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, 179 deletions

diff --git a/src/armnn/NetworkUtils.cpp b/src/armnn/NetworkUtils.cpp
index aaee4eba1a..1d46f029dc 100644
--- a/src/armnn/NetworkUtils.cpp
+++ b/src/armnn/NetworkUtils.cpp
@@ -5,8 +5,6 @@
 
 #include "NetworkUtils.hpp"
 
-#include <armnnUtils/FloatingPointConverter.hpp>
-#include <BFloat16.hpp>
 #include "SubgraphViewSelector.hpp"
 
 #include <armnn/Exceptions.hpp>
@@ -26,17 +24,6 @@ void UpdateOutputSlotToFp32(OutputSlot& outputSlot)
     outputSlot.SetTensorInfo(newTensorInfo);
 }
 
-void ChangeOutputBf16ToFp32(Layer& layer)
-{
-    for (auto&& outputSlot = layer.BeginOutputSlots(); outputSlot != layer.EndOutputSlots(); ++outputSlot)
-    {
-        if (outputSlot->GetTensorInfo().GetDataType() == DataType::BFloat16)
-        {
-            UpdateOutputSlotToFp32(*outputSlot);
-        }
-    }
-}
-
 void ChangeOutputFp16ToFp32(Layer& layer)
 {
     for (auto&& outputSlot = layer.BeginOutputSlots(); outputSlot != layer.EndOutputSlots(); ++outputSlot)
@@ -50,93 +37,6 @@ void ChangeOutputFp16ToFp32(Layer& layer)
 
 } // anonymous namespace
 
-std::vector<ConvertBf16ToFp32Layer*> InsertConvertBf16ToFp32LayersBefore(Graph& graph,
-                                                                         Layer& layer,
-                                                                         bool expectCorrectInputType)
-{
-    std::vector<ConvertBf16ToFp32Layer*> convertLayers;
-    convertLayers.reserve(layer.GetNumInputSlots());
-
-    // Insert a ConvertBf16ToFp32Layer before each input slot
-    for (auto&& inputSlot = layer.BeginInputSlots(); inputSlot != layer.EndInputSlots(); ++inputSlot)
-    {
-        bool allowInsert = true;
-        if (expectCorrectInputType)
-        {
-            // Only insert ConvertBf16ToFp32Layer before BF16 input slots
-            OutputSlot* connectedOutputSlot = inputSlot->GetConnectedOutputSlot();
-            allowInsert =
-                connectedOutputSlot && connectedOutputSlot->GetTensorInfo().GetDataType() == DataType::BFloat16;
-        }
-
-        if (allowInsert)
-        {
-            const std::string name =
-                std::string("convert_bf16_to_fp32-" + std::to_string(inputSlot->GetSlotIndex()) + "-") +
-                layer.GetName();
-            ConvertBf16ToFp32Layer* convertLayer =
-                graph.InsertNewLayer<ConvertBf16ToFp32Layer>(*inputSlot, name.c_str());
-
-            TensorInfo convertInfo = convertLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo();
-            convertInfo.SetDataType(DataType::Float32);
-
-            convertLayer->GetOutputSlot().SetTensorInfo(convertInfo);
-
-            convertLayers.emplace_back(convertLayer);
-        }
-    }
-
-    return convertLayers;
-}
-
-std::vector<ConvertFp32ToBf16Layer*> InsertConvertFp32ToBf16LayersBefore(Graph& graph,
-                                                                         Layer& layer,
-                                                                         bool expectCorrectInputType)
-{
-    std::vector<ConvertFp32ToBf16Layer*> convertLayers;
-    convertLayers.reserve(layer.GetNumInputSlots());
-
-    // Insert a ConvertFp32ToBf16Layer before each input slot
-    for (auto&& inputSlot = layer.BeginInputSlots(); inputSlot != layer.EndInputSlots(); ++inputSlot)
-    {
-        bool allowInsert = true;
-
-        if ((layer.GetType() == LayerType::Convolution2d ||
-             layer.GetType() == LayerType::FullyConnected ||
-             layer.GetType() == LayerType::DepthwiseConvolution2d)
-                && inputSlot->GetSlotIndex() == 2)
-        {
-            // Refrain from reducing bias to Bf16
-            continue;
-        }
-        if (expectCorrectInputType)
-        {
-            // Only insert ConvertFp32ToBf16Layer before FP32 input slots
-            OutputSlot* connectedOutputSlot = inputSlot->GetConnectedOutputSlot();
-            allowInsert =
-                connectedOutputSlot && connectedOutputSlot->GetTensorInfo().GetDataType() == DataType::Float32;
-        }
-
-        if (allowInsert)
-        {
-            const std::string name =
-                std::string("convert_fp32_to_bf16-" + std::to_string(inputSlot->GetSlotIndex()) + "-") +
-                layer.GetName();
-            ConvertFp32ToBf16Layer* convertLayer =
-                graph.InsertNewLayer<ConvertFp32ToBf16Layer>(*inputSlot, name.c_str());
-
-            TensorInfo convertInfo = convertLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo();
-            convertInfo.SetDataType(DataType::BFloat16);
-
-            convertLayer->GetOutputSlot().SetTensorInfo(convertInfo);
-
-            convertLayers.emplace_back(convertLayer);
-        }
-    }
-
-    return convertLayers;
-}
-
 std::vector<ConvertFp16ToFp32Layer*> InsertConvertFp16ToFp32LayersBefore(Graph& graph,
                                                                          Layer& layer,
                                                                          bool expectCorrectInputType)
@@ -176,39 +76,6 @@ std::vector<ConvertFp16ToFp32Layer*> InsertConvertFp16ToFp32LayersBefore(Graph&
     return convertLayers;
 }
 
