From fd627ffaec8fd8801d980b4c91ee7c0607ab6aaf Mon Sep 17 00:00:00 2001 From: Jan Eilers Date: Thu, 25 Feb 2021 17:44:00 +0000 Subject: IVGCVSW-5687 Update Doxygen Docu * Update Doxygen Documentation for 21.02 release Signed-off-by: Jan Eilers Change-Id: I9ed2f9caab038836ea99d7b378d7899fe431a4e5 --- 21.02/classarmnn_1_1_network_quantizer.xhtml | 399 +++++++++++++++++++++++++++ 1 file changed, 399 insertions(+) create mode 100644 21.02/classarmnn_1_1_network_quantizer.xhtml (limited to '21.02/classarmnn_1_1_network_quantizer.xhtml') diff --git a/21.02/classarmnn_1_1_network_quantizer.xhtml b/21.02/classarmnn_1_1_network_quantizer.xhtml new file mode 100644 index 0000000000..dd4fa1c27c --- /dev/null +++ b/21.02/classarmnn_1_1_network_quantizer.xhtml @@ -0,0 +1,399 @@ + + + + + + + + + + + + + +ArmNN: NetworkQuantizer Class Reference + + + + + + + + + + + + + + + + +
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+ + + + ArmNN + + + +
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+  21.02 +
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+Public Member Functions | +List of all members
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+
NetworkQuantizer Class Reference
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+ +

#include <NetworkQuantizer.hpp>

+
+Inheritance diagram for NetworkQuantizer:
+
+
+ + +INetworkQuantizer + +
+ + + + + + + + + + + + + + + +

+Public Member Functions

 NetworkQuantizer (INetwork *inputNetwork, const QuantizerOptions &options)
 
void OverrideInputRange (LayerBindingId layerId, float min, float max) override
 Overrides the default quantization values for the input layer with the given id. More...
 
void Refine (const InputTensors &inputTensors) override
 Refine input network with a set of refinement data for specified LayerBindingId. More...
 
std::pair< float, float > GetMinMaxRange (LayerGuid guid, unsigned int idx)
 
INetworkPtr ExportNetwork () override
 Extract final quantized network. More...
 
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+Additional Inherited Members

- Static Public Member Functions inherited from INetworkQuantizer
static INetworkQuantizer * CreateRaw (INetwork *inputNetwork, const QuantizerOptions &options=QuantizerOptions())
 Create Quantizer object and return raw pointer. More...
 
static INetworkQuantizerPtr Create (INetwork *inputNetwork, const QuantizerOptions &options=QuantizerOptions())
 Create Quantizer object wrapped in unique_ptr. More...
 
static void Destroy (INetworkQuantizer *quantizer)
 Destroy Quantizer object. More...
 
- Protected Member Functions inherited from INetworkQuantizer
virtual ~INetworkQuantizer ()
 
+

Detailed Description

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+

Definition at line 20 of file NetworkQuantizer.hpp.

+

Constructor & Destructor Documentation

+ +

◆ NetworkQuantizer()

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NetworkQuantizer (INetwork * inputNetwork,
const QuantizerOptions & options 
)
+ 		+inline
+
+ +

Definition at line 23 of file NetworkQuantizer.hpp.

+ +

References NetworkQuantizer::OverrideInputRange(), and NetworkQuantizer::Refine().

+
24  : m_InputNetwork(inputNetwork),
25  m_NetworkId(0),
26  m_Runtime(nullptr, &IRuntime::Destroy),
27  m_RefineCount(0),
28  m_Options(options) {}
armnn::IRuntime::Destroy
static void Destroy(IRuntime *runtime)
Definition: Runtime.cpp:42
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+
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+

Member Function Documentation

+ +

◆ ExportNetwork()

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INetworkPtr ExportNetwork ()
+ 		+overridevirtual
+
+ +

Extract final quantized network.

+ +

Implements INetworkQuantizer.

+ +

Definition at line 137 of file NetworkQuantizer.cpp.

