aboutsummaryrefslogtreecommitdiff
path: root/src/armnn/test
diff options
context:
space:
mode:
Diffstat (limited to 'src/armnn/test')
-rw-r--r--src/armnn/test/optimizations/ConvertConstantsBFloatTests.cpp127
-rw-r--r--src/armnn/test/optimizations/Fp32NetworkToBf16ConverterTests.cpp45
2 files changed, 172 insertions, 0 deletions
diff --git a/src/armnn/test/optimizations/ConvertConstantsBFloatTests.cpp b/src/armnn/test/optimizations/ConvertConstantsBFloatTests.cpp
new file mode 100644
index 0000000000..5cb89daafd
--- /dev/null
+++ b/src/armnn/test/optimizations/ConvertConstantsBFloatTests.cpp
@@ -0,0 +1,127 @@
+//
+// 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() \ No newline at end of file
diff --git a/src/armnn/test/optimizations/Fp32NetworkToBf16ConverterTests.cpp b/src/armnn/test/optimizations/Fp32NetworkToBf16ConverterTests.cpp
new file mode 100644
index 0000000000..90a15487ac
--- /dev/null
+++ b/src/armnn/test/optimizations/Fp32NetworkToBf16ConverterTests.cpp
@@ -0,0 +1,45 @@
+//
+// Copyright © 2020 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "../TestUtils.hpp"
+
+#include <Optimizer.hpp>
+
+#include <boost/test/unit_test.hpp>
+
+BOOST_AUTO_TEST_SUITE(Optimizer)
+using namespace armnn::optimizations;
+
+BOOST_AUTO_TEST_CASE(Fp32NetworkToBf16OptimizationTest)
+{
+ armnn::Graph graph;
+
+ const armnn::TensorInfo infoFP32({ 2, 2, 1, 3 }, armnn::DataType::Float32);
+
+ // Create the simple test network
+ auto input = graph.AddLayer<armnn::InputLayer>(0, "input");
+ input->GetOutputSlot().SetTensorInfo(infoFP32);
+
+ auto floor = graph.AddLayer<armnn::FloorLayer>("floor");
+ floor->GetOutputSlot().SetTensorInfo(infoFP32);
+
+ auto output = graph.AddLayer<armnn::OutputLayer>(1, "output");
+
+ // Connect up the layers
+ input->GetOutputSlot().Connect(floor->GetInputSlot(0));
+ floor->GetOutputSlot().Connect(output->GetInputSlot(0));
+
+ BOOST_TEST(CheckSequence(graph.cbegin(), graph.cend(), &IsLayerOfType<armnn::InputLayer>,
+ &IsLayerOfType<armnn::FloorLayer>, &IsLayerOfType<armnn::OutputLayer>));
+
+ // Run the optimizer
+ armnn::Optimizer::Pass(graph, armnn::MakeOptimizations(Fp32NetworkToBf16Converter()));
+
+ BOOST_TEST(CheckSequence(graph.cbegin(), graph.cend(), &IsLayerOfType<armnn::InputLayer>,
+ &IsLayerOfType<armnn::ConvertFp32ToBf16Layer>, &IsLayerOfType<armnn::FloorLayer>,
+ &IsLayerOfType<armnn::ConvertBf16ToFp32Layer>, &IsLayerOfType<armnn::OutputLayer>));
+}
+
+BOOST_AUTO_TEST_SUITE_END() \ No newline at end of file
generated by cgit v1.2.1 (git 2.23.0) at 2024-07-02 19:38:49 +0000