-std::vector<ConvertFp32ToBf16Layer*> InsertConvertFp32ToBf16LayersAfter(Graph& graph, Layer& layer)
-{
-    const unsigned int numOutputSlots = layer.GetNumOutputSlots();
-
-    std::vector<ConvertFp32ToBf16Layer*> convertLayers;
-    convertLayers.reserve(numOutputSlots);
-
-    // Update Bf16 output slots to FP32 on current layer
-    ChangeOutputBf16ToFp32(layer);
-
-    // Insert a ConvertFp32ToBf16Layer after each FP32 output slot
-    for (unsigned int slotIndex = 0u; slotIndex < numOutputSlots; ++slotIndex)
-    {
-        OutputSlot& outputSlot = layer.GetOutputSlot(slotIndex);
-        if(outputSlot.GetTensorInfo().GetDataType() == DataType::Float32)
-        {
-            const std::string name =
-                std::string("convert_fp32_to_bf16-" + std::to_string(slotIndex) + "-") + layer.GetName();
-            ConvertFp32ToBf16Layer* convertLayer =
-                graph.InsertNewLayer<ConvertFp32ToBf16Layer>(outputSlot, name.c_str());
-
-            TensorInfo convertInfo = convertLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo();
-            convertInfo.SetDataType(DataType::BFloat16);
-
-            convertLayer->GetOutputSlot().SetTensorInfo(convertInfo);
-
-            convertLayers.emplace_back(convertLayer);
-        }
-    }
-
-    return convertLayers;
-}
-
 std::vector<ConvertFp32ToFp16Layer*> InsertConvertFp32ToFp16LayersAfter(Graph& graph, Layer& layer)
 {
     const unsigned int numOutputSlots = layer.GetNumOutputSlots();
@@ -274,50 +141,4 @@ std::vector<DebugLayer*> InsertDebugLayerAfter(Graph& graph, Layer& layer, bool
     return debugLayers;
 }
 
-bool RevertConstantWeightsToFP32(Layer* layer)
-{
-    if (layer->GetType() == LayerType::Convolution2d || layer->GetType() == LayerType::FullyConnected)
-    {
-        // Revert Weights on Constant Layer to FP32 so they can be accessed by Conv2d or FullyConnected
-        // This prevents a conversion layer being added in during backend assignment which blocks
-        // the RedirectMembersToConstantInputs backward compatibility workaround/optimization.
-        auto constantLayerInfo = layer->GetInputSlot(1).GetConnection()->GetTensorInfo();
-
-        if (constantLayerInfo.IsConstant() && constantLayerInfo.GetDataType() == DataType::BFloat16)
-        {
-            std::vector<float> newValues(constantLayerInfo.GetNumElements());
-
-            auto weightLayer = PolymorphicDowncast<ConstantLayer*>(
-                    &layer->GetInputSlot(1).GetConnection()->GetOwningIConnectableLayer());
-            armnnUtils::FloatingPointConverter::ConvertBFloat16ToFloat32(
-                    weightLayer->m_LayerOutput->GetConstTensor<BFloat16>(),
-                    constantLayerInfo.GetNumElements(),
-                    newValues.data());
-
-            TensorInfo newInfo(constantLayerInfo.GetShape(), DataType::Float32);
-            newInfo.SetConstant(true);
-            ConstTensor newInput(newInfo, newValues);
-            weightLayer->m_LayerOutput.reset(new ScopedTensorHandle(newInput));
-            weightLayer->GetOutputSlot(0).SetTensorInfo(newInfo);
-
-            // Connect Conv2d/FullyConnected to InputLayer directly leaving out
-            // the ConversionLayer to be cleaned up later
-            auto& conversionLayer = layer->GetInputSlot(0).GetConnection()->GetOwningIConnectableLayer();
-            auto actualInputOutputSlot = conversionLayer.GetInputSlot(0).GetConnection();
-
-            auto& conversionLayerOutputSlot =
-                    layer->GetInputSlot(0).GetConnection()->GetOwningIConnectableLayer().GetOutputSlot(0);
-            auto& conversionLayerInputSlot =
-                    layer->GetInputSlot(0).GetConnection()->GetOwningIConnectableLayer().GetInputSlot(0);
-            actualInputOutputSlot->Disconnect(conversionLayerInputSlot);
-            conversionLayerOutputSlot.Disconnect(layer->GetInputSlot(0));
-
-            actualInputOutputSlot->Connect(layer->GetInputSlot(0));
-
-            return true;
-        }
-    }
-    return false;
-}
-
 } // namespace armnn