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telsoa014fcda012018-03-09 14:13:49 +00001//
2// Copyright © 2017 Arm Ltd. All rights reserved.
David Beckecb56cd2018-09-05 12:52:57 +01003// SPDX-License-Identifier: MIT
telsoa014fcda012018-03-09 14:13:49 +00004//
5#pragma once
6
Derek Lamberti836b27b2019-11-20 10:51:57 +00007#include "BackendOptions.hpp"
telsoa014fcda012018-03-09 14:13:49 +00008#include "INetwork.hpp"
telsoa01c577f2c2018-08-31 09:22:23 +01009#include "IProfiler.hpp"
Matthew Bentham313e1c82019-03-25 17:37:47 +000010#include "Tensor.hpp"
11#include "Types.hpp"
telsoa014fcda012018-03-09 14:13:49 +000012#include "TypesUtils.hpp"
13
Matthew Bentham313e1c82019-03-25 17:37:47 +000014#include <memory>
15
telsoa014fcda012018-03-09 14:13:49 +000016namespace armnn
17{
18
19using NetworkId = int;
20
telsoa01c577f2c2018-08-31 09:22:23 +010021class IGpuAccTunedParameters;
telsoa014fcda012018-03-09 14:13:49 +000022
23class IRuntime;
24using IRuntimePtr = std::unique_ptr<IRuntime, void(*)(IRuntime* runtime)>;
25
David Monahan4f1e8e42019-09-04 09:22:10 +010026struct INetworkProperties
27{
28 INetworkProperties(bool importEnabled = false, bool exportEnabled = false)
29 : m_ImportEnabled(importEnabled),
30 m_ExportEnabled(exportEnabled) {}
31
32 const bool m_ImportEnabled;
33 const bool m_ExportEnabled;
34
35 virtual ~INetworkProperties() {}
36};
37
telsoa014fcda012018-03-09 14:13:49 +000038class IRuntime
39{
40public:
41 struct CreationOptions
42 {
telsoa01c577f2c2018-08-31 09:22:23 +010043 CreationOptions()
44 : m_GpuAccTunedParameters(nullptr)
45 , m_EnableGpuProfiling(false)
Matteo Martincighe7d44982019-08-05 12:16:47 +010046 , m_DynamicBackendsPath("")
telsoa01c577f2c2018-08-31 09:22:23 +010047 {}
telsoa014fcda012018-03-09 14:13:49 +000048
telsoa01c577f2c2018-08-31 09:22:23 +010049 /// If set, uses the GpuAcc tuned parameters from the given object when executing GPU workloads.
50 /// It will also be updated with new tuned parameters if it is configured to do so.
51 std::shared_ptr<IGpuAccTunedParameters> m_GpuAccTunedParameters;
52
53 // Setting this flag will allow the user to obtain GPU profiling information from the runtime.
54 bool m_EnableGpuProfiling;
Matteo Martincighe7d44982019-08-05 12:16:47 +010055
56 // Setting this value will override the paths set by the DYNAMIC_BACKEND_PATHS compiler directive
57 // Only a single path is allowed for the override
58 std::string m_DynamicBackendsPath;
Aron Virginas-Tar1a0f6912019-08-23 15:18:44 +010059
60 struct ExternalProfilingOptions
61 {
62 ExternalProfilingOptions()
63 : m_EnableProfiling(false)
64 , m_OutgoingCaptureFile("")
65 , m_IncomingCaptureFile("")
66 , m_FileOnly(false)
Colm Donelan02705242019-11-14 14:19:07 +000067 , m_CapturePeriod(LOWEST_CAPTURE_PERIOD)
Aron Virginas-Tar1a0f6912019-08-23 15:18:44 +010068 {}
69
70 bool m_EnableProfiling;
71 std::string m_OutgoingCaptureFile;
72 std::string m_IncomingCaptureFile;
73 bool m_FileOnly;
74 uint32_t m_CapturePeriod;
75 };
Jim Flynn4951b8c2019-10-03 10:04:30 -070076 ExternalProfilingOptions m_ProfilingOptions;
Derek Lamberti836b27b2019-11-20 10:51:57 +000077
78 /// Pass backend specific options.
