| // |
| // Copyright © 2020 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "../TestUtils.hpp" |
| |
| #include <BFloat16.hpp> |
| #include <Optimizer.hpp> |
| |
| #include <boost/test/unit_test.hpp> |
| |
| using namespace armnn; |
| |
| BOOST_AUTO_TEST_SUITE(Optimizer) |
| using namespace armnn::optimizations; |
| |
| BOOST_AUTO_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), 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::ScopedCpuTensorHandle>(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 |
| BOOST_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 |
| BOOST_CHECK(fc->m_Weight->GetTensorInfo().GetDataType() == armnn::DataType::BFloat16); |
| |
| // Check whether data matches expected Bf16 data |
| BFloat16* data = fc->m_Weight->GetTensor<BFloat16>(); |
| BOOST_CHECK(data[0] == BFloat16(0.0f)); |
| BOOST_CHECK(data[1] == BFloat16(-1.0f)); |
| BOOST_CHECK(data[2] == BFloat16(3.796875f)); // 0x4073 |
| BOOST_CHECK(data[3] == BFloat16(3.1072295E29f)); // 0x707B |
| BOOST_CHECK(data[4] == BFloat16(9.131327E-10f)); // 0x307B |
| BOOST_CHECK(data[5] == BFloat16(-3.796875f)); // 0xC073 |
| BOOST_CHECK(data[6] == BFloat16(-3.1072295E29f)); // 0xF07B |
| BOOST_CHECK(data[7] == BFloat16(-9.131327E-10f)); // 0xB07B |
| } |
| |
| BOOST_AUTO_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), 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::ScopedCpuTensorHandle>(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. |
| BOOST_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. |
| BOOST_CHECK(fc->m_Weight->GetTensorInfo().GetDataType() == armnn::DataType::Float32); |
| |
| // Now test the data matches float32 data |
| float* data = fc->m_Weight->GetTensor<float>(); |
| BOOST_CHECK(data[0] == 0.0f); |
| BOOST_CHECK(data[1] == -1.0f); |
| BOOST_CHECK(data[2] == 3.796875f); |
| BOOST_CHECK(data[3] == 3.1072295E29f); |
| BOOST_CHECK(data[4] == 9.131327E-10f); |
| BOOST_CHECK(data[5] == -3.796875f); |
| BOOST_CHECK(data[6] == -3.1072295E29f); |
| BOOST_CHECK(data[7] == -9.131327E-10f); |
| } |
| |
| BOOST_AUTO_TEST_SUITE_END() |