1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
|
//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include <armnn/ArmNN.hpp>
#include <armnn/INetwork.hpp>
#include "../Serializer.hpp"
#include <armnnDeserializeParser/IDeserializeParser.hpp>
#include <numeric>
#include <sstream>
#include <vector>
#include <boost/test/unit_test.hpp>
#include <flatbuffers/idl.h>
using armnnDeserializeParser::IDeserializeParser;
namespace
{
armnn::INetworkPtr DeserializeNetwork(const std::string& serializerString)
{
std::vector<std::uint8_t> const serializerVector{serializerString.begin(), serializerString.end()};
return armnnDeserializeParser::IDeserializeParser::Create()->CreateNetworkFromBinary(serializerVector);
}
std::string SerializeNetwork(const armnn::INetwork& network)
{
armnnSerializer::Serializer serializer;
serializer.Serialize(network);
std::stringstream stream;
serializer.SaveSerializedToStream(stream);
std::string serializerString{stream.str()};
return serializerString;
}
} // anonymous namespace
BOOST_AUTO_TEST_SUITE(SerializerTests)
BOOST_AUTO_TEST_CASE(SimpleNetworkSerialization)
{
armnn::INetworkPtr network = armnn::INetwork::Create();
armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0);
armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1);
armnn::IConnectableLayer* const additionLayer0 = network->AddAdditionLayer();
inputLayer0->GetOutputSlot(0).Connect(additionLayer0->GetInputSlot(0));
inputLayer1->GetOutputSlot(0).Connect(additionLayer0->GetInputSlot(1));
armnn::IConnectableLayer* const outputLayer0 = network->AddOutputLayer(0);
additionLayer0->GetOutputSlot(0).Connect(outputLayer0->GetInputSlot(0));
armnnSerializer::Serializer serializer;
serializer.Serialize(*network);
std::stringstream stream;
serializer.SaveSerializedToStream(stream);
BOOST_TEST(stream.str().length() > 0);
}
BOOST_AUTO_TEST_CASE(SimpleNetworkWithMultiplicationSerialization)
{
const armnn::TensorInfo info({ 1, 5, 2, 3 }, armnn::DataType::Float32);
armnn::INetworkPtr network = armnn::INetwork::Create();
armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0);
armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1);
const char* multLayerName = "mult_0";
armnn::IConnectableLayer* const multiplicationLayer0 = network->AddMultiplicationLayer(multLayerName);
inputLayer0->GetOutputSlot(0).Connect(multiplicationLayer0->GetInputSlot(0));
inputLayer1->GetOutputSlot(0).Connect(multiplicationLayer0->GetInputSlot(1));
armnn::IConnectableLayer* const outputLayer0 = network->AddOutputLayer(0);
multiplicationLayer0->GetOutputSlot(0).Connect(outputLayer0->GetInputSlot(0));
armnnSerializer::Serializer serializer;
serializer.Serialize(*network);
std::stringstream stream;
serializer.SaveSerializedToStream(stream);
BOOST_TEST(stream.str().length() > 0);
BOOST_TEST(stream.str().find(multLayerName) != stream.str().npos);
}
BOOST_AUTO_TEST_CASE(SimpleSoftmaxIntegration)
{
armnn::TensorInfo tensorInfo({1, 10}, armnn::DataType::Float32);
armnn::SoftmaxDescriptor descriptor;
descriptor.m_Beta = 1.0f;
// Create test network
armnn::INetworkPtr network = armnn::INetwork::Create();
armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
armnn::IConnectableLayer* const softmaxLayer = network->AddSoftmaxLayer(descriptor, "softmax");
armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
inputLayer->GetOutputSlot(0).Connect(softmaxLayer->GetInputSlot(0));
inputLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo);
softmaxLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
softmaxLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo);
// Serialize & deserialize network
armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
BOOST_CHECK(deserializedNetwork);
armnn::IRuntime::CreationOptions options;
armnn::IRuntimePtr runtime = armnn::IRuntime::Create(options);
