IVGCVSW-7214 Disable BF16-Turbo-Mode and remove conversion layers

 - Remove Bf16ToFp32 Conversion Layer
 - Remove Fp32ToBf16 Conversion Layer
 - Remove B16 Conversion tests
 * Throw exception if m_ReduceFp32ToBf16 optimzer option is set to true
 * Provide comments to enable fast math in order to use bf16
 * Update docs to inform users to enable fast math for bf16

 Execute Network Changes
 * Require bf16_turbo_mode to also have fast_math_enabled set to true
 - Remove setting m_ReduceFp32ToBf16 optimizer option

Signed-off-by: Ryan OShea <ryan.oshea3@arm.com>
Change-Id: Ibaa6da9d29c96a1ce32ff5196b0847fde9f04a1c

1 files changed, 0 insertions, 151 deletions

diff --git a/src/armnn/test/optimizations/FuseConvertF32BF16IntoConstLayerTests.cpp b/src/armnn/test/optimizations/FuseConvertF32BF16IntoConstLayerTests.cpp
deleted file mode 100644
index 93d5948d61..0000000000
--- a/src/armnn/test/optimizations/FuseConvertF32BF16IntoConstLayerTests.cpp
+++ /dev/null
@@ -1,151 +0,0 @@
-//
-// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-#include <LayersFwd.hpp>
-#include <Network.hpp>
-#include <NetworkUtils.hpp>
-#include <Optimizer.hpp>
-#include <TestUtils.hpp>
-
-#include <armnn/backends/TensorHandle.hpp>
-
-#include <doctest/doctest.h>
-
-TEST_SUITE("Optimizer")
-{
-using namespace armnn;
-using namespace armnn::optimizations;
-
-TEST_CASE("FuseConvertFp32Fp16intoConst")
-{
-    Graph graph;
-    const unsigned int shape[] = {1, 2, 2, 3};
-
-    const TensorInfo constTensorInfo(4, shape, DataType::Float32, 1.0, 0, true);
-    const TensorInfo outputConvertInfo(4, shape, DataType::BFloat16, 1.0, 0, true);
-
-    ConstantLayer* constantLayer = graph.AddLayer<ConstantLayer>("constant");
-    std::vector<float> constantValues(constTensorInfo.GetNumElements(), 3.1416f);
-    ConstTensor constTensor(constTensorInfo, constantValues.data());
-    constantLayer->m_LayerOutput = std::make_shared<ScopedTensorHandle>(constTensor);
-    constantLayer->GetOutputSlot().SetTensorInfo(constTensorInfo);
-
-    ConvertFp32ToBf16Layer* convertLayer = graph.AddLayer<ConvertFp32ToBf16Layer>("convert");
-    convertLayer->GetOutputSlot().SetTensorInfo(outputConvertInfo);
-
-    OutputLayer* output = graph.AddLayer<OutputLayer>(0, "output");
-
-    // Connect up constant -> convert -> output
-    constantLayer->GetOutputSlot().Connect(convertLayer->GetInputSlot(0));
-    convertLayer->GetOutputSlot().Connect(output->GetInputSlot(0));
-
-    auto checkConstantFloat32 = [](const armnn::Layer *const layer) -> bool {
-        return IsLayerOfType<ConstantLayer>(layer) &&
-               (layer->GetDataType() == DataType::Float32);
-    };
-    auto checkConstantBFloat16 = [](const armnn::Layer *const layer) -> bool {
-        return IsLayerOfType<ConstantLayer>(layer) &&
-               (layer->GetDataType() == DataType::BFloat16);
-    };
-
-    CHECK(CheckSequence(graph.cbegin(), graph.cend(),
-                        checkConstantFloat32,
-                        &IsLayerOfType<ConvertFp32ToBf16Layer>,
-                        &IsLayerOfType<OutputLayer>));
-
-    armnn::Optimizer::Pass(graph, MakeOptimizations(FuseConversionLayersIntoConstLayers()));
-
-    CHECK(CheckSequence(graph.cbegin(), graph.cend(),
-                        checkConstantBFloat16,
-                        &IsLayerOfType<OutputLayer>));
-}
-
-TEST_CASE("RevertConstantWeightsToFP32")
-{
-    Graph graph;
-    const unsigned int shape[] = {1, 2, 2, 3};
-
-    const TensorInfo constTensorInfo(4, shape, DataType::Float32, 1.0, 0, true);
-    const TensorInfo outputConvertInfo(4, shape, DataType::BFloat16, 1.0, 0, true);
-
-    TensorInfo inputInfo(4, shape, DataType::Float32);
-    auto* input = graph.AddLayer<InputLayer>(0, "input0");
-    input->GetOutputSlot().SetTensorInfo(inputInfo);