79 ///
80 /// For example, to enable GpuAcc tuning add the following
81 /// m_BackendOption.emplace_back(
82 /// BackendOptions{"GpuAcc",
83 /// {
84 /// {"TuningLevel", 2},
85 /// {"TuningFile", filename}
86 /// }
87 /// });
88 /// Execute representative workloads through the runtime to generate tuning data.
89 /// The tuning file is written once the runtime is destroyed
90
91 /// To execute with the tuning data, start up with just the tuning file specified.
92 /// m_BackendOption.emplace_back(
93 /// BackendOptions{"GpuAcc",
94 /// {
95 /// {"TuningFile", filename}
96 /// }
97 /// });
98
99 /// The following backend options are available:
100 /// GpuAcc:
101 /// "TuningLevel" : int [0..3] (0=UseOnly(default) | 1=RapidTuning | 2=NormalTuning | 3=ExhaustiveTuning)
102 /// "TuningFile" : string [filenameString]
103 /// "KernelProfilingEnabled" : bool [true | false]
104 std::vector<BackendOptions> m_BackendOptions;
telsoa014fcda012018-03-09 14:13:49 +0000105 };
106
107 static IRuntime* CreateRaw(const CreationOptions& options);
108 static IRuntimePtr Create(const CreationOptions& options);
109 static void Destroy(IRuntime* runtime);
110
telsoa01c577f2c2018-08-31 09:22:23 +0100111 /// Loads a complete network into the IRuntime.
112 /// @param [out] networkIdOut - Unique identifier for the network is returned in this reference.
113 /// @param [in] network - Complete network to load into the IRuntime.
telsoa014fcda012018-03-09 14:13:49 +0000114 /// The runtime takes ownership of the network once passed in.
115 /// @return armnn::Status
116 virtual Status LoadNetwork(NetworkId& networkIdOut, IOptimizedNetworkPtr network) = 0;
117
telsoa01c577f2c2018-08-31 09:22:23 +0100118 /// Load a complete network into the IRuntime.
119 /// @param [out] networkIdOut Unique identifier for the network is returned in this reference.
120 /// @param [in] network Complete network to load into the IRuntime.
121 /// @param [out] errorMessage Error message if there were any errors.
122 /// The runtime takes ownership of the network once passed in.
123 /// @return armnn::Status
124 virtual Status LoadNetwork(NetworkId& networkIdOut,
125 IOptimizedNetworkPtr network,
David Monahan4f1e8e42019-09-04 09:22:10 +0100126 std::string& errorMessage) = 0;
127
128 virtual Status LoadNetwork(NetworkId& networkIdOut,
129 IOptimizedNetworkPtr network,
130 std::string& errorMessage,
131 const INetworkProperties& networkProperties) = 0;
telsoa01c577f2c2018-08-31 09:22:23 +0100132
telsoa014fcda012018-03-09 14:13:49 +0000133 virtual TensorInfo GetInputTensorInfo(NetworkId networkId, LayerBindingId layerId) const = 0;
134 virtual TensorInfo GetOutputTensorInfo(NetworkId networkId, LayerBindingId layerId) const = 0;
135
telsoa01c577f2c2018-08-31 09:22:23 +0100136 /// Evaluates a network using input in inputTensors and outputs filled into outputTensors
telsoa014fcda012018-03-09 14:13:49 +0000137 virtual Status EnqueueWorkload(NetworkId networkId,
telsoa01c577f2c2018-08-31 09:22:23 +0100138 const InputTensors& inputTensors,
139 const OutputTensors& outputTensors) = 0;
telsoa014fcda012018-03-09 14:13:49 +0000140
telsoa01c577f2c2018-08-31 09:22:23 +0100141 /// Unloads a network from the IRuntime.
telsoa014fcda012018-03-09 14:13:49 +0000142 /// At the moment this only removes the network from the m_Impl->m_Network.
143 /// This might need more work in the future to be AndroidNN compliant.
telsoa01c577f2c2018-08-31 09:22:23 +0100144 /// @param [in] networkId - Unique identifier for the network to be unloaded. Generated in LoadNetwork().
telsoa014fcda012018-03-09 14:13:49 +0000145 /// @return armnn::Status
146 virtual Status UnloadNetwork(NetworkId networkId) = 0;
147
telsoa01c577f2c2018-08-31 09:22:23 +0100148 virtual const IDeviceSpec& GetDeviceSpec() const = 0;
149
150 /// Gets the profiler corresponding to the given network id.
