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, 89 deletions

diff --git a/delegate/src/test/DelegateOptionsTestHelper.hpp b/delegate/src/test/DelegateOptionsTestHelper.hpp
index 87bf0d6c3d..7e147de31f 100644
--- a/delegate/src/test/DelegateOptionsTestHelper.hpp
+++ b/delegate/src/test/DelegateOptionsTestHelper.hpp
@@ -219,95 +219,6 @@ std::vector<char> CreateCeilTfLiteModel(tflite::TensorType tensorType,
                              flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize());
 }
 
-void ReduceFp32ToBf16TestImpl()
-{
-    using namespace tflite;
-    // Set input data
-    std::vector<int32_t> inputShape{ 1, 5, 5, 1 };
-    std::vector<int32_t> filterShape{ 1, 3, 3, 1 };
-    std::vector<int32_t> biasShape{ 1 };
-    std::vector<int32_t> outputShape{ 1, 3, 3, 1 };
-
-    std::vector<float> inputValues =
-        {
-            1, 5, 2, 3, 5,
-            8, 7, 3, 6, 3,
-            3, 3, 9, 1, 9,
-            4, 1, 8, 1, 3,
-            6, 8, 1, 9, 2
-        };
-
-    std::vector<float> filterValues =
-        {
-            4, 5, 6,
-            0, 0, 0,
-            3, 2, 1
-        };
-
-    std::vector<float> biasValues = { 5 };
-
-    std::vector<float> expectedResult =
-        {
-            28, 38, 29,
-            96, 104, 53,
-            31, 55, 24
-        };
-
-    tflite::Padding padding = Padding_SAME;
-
-    std::vector<char> modelBuffer;
-    modelBuffer = CreateConv2dTfLiteModel<float>(BuiltinOperator_CONV_2D,
-                                                 ::tflite::TensorType_FLOAT32,
-                                                 2,
-                                                 2,
-                                                 1,
-                                                 1,
-                                                 padding,
-                                                 ActivationFunctionType_NONE,
-                                                 inputShape,
-                                                 filterShape,
-                                                 biasShape,
-                                                 outputShape,
-                                                 filterValues,
-                                                 biasValues);
-
-
-    const Model* tfLiteModel = GetModel(modelBuffer.data());
-    // Create TfLite Interpreters
-    std::unique_ptr<Interpreter> armnnDelegateInterpreter;
-    CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
-          (&armnnDelegateInterpreter) == kTfLiteOk);
-    CHECK(armnnDelegateInterpreter != nullptr);
-    CHECK(armnnDelegateInterpreter->AllocateTensors() == kTfLiteOk);
-
-    // Create the Armnn Delegate
-    std::vector<armnn::BackendId> backends = {armnn::Compute::CpuRef};
-    std::vector<armnn::BackendOptions> backendOptions;
-
-    // Enable debug with BF16 enabled
-    armnn::OptimizerOptions optimizerOptions(false, true, true, false);
-
-    armnnDelegate::DelegateOptions delegateOptions(backends, optimizerOptions);
-    std::unique_ptr<TfLiteDelegate, decltype(&armnnDelegate::TfLiteArmnnDelegateDelete)>
-        theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions),
-                         armnnDelegate::TfLiteArmnnDelegateDelete);
-    CHECK(theArmnnDelegate != nullptr);
-    // Modify armnnDelegateInterpreter to use armnnDelegate
-    CHECK(armnnDelegateInterpreter->ModifyGraphWithDelegate(theArmnnDelegate.get()) == kTfLiteOk);
-
-    // Set input data
-    armnnDelegate::FillInput(armnnDelegateInterpreter, 0, inputValues);
-
-    // Run EnqueueWorkload
-    CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk);
-
-    // Compare output data
-    auto armnnDelegateOutputId = armnnDelegateInterpreter->outputs()[0];
-    auto armnnDelegateOutputData = armnnDelegateInterpreter->typed_tensor<float>(armnnDelegateOutputId);
-    armnnDelegate::CompareData(expectedResult.data(), armnnDelegateOutputData, expectedResult.size());
-    armnnDelegateInterpreter.reset(nullptr);
-}
-
 template <typename T>
 void DelegateOptionTest(tflite::TensorType tensorType,
                         const std::vector<armnn::BackendId>& backends,