1 //
2 // Copyright © 2017, 2023 Arm Ltd. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5
6 #include "JsonPrinterTestImpl.hpp"
7 #include "armnn/utility/StringUtils.hpp"
8
9 #include <Profiling.hpp>
10
11 #include <armnn/Descriptors.hpp>
12 #include <armnn/IRuntime.hpp>
13 #include <armnn/INetwork.hpp>
14
15 #include <doctest/doctest.h>
16
17 #include <sstream>
18 #include <stack>
19 #include <string>
20 #include <algorithm>
21
AreMatchingPair(const char opening,const char closing)22 inline bool AreMatchingPair(const char opening, const char closing)
23 {
24 return (opening == '{' && closing == '}') || (opening == '[' && closing == ']');
25 }
26
AreParenthesesMatching(const std::string & exp)27 bool AreParenthesesMatching(const std::string& exp)
28 {
29 std::stack<char> expStack;
30 for (size_t i = 0; i < exp.length(); ++i)
31 {
32 if (exp[i] == '{' || exp[i] == '[')
33 {
34 expStack.push(exp[i]);
35 }
36 else if (exp[i] == '}' || exp[i] == ']')
37 {
38 if (expStack.empty() || !AreMatchingPair(expStack.top(), exp[i]))
39 {
40 return false;
41 }
42 else
43 {
44 expStack.pop();
45 }
46 }
47 }
48 return expStack.empty();
49 }
50
ExtractMeasurements(const std::string & exp)51 std::vector<double> ExtractMeasurements(const std::string& exp)
52 {
53 std::vector<double> numbers;
54 bool inArray = false;
55 std::string numberString;
56 for (size_t i = 0; i < exp.size(); ++i)
57 {
58 if (exp[i] == '[')
59 {
60 inArray = true;
61 }
62 else if (exp[i] == ']' && inArray)
63 {
64 try
65 {
66 armnn::stringUtils::StringTrim(numberString, "\t,\n");
67 numbers.push_back(std::stod(numberString));
68 }
69 catch (std::invalid_argument const&)
70 {
71 FAIL(("Could not convert measurements to double: " + numberString));
72 }
73
74 numberString.clear();
75 inArray = false;
76 }
77 else if (exp[i] == ',' && inArray)
78 {
79 try
80 {
81 armnn::stringUtils::StringTrim(numberString, "\t,\n");
82 numbers.push_back(std::stod(numberString));
83 }
84 catch (std::invalid_argument const&)
85 {
86 FAIL(("Could not convert measurements to double: " + numberString));
87 }
88 numberString.clear();
89 }
90 else if (exp[i] != '[' && inArray && exp[i] != ',' && exp[i] != ' ')
91 {
92 numberString += exp[i];
93 }
94 }
95 return numbers;
96 }
97
ExtractSections(const std::string & exp)98 std::vector<std::string> ExtractSections(const std::string& exp)
99 {
100 std::vector<std::string> sections;
101
102 std::stack<size_t> s;
103 for (size_t i = 0; i < exp.size(); i++)
104 {
105 if (exp.at(i) == '{')
106 {
107 s.push(i);
108 }
109 else if (exp.at(i) == '}')
110 {
111 size_t from = s.top();
112 s.pop();
113 sections.push_back(exp.substr(from, i - from + 1));
114 }
115 }
116
117 return sections;
118 }
119
GetSoftmaxProfilerJson(const std::vector<armnn::BackendId> & backends)120 std::string GetSoftmaxProfilerJson(const std::vector<armnn::BackendId>& backends)
121 {
122 using namespace armnn;
123
124 CHECK(!backends.empty());
125
126 ProfilerManager& profilerManager = armnn::ProfilerManager::GetInstance();
127
128 // Create runtime in which test will run
129 IRuntime::CreationOptions options;
130 options.m_EnableGpuProfiling = backends.front() == armnn::Compute::GpuAcc;
131 IRuntimePtr runtime(IRuntime::Create(options));
132
133 // build up the structure of the network
134 INetworkPtr net(INetwork::Create());
135 IConnectableLayer* input = net->AddInputLayer(0, "input");
136 SoftmaxDescriptor softmaxDescriptor;
137 // Set Axis to -1 if CL or Neon until further Axes are supported.
