" };
-    BOOST_TEST(CheckRelatedLayers<DepthToSpaceLayer>(graph, testRelatedLayers));
-}
-
-// This unit test needs the reference backend, it's not available if the reference backend is not built
-#if defined(ARMNNREF_ENABLED)
-
-/// Tests that a optimization performed by PermuteAndBatchToSpaceAsDepthToSpace does not change the behaviour
-/// of the network (i.e. it still produces the correct output).
-BOOST_AUTO_TEST_CASE(PermuteAndBatchToSpaceAsDepthToSpaceCorrectnessTest)
-{
-    INetworkPtr network = CreateTestNetwork();
-
-    IRuntimePtr runtime = IRuntime::Create(IRuntime::CreationOptions());
-    IOptimizedNetworkPtr optimizedNetwork = Optimize(*network, { Compute::CpuRef }, runtime->GetDeviceSpec());
-
-    // Confirm that the optimization has actually taken place
-    const Graph& optGraph = static_cast<OptimizedNetwork*>(optimizedNetwork.get())->GetGraph();
-    BOOST_TEST(CheckSequence(optGraph.cbegin(), optGraph.cend(), &IsLayerOfType<InputLayer>,
-                             &IsLayerOfType<DepthToSpaceLayer>, &IsLayerOfType<OutputLayer>));
-
-    // Load the graph into a runtime so we can check it produces the correct output
-    NetworkId netId;
-    runtime->LoadNetwork(netId, std::move(optimizedNetwork));
-
-    std::vector<float> inputData{
-        // Each row here is a row of pixels where each pixel has 4 channels
-        // clang-format off
-        1.0f,  2.0f,  3.0f,  4.0f,      10.0f,  20.0f,  30.0f,  40.0f,      100.0f,  200.0f,  300.0f,  400.0f,
-        -1.0f, -2.0f, -3.0f, -4.0f,    -10.0f, -20.0f, -30.0f, -40.0f,     -100.0f, -200.0f, -300.0f, -400.0f,
-        // clang-format on
-    };
-    ConstTensor input(TensorInfo({ 1, 2, 3, 4 }, DataType::Float32), inputData);
-    InputTensors inputs = { { 0, input } };
-    std::vector<float> outputData(4 * 6);
-    Tensor output(TensorInfo({ 1, 4, 6, 1 }, DataType::Float32), outputData.data());
-    OutputTensors outputs = { { 0, output } };
-    runtime->EnqueueWorkload(netId, inputs, outputs);
-
-    // Check the output is as expected.
-    // Note this output has been generated by running the network *without* the optimization.
-    std::vector<float> expectedOutput = {
-        // Rows and columns here match exactly with the tensor, as there is only 1 channel.
-        // clang-format off
-        1.0f,  2.0f,     10.0f,  20.0f,     100.0f,  200.0f,
-        3.0f,  4.0f,     30.0f,  40.0f,     300.0f,  400.0f,
-
-        -1.0f, -2.0f,   -10.0f, -20.0f,    -100.0f, -200.0f,
-        -3.0f, -4.0f,   -30.0f, -40.0f,    -300.0f, -400.0f,
-        // clang-format on
-    };
-    BOOST_TEST(outputData == expectedOutput);
-}
-#endif
-
-BOOST_AUTO_TEST_SUITE_END()
\ No newline at end of file