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, 128 deletions

diff --git a/src/armnn/test/optimizations/ConvertConstantsBFloatTests.cpp b/src/armnn/test/optimizations/ConvertConstantsBFloatTests.cpp
deleted file mode 100644
index 4aacf7f4fe..0000000000
--- a/src/armnn/test/optimizations/ConvertConstantsBFloatTests.cpp
+++ /dev/null
@@ -1,128 +0,0 @@
-//
-// Copyright © 2020 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-#include <TestUtils.hpp>
-
-#include <BFloat16.hpp>
-#include <Optimizer.hpp>
-
-#include <doctest/doctest.h>
-
-using namespace armnn;
-
-TEST_SUITE("Optimizer")
-{
-using namespace armnn::optimizations;
-
-TEST_CASE("ConvertConstantsFloatToBFloatTest")
-{
-    armnn::Graph graph;
-
-    const armnn::TensorInfo info({ 1, 1, 1, 2 }, armnn::DataType::BFloat16);
-
-    // Create const tensor from fp32 data
-    unsigned int dims[] = { 4, 2, 1, 1 };
-    std::vector<float> floatWeights{ 0.0f, -1.0f,
-                                     3.8f, // 0x40733333 Round down
-                                     3.1055E+29f, // 0x707ADC3C Round up
-                                     9.149516E-10f, // 0x307B7FFF Round down
-                                    -3.8f, // 0xC0733333 Round down
-                                    -3.1055E+29f, // 0xF07ADC3C Round up
-                                    -9.149516E-10f // 0xB07B7FFF Round down
-                                   };
-    armnn::ConstTensor weights(armnn::TensorInfo(4, dims, armnn::DataType::Float32, 0.0f, 0, true), floatWeights);
-
-    // Create simple test network
-    auto input = graph.AddLayer<armnn::InputLayer>(0, "input");
-    input->GetOutputSlot().SetTensorInfo(info);
-
-    auto fc      = graph.AddLayer<armnn::FullyConnectedLayer>(armnn::FullyConnectedDescriptor(), "fc");
-    fc->m_Weight = std::make_unique<armnn::ScopedTensorHandle>(weights);
-    fc->GetOutputSlot().SetTensorInfo(info);
-
-    auto output = graph.AddLayer<armnn::OutputLayer>(1, "output");
-
-    // Connect up the layers
-    input->GetOutputSlot().Connect(fc->GetInputSlot(0));
-    fc->GetOutputSlot().Connect(output->GetInputSlot(0));
-
-    // Check tensor data type before conversion
-    CHECK(fc->m_Weight->GetTensorInfo().GetDataType() == armnn::DataType::Float32);
-
-    // Run the optimizer
-    armnn::Optimizer::Pass(graph, armnn::MakeOptimizations(ConvertConstantsFloatToBFloat()));
-
-    // Check tensor data type after conversion
-    CHECK(fc->m_Weight->GetTensorInfo().GetDataType() == armnn::DataType::BFloat16);
-
-    // Check whether data matches expected Bf16 data
-    const BFloat16* data = fc->m_Weight->GetConstTensor<BFloat16>();
-    CHECK(data[0] == BFloat16(0.0f));
-    CHECK(data[1] == BFloat16(-1.0f));
-    CHECK(data[2] == BFloat16(3.796875f)); // 0x4073
-    CHECK(data[3] == BFloat16(3.1072295E29f)); // 0x707B
-    CHECK(data[4] == BFloat16(9.131327E-10f)); // 0x307B
-    CHECK(data[5] == BFloat16(-3.796875f)); // 0xC073
-    CHECK(data[6] == BFloat16(-3.1072295E29f)); // 0xF07B
-    CHECK(data[7] == BFloat16(-9.131327E-10f)); // 0xB07B
-}
-
-TEST_CASE("ConvertConstantsBFloatToFloatTest")
-{
-    armnn::Graph graph;
-
-    const armnn::TensorInfo info({ 1, 1, 1, 2 }, armnn::DataType::Float32);
-
-    // Create the BFloat16 precision input data
-    unsigned int dims[] = { 4, 2, 1, 1 };
-    std::vector<float> convWeightsData{ 0.f, -1.f,
-                                        3.796875f, // 0x4073
-                                        3.1072295E29f, // 0x707B
-                                        9.131327E-10f, // 0x307B
-                                       -3.796875f, // 0xC073
-                                       -3.1072295E29f, // 0xF07B
-                                       -9.131327E-10f // 0xB07B
-                                       };
-    std::vector<uint16_t> bfWeights(8);
-    armnnUtils::FloatingPointConverter::ConvertFloat32ToBFloat16(convWeightsData.data(), convWeightsData.size(),
-                                                                 bfWeights.data());
-    armnn::ConstTensor weights(armnn::TensorInfo(4, dims, armnn::DataType::BFloat16, 0.0f, 0, true), bfWeights);
-
-    //Create the simple test network
-    auto input = graph.AddLayer<armnn::InputLayer>(0, "input");
-    input->GetOutputSlot().SetTensorInfo(info);
-
-    auto fc      = graph.AddLayer<armnn::FullyConnectedLayer>(armnn::FullyConnectedDescriptor(), "fc");
-    fc->m_Weight = std::make_unique<armnn::ScopedTensorHandle>(weights);
-    fc->GetOutputSlot().SetTensorInfo(info);
-
-    auto output = graph.AddLayer<armnn::OutputLayer>(1, "output");
-
-    //Connect up the layers
-    input->GetOutputSlot().Connect(fc->GetInputSlot(0));
-    fc->GetOutputSlot().Connect(output->GetInputSlot(0));
-
-    //Test the tensor info is correct.
-    CHECK(fc->m_Weight->GetTensorInfo().GetDataType() == armnn::DataType::BFloat16);
-
-    // Run the optimizer
-    armnn::Optimizer::Pass(graph, armnn::MakeOptimizations(ConvertConstantsBFloatToFloat()));
-
-    //Test the tensor info is correct.
-    CHECK(fc->m_Weight->GetTensorInfo().GetDataType() == armnn::DataType::Float32);
-
-    // Now test the data matches float32 data
-    const float* data = fc->m_Weight->GetConstTensor<float>();
-    CHECK(data[0] == 0.0f);
-    CHECK(data[1] == -1.0f);
-    CHECK(data[2] == 3.796875f);
-    CHECK(data[3] == 3.1072295E29f);
-    CHECK(data[4] == 9.131327E-10f);
-    CHECK(data[5] == -3.796875f);
-    CHECK(data[6] == -3.1072295E29f);
-    CHECK(data[7] == -9.131327E-10f);
-}
-
-}
\ No newline at end of file