151 /// @param networkId The id of the network for which to get the profile.
152 /// @return A pointer to the requested profiler, or nullptr if not found.
153 virtual const std::shared_ptr<IProfiler> GetProfiler(NetworkId networkId) const = 0;
telsoa014fcda012018-03-09 14:13:49 +0000154
Nattapat Chaimanowong6e948202019-03-22 14:01:46 +0000155 /// Registers a callback function to debug layers performing custom computations on intermediate tensors.
156 /// @param networkId The id of the network to register the callback.
157 /// @param func callback function to pass to the debug layer.
158 virtual void RegisterDebugCallback(NetworkId networkId, const DebugCallbackFunction& func) = 0;
159
telsoa014fcda012018-03-09 14:13:49 +0000160protected:
161 ~IRuntime() {}
162};
163
Derek Lamberti836b27b2019-11-20 10:51:57 +0000164
165/// The following API is replaced by the backend options API.
telsoa01c577f2c2018-08-31 09:22:23 +0100166using IGpuAccTunedParametersPtr = std::shared_ptr<IGpuAccTunedParameters>;
telsoa014fcda012018-03-09 14:13:49 +0000167
telsoa01c577f2c2018-08-31 09:22:23 +0100168/// Manages a set of GpuAcc parameters which have been tuned for maximum performance.
169/// Passes an instance of this object to the IRuntime::Create() method (via IRuntime::CreationOptions) to use it
170/// for all GPU workload execution.
telsoa014fcda012018-03-09 14:13:49 +0000171///
172/// Can be created in two modes:
telsoa01c577f2c2018-08-31 09:22:23 +0100173/// - In UseTunedParameters mode, the parameters stored in this object are used to execute GPU workloads.
174/// - In UpdateTunedParameters mode, additionally, whenever a GPU workload is executed for the first time, the
telsoa014fcda012018-03-09 14:13:49 +0000175/// optimum parameters will be found and stored in this object. WARNING - This tuning can be slow.
176///
telsoa01c577f2c2018-08-31 09:22:23 +0100177/// The parameters can be loaded from and saved to a file so that you can first run a slow initial read-write
telsoa014fcda012018-03-09 14:13:49 +0000178/// execution, save the parameters for later and then run fast read-only executions using the optimised parameters.
telsoa01c577f2c2018-08-31 09:22:23 +0100179class IGpuAccTunedParameters
telsoa014fcda012018-03-09 14:13:49 +0000180{
181public:
182 enum class Mode
183 {
184 UseTunedParameters,
185 UpdateTunedParameters
186 };
187
Ruomei Yan49937f32019-04-25 14:24:05 +0100188 enum class TuningLevel
189 {
190 Rapid = 0,
191 Normal = 1,
192 Exhaustive = 2
193 };
194
telsoa014fcda012018-03-09 14:13:49 +0000195 /// Creates an IClTunedParameters with the given mode.
196 /// @{
Ruomei Yan49937f32019-04-25 14:24:05 +0100197 static IGpuAccTunedParameters* CreateRaw(Mode mode, TuningLevel tunerMode);
198 static IGpuAccTunedParametersPtr Create(Mode mode, TuningLevel tunerMode);
telsoa014fcda012018-03-09 14:13:49 +0000199 /// @}
telsoa01c577f2c2018-08-31 09:22:23 +0100200 static void Destroy(IGpuAccTunedParameters* params);
telsoa014fcda012018-03-09 14:13:49 +0000201
202 /// Loads an existing set of tuned parameters from the given file.
203 /// If there is an error loading the file, an armnn::Exception is thrown.
204 virtual void Load(const char* filename) = 0;
205
206 /// Saves the current set of tuned parameters to the given file.
207 /// If there is an error saving to the file, an armnn::Exception is thrown.
208 virtual void Save(const char* filename) const = 0;
209
210protected:
telsoa01c577f2c2018-08-31 09:22:23 +0100211 virtual ~IGpuAccTunedParameters() {};
telsoa014fcda012018-03-09 14:13:49 +0000212};
213
David Monahan4f1e8e42019-09-04 09:22:10 +0100214} // namespace armnn