+ +

References armnn::ApplyStrategyToLayers(), armnn::QAsymmS8, armnn::QAsymmU8, armnn::QSymmS16, armnn::QSymmS8, and Graph::TopologicalSort().

+ +

Referenced by NetworkQuantizer::GetMinMaxRange().

+
138 {
139  const Graph& graph = m_InputNetwork->pNetworkImpl->GetGraph().TopologicalSort();
140 
141  // Step 1) Walk the graph and populate default min/max values for
142  // intermediate tensors, only if Runtime does not exist (created
143  // if Refine has been called)
144  if (!m_Runtime)
145  {
146  m_Ranges.SetDynamicMode(false);
147  StaticRangeStrategy rangeStrategy(m_Ranges);
148  ApplyStrategyToLayers(graph, rangeStrategy);
149  }
150  else
151  {
152  // Set min/max range of non-calibrated layers to parent layer's range
153  m_DynamicQuantizationStrategy.value().VisitNonCalibratedLayers();
154  // now tear down the runtime and the dynamic visitor.
155  m_Runtime.reset(nullptr);
156  m_DynamicQuantizationStrategy = EmptyOptional();
157  m_RefineCount = 0;
158  }
159 
160  // Step 2) Convert input InputNetwork to Quantized InputNetwork
161  std::unique_ptr<IQuantizationScheme> quantizationScheme;
162  switch (m_Options.m_ActivationFormat)
163  {
164  case DataType::QAsymmU8:
165  quantizationScheme = std::make_unique<QAsymmU8QuantizationScheme>();
166  break;
167  case DataType::QAsymmS8:
168  quantizationScheme = std::make_unique<QAsymmS8QuantizationScheme>();
169  break;
170  case DataType::QSymmS8:
171  quantizationScheme = std::make_unique<QSymmS8QuantizationScheme>();
172  break;
173  case DataType::QSymmS16:
174  quantizationScheme = std::make_unique<QSymm16QuantizationScheme>();
175  break;
176  default:
177  throw InvalidArgumentException("Unsupported quantization target");
178  }
179 
180  QuantizerStrategy quantizerVisitor(m_Ranges, quantizationScheme.get(), m_Options.m_PreserveType);
181  ApplyStrategyToLayers(graph, quantizerVisitor);
182 
183  // clear the ranges
184  m_Ranges.Reset();
185 
186  return quantizerVisitor.RetrieveFinalNetwork();
187 }
+ + +
armnn::INetwork::pNetworkImpl
std::unique_ptr< NetworkImpl > pNetworkImpl
Definition: INetwork.hpp:693
+
armnn::ApplyStrategyToLayers
void ApplyStrategyToLayers(const LayerContainer &layerContainer, IStrategy &strategy)
Definition: NetworkQuantizerUtils.hpp:61
+ + +
armnn::RangeTracker::SetDynamicMode
void SetDynamicMode(bool flag)
Definition: RangeTracker.hpp:45
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+ +

◆ GetMinMaxRange()

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std::pair<float, float> GetMinMaxRange (LayerGuid guid,
unsigned int idx 
)
+ 		+inline
+
+ +

Definition at line 34 of file NetworkQuantizer.hpp.

+ +

References NetworkQuantizer::ExportNetwork(), and RangeTracker::GetRange().

+
34 { return m_Ranges.GetRange(guid, idx); }
armnn::RangeTracker::GetRange
MinMaxRange GetRange(LayerGuid guid, unsigned int idx) const
Retrieve the Range for a particular output slot on a particular layer.
Definition: RangeTracker.cpp:29
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◆ OverrideInputRange()

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void OverrideInputRange (LayerBindingId layerId,
float min,
float max 
)
+ 		+overridevirtual
+
+ +

Overrides the default quantization values for the input layer with the given id.

+ +

Implements INetworkQuantizer.

+ +

Definition at line 51 of file NetworkQuantizer.cpp.

