1 //
2 // Copyright © 2020 Arm Ltd. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5
6 #include "../TestUtils.hpp"
7
8 #include <BFloat16.hpp>
9 #include <Optimizer.hpp>
10
11 #include <boost/test/unit_test.hpp>
12
13 using namespace armnn;
14
15 BOOST_AUTO_TEST_SUITE(Optimizer)
16 using namespace armnn::optimizations;
17
BOOST_AUTO_TEST_CASE(ConvertConstantsFloatToBFloatTest)18 BOOST_AUTO_TEST_CASE(ConvertConstantsFloatToBFloatTest)
19 {
20 armnn::Graph graph;
21
22 const armnn::TensorInfo info({ 1, 1, 1, 2 }, armnn::DataType::BFloat16);
23
24 // Create const tensor from fp32 data
25 unsigned int dims[] = { 4, 2, 1, 1 };
26 std::vector<float> floatWeights{ 0.0f, -1.0f,
27 3.8f, // 0x40733333 Round down
28 3.1055E+29f, // 0x707ADC3C Round up
29 9.149516E-10f, // 0x307B7FFF Round down
30 -3.8f, // 0xC0733333 Round down
31 -3.1055E+29f, // 0xF07ADC3C Round up
32 -9.149516E-10f // 0xB07B7FFF Round down
33 };
34 armnn::ConstTensor weights(armnn::TensorInfo(4, dims, armnn::DataType::Float32), floatWeights);
35
36 // Create simple test network
37 auto input = graph.AddLayer<armnn::InputLayer>(0, "input");
38 input->GetOutputSlot().SetTensorInfo(info);
39
40 auto fc = graph.AddLayer<armnn::FullyConnectedLayer>(armnn::FullyConnectedDescriptor(), "fc");
41 fc->m_Weight = std::make_unique<armnn::ScopedCpuTensorHandle>(weights);
42 fc->GetOutputSlot().SetTensorInfo(info);
43
44 auto output = graph.AddLayer<armnn::OutputLayer>(1, "output");
45
46 // Connect up the layers
47 input->GetOutputSlot().Connect(fc->GetInputSlot(0));
48 fc->GetOutputSlot().Connect(output->GetInputSlot(0));
49
50 // Check tensor data type before conversion
51 BOOST_CHECK(fc->m_Weight->GetTensorInfo().GetDataType() == armnn::DataType::Float32);
52
53 // Run the optimizer
54 armnn::Optimizer::Pass(graph, armnn::MakeOptimizations(ConvertConstantsFloatToBFloat()));
55
56 // Check tensor data type after conversion
57 BOOST_CHECK(fc->m_Weight->GetTensorInfo().GetDataType() == armnn::DataType::BFloat16);
58
59 // Check whether data matches expected Bf16 data
60 BFloat16* data = fc->m_Weight->GetTensor<BFloat16>();
61 BOOST_CHECK(data[0] == BFloat16(0.0f));
62 BOOST_CHECK(data[1] == BFloat16(-1.0f));
63 BOOST_CHECK(data[2] == BFloat16(3.796875f)); // 0x4073
64 BOOST_CHECK(data[3] == BFloat16(3.1072295E29f)); // 0x707B
65 BOOST_CHECK(data[4] == BFloat16(9.131327E-10f)); // 0x307B
66 BOOST_CHECK(data[5] == BFloat16(-3.796875f)); // 0xC073
67 BOOST_CHECK(data[6] == BFloat16(-3.1072295E29f)); // 0xF07B
68 BOOST_CHECK(data[7] == BFloat16(-9.131327E-10f)); // 0xB07B
69 }
70
BOOST_AUTO_TEST_CASE(ConvertConstantsBFloatToFloatTest)71 BOOST_AUTO_TEST_CASE(ConvertConstantsBFloatToFloatTest)
72 {
73 armnn::Graph graph;
74
75 const armnn::TensorInfo info({ 1, 1, 1, 2 }, armnn::DataType::Float32);
76
77 // Create the BFloat16 precision input data
78 unsigned int dims[] = { 4, 2, 1, 1 };
79 std::vector<float> convWeightsData{ 0.f, -1.f,
80 3.796875f, // 0x4073
81 3.1072295E29f, // 0x707B
82 9.131327E-10f, // 0x307B
83 -3.796875f, // 0xC073
84 -3.1072295E29f, // 0xF07B
85 -9.131327E-10f // 0xB07B
86 };
87 std::vector<uint16_t> bfWeights(8);
88 armnnUtils::FloatingPointConverter::ConvertFloat32ToBFloat16(convWeightsData.data(), convWeightsData.size(),
89 bfWeights.data());
90 armnn::ConstTensor weights(armnn::TensorInfo(4, dims, armnn::DataType::BFloat16), bfWeights);
91
92 //Create the simple test network
93 auto input = graph.AddLayer<armnn::InputLayer>(0, "input");
94 input->GetOutputSlot().SetTensorInfo(info);
95
96 auto fc = graph.AddLayer<armnn::FullyConnectedLayer>(armnn::FullyConnectedDescriptor(), "fc");
97 fc->m_Weight = std::make_unique<armnn::ScopedCpuTensorHandle>(weights);
98 fc->GetOutputSlot().SetTensorInfo(info);
99
100 auto output = graph.AddLayer<armnn::OutputLayer>(1, "output");
101
102 //Connect up the layers
103 input->GetOutputSlot().Connect(fc->GetInputSlot(0));
104 fc->GetOutputSlot().Connect(output->GetInputSlot(0));
105
106 //Test the tensor info is correct.
107 BOOST_CHECK(fc->m_Weight->GetTensorInfo().GetDataType() == armnn::DataType::BFloat16);
108
109 // Run the optimizer
110 armnn::Optimizer::Pass(graph, armnn::MakeOptimizations(ConvertConstantsBFloatToFloat()));
111
112 //Test the tensor info is correct.
113 BOOST_CHECK(fc->m_Weight->GetTensorInfo().GetDataType() == armnn::DataType::Float32);
114
115 // Now test the data matches float32 data
116 float* data = fc->m_Weight->GetTensor<float>();
117 BOOST_CHECK(data[0] == 0.0f);
118 BOOST_CHECK(data[1] == -1.0f);
119 BOOST_CHECK(data[2] == 3.796875f);
120 BOOST_CHECK(data[3] == 3.1072295E29f);
121 BOOST_CHECK(data[4] == 9.131327E-10f);
122 BOOST_CHECK(data[5] == -3.796875f);
123 BOOST_CHECK(data[6] == -3.1072295E29f);
124 BOOST_CHECK(data[7] == -9.131327E-10f);
125 }
126
127 BOOST_AUTO_TEST_SUITE_END()