armnn::IOptimizedNetworkPtr optimizedNetwork =
armnn::Optimize(*network, {armnn::Compute::CpuRef}, runtime->GetDeviceSpec());
BOOST_CHECK(optimizedNetwork);
armnn::IOptimizedNetworkPtr deserializedOptimizedNetwork =
armnn::Optimize(*deserializedNetwork, {armnn::Compute::CpuRef}, runtime->GetDeviceSpec());
BOOST_CHECK(deserializedOptimizedNetwork);
armnn::NetworkId networkId1;
armnn::NetworkId networkId2;
runtime->LoadNetwork(networkId1, std::move(optimizedNetwork));
runtime->LoadNetwork(networkId2, std::move(deserializedOptimizedNetwork));
std::vector<float> inputData(tensorInfo.GetNumElements());
std::iota(inputData.begin(), inputData.end(), 0);
armnn::InputTensors inputTensors1
{
{0, armnn::ConstTensor(runtime->GetInputTensorInfo(networkId1, 0), inputData.data())}
};
armnn::InputTensors inputTensors2
{
{0, armnn::ConstTensor(runtime->GetInputTensorInfo(networkId2, 0), inputData.data())}
};
std::vector<float> outputData1(inputData.size());
std::vector<float> outputData2(inputData.size());
armnn::OutputTensors outputTensors1
{
{0, armnn::Tensor(runtime->GetOutputTensorInfo(networkId1, 0), outputData1.data())}
};
armnn::OutputTensors outputTensors2
{
{0, armnn::Tensor(runtime->GetOutputTensorInfo(networkId2, 0), outputData2.data())}
};
runtime->EnqueueWorkload(networkId1, inputTensors1, outputTensors1);
runtime->EnqueueWorkload(networkId2, inputTensors2, outputTensors2);
BOOST_CHECK_EQUAL_COLLECTIONS(outputData1.begin(), outputData1.end(),
outputData2.begin(), outputData2.end());
}
BOOST_AUTO_TEST_CASE(SimplePooling2dIntegration)
{
armnn::NetworkId networkIdentifier;
armnn::IRuntime::CreationOptions options; // default options
armnn::IRuntimePtr runtime = armnn::IRuntime::Create(options);
unsigned int inputShape[] = {1, 2, 2, 1};
unsigned int outputShape[] = {1, 1, 1, 1};
auto inputTensorInfo = armnn::TensorInfo(4, inputShape, armnn::DataType::Float32);
auto outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::DataType::Float32);
armnn::Pooling2dDescriptor desc;
desc.m_DataLayout = armnn::DataLayout::NHWC;
desc.m_PadTop = 0;
desc.m_PadBottom = 0;
desc.m_PadLeft = 0;
desc.m_PadRight = 0;
desc.m_PoolType = armnn::PoolingAlgorithm::Average;
desc.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor;
desc.m_PaddingMethod = armnn::PaddingMethod::Exclude;
desc.m_PoolHeight = 2;
desc.m_PoolWidth = 2;
desc.m_StrideX = 2;
desc.m_StrideY = 2;
armnn::INetworkPtr network = armnn::INetwork::Create();
armnn::IConnectableLayer *const inputLayer = network->AddInputLayer(0);
armnn::IConnectableLayer *const pooling2dLayer = network->AddPooling2dLayer(desc, "ReshapeLayer");
armnn::IConnectableLayer *const outputLayer = network->AddOutputLayer(0);
inputLayer->GetOutputSlot(0).Connect(pooling2dLayer->GetInputSlot(0));
inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
pooling2dLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
pooling2dLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
auto deserializeNetwork = DeserializeNetwork(SerializeNetwork(*network));
//Optimize the deserialized network
auto deserializedOptimized = Optimize(*deserializeNetwork, {armnn::Compute::CpuRef},
runtime->GetDeviceSpec());
// Load graph into runtime
runtime->LoadNetwork(networkIdentifier, std::move(deserializedOptimized));
std::vector<float> input1Data(inputTensorInfo.GetNumElements());
std::iota(input1Data.begin(), input1Data.end(), 4);
armnn::InputTensors inputTensors
{
{0, armnn::ConstTensor(runtime->GetInputTensorInfo(networkIdentifier, 0), input1Data.data())}
};
std::vector<float> outputData(input1Data.size());
armnn::OutputTensors outputTensors
{
{0, armnn::Tensor(runtime->GetOutputTensorInfo(networkIdentifier, 0), outputData.data())}
};
runtime->EnqueueWorkload(networkIdentifier, inputTensors, outputTensors);
BOOST_CHECK_EQUAL(outputData[0], 5.5);
}
BOOST_AUTO_TEST_SUITE_END()
|