+ +

References Graph::GetInputLayers(), and armnn::VisitLayers().

+ +

Referenced by NetworkQuantizer::NetworkQuantizer().

+
52 {
53  const Graph& graph = m_InputNetwork->pNetworkImpl->GetGraph();
54  auto inputLayers = graph.GetInputLayers();
55 
56  // Walk the input layers of the graph and override the quantization parameters of the one with the given id
57  OverrideInputRangeVisitor overrideInputRangeVisitor(m_Ranges, layerId, RangeTracker::MinMaxRange{min, max});
58  VisitLayers(inputLayers, overrideInputRangeVisitor);
59 }
armnn::VisitLayers
void VisitLayers(const LayerContainer &layerContainer, ILayerVisitor &visitor)
Definition: NetworkQuantizerUtils.hpp:50
+
armnn::RangeTracker::MinMaxRange
std::pair< float, float > MinMaxRange
Definition: RangeTracker.hpp:20
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armnn::INetwork::pNetworkImpl
std::unique_ptr< NetworkImpl > pNetworkImpl
Definition: INetwork.hpp:693
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+ +

◆ Refine()

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void Refine (const InputTensors & inputTensors)
+ 		+overridevirtual
+
+ +

Refine input network with a set of refinement data for specified LayerBindingId.

+ +

Implements INetworkQuantizer.

+ +

Definition at line 61 of file NetworkQuantizer.cpp.

+ +

References armnn::ApplyStrategyToLayers(), IRuntime::Create(), armnnUtils::FindMinMax(), armnn::Optimize(), and Graph::TopologicalSort().

+ +

Referenced by NetworkQuantizer::NetworkQuantizer().