138 if ( backends.front() == armnn::Compute::CpuAcc || backends.front() == armnn::Compute::GpuAcc)
139 {
140 softmaxDescriptor.m_Axis = -1;
141 }
142 IConnectableLayer* softmax = net->AddSoftmaxLayer(softmaxDescriptor, "softmax");
143 IConnectableLayer* output = net->AddOutputLayer(0, "output");
144
145 input->GetOutputSlot(0).Connect(softmax->GetInputSlot(0));
146 softmax->GetOutputSlot(0).Connect(output->GetInputSlot(0));
147
148 // set the tensors in the network
149 TensorInfo inputTensorInfo(TensorShape({1, 5}), DataType::QAsymmU8);
150 inputTensorInfo.SetQuantizationOffset(100);
151 inputTensorInfo.SetQuantizationScale(10000.0f);
152 input->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
153
154 TensorInfo outputTensorInfo(TensorShape({1, 5}), DataType::QAsymmU8);
155 outputTensorInfo.SetQuantizationOffset(0);
156 outputTensorInfo.SetQuantizationScale(1.0f / 256.0f);
157 softmax->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
158
159 // optimize the network
160 armnn::OptimizerOptionsOpaque optOptions;
161 optOptions.SetProfilingEnabled(true);
162 IOptimizedNetworkPtr optNet = Optimize(*net, backends, runtime->GetDeviceSpec(), optOptions);
163 if(!optNet)
164 {
165 FAIL("Error occurred during Optimization, Optimize() returned nullptr.");
166 }
167 // load it into the runtime
168 NetworkId netId;
169 auto error = runtime->LoadNetwork(netId, std::move(optNet));
170 CHECK(error == Status::Success);
171
172 // create structures for input & output
173 std::vector<uint8_t> inputData
174 {
175 1, 10, 3, 200, 5
176 // one of inputs is sufficiently larger than the others to saturate softmax
177 };
178 std::vector<uint8_t> outputData(5);
179
180 TensorInfo inputTensorInfo2 = runtime->GetInputTensorInfo(netId, 0);
181 inputTensorInfo2.SetConstant(true);
182 armnn::InputTensors inputTensors
183 {
184 {0, armnn::ConstTensor(inputTensorInfo2, inputData.data())}
185 };
186 armnn::OutputTensors outputTensors
187 {
188 {0, armnn::Tensor(runtime->GetOutputTensorInfo(netId, 0), outputData.data())}
189 };
190
191 runtime->GetProfiler(netId)->EnableProfiling(true);
192
193 // do the inferences
194 runtime->EnqueueWorkload(netId, inputTensors, outputTensors);
195 runtime->EnqueueWorkload(netId, inputTensors, outputTensors);
196 runtime->EnqueueWorkload(netId, inputTensors, outputTensors);
197
198 // retrieve the Profiler.Print() output
199 std::stringstream ss;
200 profilerManager.GetProfiler()->Print(ss);
201
202 return ss.str();
203 }
204
ValidateProfilerJson(std::string & result)205 inline void ValidateProfilerJson(std::string& result)
206 {
207 // ensure all measurements are greater than zero
208 std::vector<double> measurementsVector = ExtractMeasurements(result);
209 CHECK(!measurementsVector.empty());
210
211 // check sections contain raw and unit tags
212 // first ensure Parenthesis are balanced
213 if (AreParenthesesMatching(result))
214 {
215 // remove parent sections that will not have raw or unit tag
216 std::vector<std::string> sectionVector = ExtractSections(result);
217 for (size_t i = 0; i < sectionVector.size(); ++i)
218 {
219
220 if (sectionVector[i].find("\"ArmNN\":") != std::string::npos
221 || sectionVector[i].find("\"optimize_measurements\":") != std::string::npos
222 || sectionVector[i].find("\"loaded_network_measurements\":") != std::string::npos
223 || sectionVector[i].find("\"inference_measurements\":") != std::string::npos)
224 {
225 sectionVector.erase(sectionVector.begin() + static_cast<int>(i));
226 }
227 }
228 CHECK(!sectionVector.empty());
229
230 CHECK(std::all_of(sectionVector.begin(), sectionVector.end(),
231 [](std::string i) { return (i.find("\"raw\":") != std::string::npos); }));
232
233 CHECK(std::all_of(sectionVector.begin(), sectionVector.end(),
234 [](std::string i) { return (i.find("\"unit\":") != std::string::npos); }));
235 }
236
237 // remove the time measurements as they vary from test to test
238 result.erase(std::remove_if (result.begin(),result.end(),
239 [](char c) { return c == '.'; }), result.end());
240 result.erase(std::remove_if (result.begin(), result.end(), &isdigit), result.end());
241 result.erase(std::remove_if (result.begin(),result.end(),
242 [](char c) { return c == '\t'; }), result.end());
243
244 CHECK(result.find("ArmNN") != std::string::npos);
245 CHECK(result.find("inference_measurements") != std::string::npos);
246
247 // ensure no spare parenthesis present in print output
248 CHECK(AreParenthesesMatching(result));
249 }
250
RunSoftmaxProfilerJsonPrinterTest(const std::vector<armnn::BackendId> & backends)251 void RunSoftmaxProfilerJsonPrinterTest(const std::vector<armnn::BackendId>& backends)
252 {
253 // setup the test fixture and obtain JSON Printer result
254 std::string result = GetSoftmaxProfilerJson(backends);
255
256 // validate the JSON Printer result
257 ValidateProfilerJson(result);
258
259 const armnn::BackendId& firstBackend = backends.at(0);
260 if (firstBackend == armnn::Compute::GpuAcc)
261 {
262 CHECK(result.find("OpenClKernelTimer/: softmax_layer_max_shift_exp_sum_quantized_serial GWS[,,]")
263 != std::string::npos);
264 }
265 else if (firstBackend == armnn::Compute::CpuAcc)
266 {
267 CHECK(result.find("NeonKernelTimer") != std::string::npos); // Validate backend
268
269 bool softmaxCheck = ((result.find("softmax") != std::string::npos) || // Validate softmax
270 (result.find("Softmax") != std::string::npos) ||
271 (result.find("SoftMax") != std::string::npos));
272 CHECK(softmaxCheck);
273
274 }
275 }
276