-
-    auto* constantLayer = graph.AddLayer<ConstantLayer>("constant");
-    std::vector<float> constantValues(constTensorInfo.GetNumElements(), 3.1416f);
-    ConstTensor constTensor(constTensorInfo, constantValues.data());
-    constantLayer->m_LayerOutput = std::make_shared<ScopedTensorHandle>(constTensor);
-    constantLayer->GetOutputSlot().SetTensorInfo(constTensorInfo);
-
-    ConvertFp32ToBf16Layer* convertLayerInputs = graph.AddLayer<ConvertFp32ToBf16Layer>("convert");
-    convertLayerInputs->GetOutputSlot().SetTensorInfo(outputConvertInfo);
-    ConvertFp32ToBf16Layer* convertLayerWeights = graph.AddLayer<ConvertFp32ToBf16Layer>("convert2");
-    convertLayerWeights->GetOutputSlot().SetTensorInfo(outputConvertInfo);
-    ConvertFp32ToBf16Layer* convertLayerBiases = graph.AddLayer<ConvertFp32ToBf16Layer>("convert3");
-    convertLayerBiases->GetOutputSlot().SetTensorInfo(outputConvertInfo);
-
-    auto* biases  = graph.AddLayer<armnn::ConstantLayer>("Biases");
-    biases->m_LayerOutput  = std::make_unique<armnn::ScopedTensorHandle>(constTensor);
-    biases->GetOutputSlot().SetTensorInfo(constTensorInfo);
-
-    armnn::Convolution2dDescriptor descriptor;
-    descriptor.m_BiasEnabled = true;
-    auto* conv = graph.AddLayer<armnn::Convolution2dLayer>(descriptor, "conv2d");
-    const armnn::TensorInfo infoFP32({ 2, 3, 8, 1 }, armnn::DataType::Float32);
-    conv->GetOutputSlot().SetTensorInfo(infoFP32);
-
-    auto* output = graph.AddLayer<OutputLayer>(0, "output");
-
-    // Connect up Input    -> Convert ->
-    //            Constant -> Convert -> Conv2d -> Output
-    //            Constant -> Convert ->
-    input->GetOutputSlot().Connect(convertLayerInputs->GetInputSlot(0));
-    constantLayer->GetOutputSlot().Connect(convertLayerWeights->GetInputSlot(0));
-    biases->GetOutputSlot().Connect(convertLayerBiases->GetInputSlot(0));
-
-    convertLayerInputs->GetOutputSlot().Connect(conv->GetInputSlot(0));
-    convertLayerWeights->GetOutputSlot().Connect(conv->GetInputSlot(1));
-    convertLayerBiases->GetOutputSlot().Connect(conv->GetInputSlot(2));
-
-    conv->GetOutputSlot().Connect(output->GetInputSlot(0));
-
-    auto checkConstantFloat32 = [](const armnn::Layer *const layer) -> bool {
-        return IsLayerOfType<ConstantLayer>(layer) &&
-               (layer->GetDataType() == DataType::Float32);
-    };
-    auto checkConstantBFloat16 = [](const armnn::Layer *const layer) -> bool {
-        return IsLayerOfType<ConstantLayer>(layer) &&
-               (layer->GetDataType() == DataType::BFloat16);
-    };
-
-    CHECK(CheckSequence(graph.cbegin(), graph.cend(),
-                        &IsLayerOfType<InputLayer>,
-                        checkConstantFloat32,
-                        checkConstantFloat32,
-                        &IsLayerOfType<ConvertFp32ToBf16Layer>,
-                        &IsLayerOfType<ConvertFp32ToBf16Layer>,
-                        &IsLayerOfType<ConvertFp32ToBf16Layer>,
-                        &IsLayerOfType<Convolution2dLayer>,
-                        &IsLayerOfType<OutputLayer>));
-
-    armnn::Optimizer::Pass(graph, MakeOptimizations(FuseConversionLayersIntoConstLayers()));
-
-    bool revert = RevertConstantWeightsToFP32(conv);
-
-    // Erase unconnected layer as occurs during Topological Sort.
-    graph.EraseLayer(convertLayerInputs);
-
-    CHECK(revert);
-    CHECK(constantLayer->GetDataType() == DataType::Float32);
-
-    CHECK(CheckSequence(graph.cbegin(), graph.cend(),
-                        &IsLayerOfType<InputLayer>,
-                        checkConstantBFloat16,
-                        checkConstantFloat32,
-                        &IsLayerOfType<Convolution2dLayer>,
-                        &IsLayerOfType<OutputLayer>));
-}
-}