+
62 {
63  // The first time Refine is called the m_Runtime and the DynamicQuantizationStrategy
64  // will not have been created. Need to get the environment set up, Runtime loaded,
65  // DynamicQuantizationStrategy created and run over the network to initialise itself
66  // and the RangeTracker the Debug callback registered and an initial inference
67  // done to set up the first min/max values
68  if (!m_Runtime)
69  {
70  m_RefineCount = 0;
71  m_Ranges.SetDynamicMode(true);
72  const Graph& cGraph = m_InputNetwork->pNetworkImpl->GetGraph().TopologicalSort();
73 
74  // need to insert Debug layers in the DynamicQuantizationStrategy
75  Graph& graph = const_cast<Graph&>(cGraph);
76 
77  // Initialize RangeTracker to the default values for each layer.
78  // The default values are overwritten by the min/max that is
79  // recorded during the first dataset min/max calibration. This
80  // initialisation is only required for the first call of Refine().
81  m_DynamicQuantizationStrategy = DynamicQuantizationStrategy(m_Ranges, graph);
82  ApplyStrategyToLayers(cGraph, m_DynamicQuantizationStrategy.value());
83 
84  IRuntime::CreationOptions options;
85  m_Runtime = IRuntime::Create(options);
86 
87  // Optimize network - debug already enabled for layers that require quantization
88  OptimizerOptions optimizerOptions(false, false);
89  std::vector<BackendId> backends = {"CpuRef"};
90  IOptimizedNetworkPtr optimizedNet = Optimize(*m_InputNetwork,
91  backends,
92  m_Runtime->GetDeviceSpec(),
93  optimizerOptions);
94 
95  m_Runtime->LoadNetwork(m_NetworkId, std::move(optimizedNet));
96 
97  // Debug callback function to refine min/max in RangeTracker
98  auto rangeTrackerCallback = [&](LayerGuid guid, unsigned int slotIndex, ITensorHandle *tensorHandle) {
99  // Get min/max pair from tensor data
100  std::pair<float, float> minMax = armnnUtils::FindMinMax(tensorHandle);
101 
102  // For first calibration dataset, set min/max range in RangeTracker to
103  // min/max ranges gathered during inference
104  if (m_RefineCount == 0)
105  {
106  m_Ranges.ResetMinMax(guid, slotIndex, minMax.first, minMax.second);
107  }
108  else
109  {
110  // For every other calibration dataset, only set min/max range if the
111  // values gathered are less than / greater than originally recorded.
112  m_Ranges.RefineMin(guid, slotIndex, minMax.first);
113  m_Ranges.RefineMax(guid, slotIndex, minMax.second);
114  }
115  };
116 
117  m_Runtime->RegisterDebugCallback(m_NetworkId, rangeTrackerCallback);
118  }
119 
120  // Create output tensor for EnqueueWorkload
121  std::vector<armnn::BindingPointInfo> outputBindings;
122  auto outputLayers = m_DynamicQuantizationStrategy.value().GetOutputLayers();
123  std::vector<TContainer> outputVectors;
124  for (auto outputLayerBindingId : outputLayers)
125  {
126  auto outputTensorInfo = m_Runtime->GetOutputTensorInfo(m_NetworkId, outputLayerBindingId);
127  outputBindings.push_back(std::make_pair(outputLayerBindingId, outputTensorInfo));
128  outputVectors.push_back(std::vector<float>(outputTensorInfo.GetNumElements(), 0));
129  }
130  OutputTensors outputTensors = armnnUtils::MakeOutputTensors<TContainer>(outputBindings, outputVectors);
131 
132  // Execute EnqueueWorkload with calibration image
133  m_Runtime->EnqueueWorkload(m_NetworkId, inputTensors, outputTensors);
134  ++m_RefineCount;
135 }
armnn::IRuntime::Create
static IRuntimePtr Create(const CreationOptions &options)
Definition: Runtime.cpp:37
+
armnn::RangeTracker::ResetMinMax
void ResetMinMax(LayerGuid guid, unsigned int idx, float newMin, float newMax)
Overwrite min and max in RangeTracker with newMin and newMax.
Definition: RangeTracker.cpp:64
+
armnn::RangeTracker::RefineMax
void RefineMax(LayerGuid guid, unsigned int slotIndex, float newMax)
Update max in RangeTracker with new_max if it is greater than current value.
Definition: RangeTracker.cpp:55
+
armnn::INetwork::pNetworkImpl
std::unique_ptr< NetworkImpl > pNetworkImpl
Definition: INetwork.hpp:693
+
armnn::Optimize
IOptimizedNetworkPtr Optimize(const INetwork &network, const std::vector< BackendId > &backendPreferences, const IDeviceSpec &deviceSpec, const OptimizerOptions &options=OptimizerOptions(), Optional< std::vector< std::string > &> messages=EmptyOptional())
Create an optimized version of the network.
Definition: Network.cpp:1502
+
armnn::ApplyStrategyToLayers
void ApplyStrategyToLayers(const LayerContainer &layerContainer, IStrategy &strategy)
Definition: NetworkQuantizerUtils.hpp:61
+
armnn::OutputTensors
std::vector< std::pair< LayerBindingId, class Tensor > > OutputTensors
Definition: Tensor.hpp:341
+
armnn::IOptimizedNetworkPtr
std::unique_ptr< IOptimizedNetwork, void(*)(IOptimizedNetwork *network)> IOptimizedNetworkPtr
Definition: INetwork.hpp:174
+
armnnUtils::FindMinMax
std::pair< float, float > FindMinMax(armnn::ITensorHandle *tensorHandle)
Definition: TensorUtils.cpp:58
+
armnn::RangeTracker::SetDynamicMode
void SetDynamicMode(bool flag)
Definition: RangeTracker.hpp:45
+
armnn::LayerGuid
profiling::ProfilingGuid LayerGuid
Define LayerGuid type.
Definition: Types.hpp:275
+
armnn::RangeTracker::RefineMin
void RefineMin(LayerGuid guid, unsigned int slotIndex, float newMin)
Update min in RangeTracker with new_min if it is lower than current value.
Definition: RangeTracker.cpp:46
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The documentation for this class was generated from the following files: +
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+ + + + -- cgit v1.2.1