ArmNN
 20.11
ClBackend.cpp
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1 //
2 // Copyright © 2017 Arm Ltd. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 
6 #include "ClBackend.hpp"
7 #include "ClBackendId.hpp"
9 #include "ClWorkloadFactory.hpp"
10 #include "ClBackendContext.hpp"
11 #include "ClLayerSupport.hpp"
13 
15 #include <armnn/Descriptors.hpp>
16 
20 
24 
33 
34 #include <Optimizer.hpp>
35 
36 #include <arm_compute/core/Types.h>
37 #include <arm_compute/runtime/CL/CLBufferAllocator.h>
38 
39 namespace armnn
40 {
41 
43 {
44  static const BackendId s_Id{ClBackendId()};
45  return s_Id;
46 }
47 
49 {
50  return std::make_unique<ClMemoryManager>(std::make_unique<arm_compute::CLBufferAllocator>());
51 }
52 
54  const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) const
55 {
56  return std::make_unique<ClWorkloadFactory>(
57  PolymorphicPointerDowncast<ClMemoryManager>(memoryManager));
58 }
59 
61  const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, const ModelOptions& modelOptions) const
62 {
63  return std::make_unique<ClWorkloadFactory>(
64  PolymorphicPointerDowncast<ClMemoryManager>(memoryManager), CreateBackendSpecificModelContext(modelOptions));
65 }
66 
68  TensorHandleFactoryRegistry& registry) const
69 {
70  auto memoryManager = std::make_shared<ClMemoryManager>(std::make_unique<arm_compute::CLBufferAllocator>());
71 
72  registry.RegisterMemoryManager(memoryManager);
73  registry.RegisterFactory(std::make_unique<ClTensorHandleFactory>(memoryManager));
74 
75  return std::make_unique<ClWorkloadFactory>(
76  PolymorphicPointerDowncast<ClMemoryManager>(memoryManager));
77 }
78 
80  TensorHandleFactoryRegistry& registry, const ModelOptions& modelOptions) const
81 {
82  auto memoryManager = std::make_shared<ClMemoryManager>(std::make_unique<arm_compute::CLBufferAllocator>());
83 
84  registry.RegisterMemoryManager(memoryManager);
85  registry.RegisterFactory(std::make_unique<ClTensorHandleFactory>(memoryManager));
86 
87  return std::make_unique<ClWorkloadFactory>(
88  PolymorphicPointerDowncast<ClMemoryManager>(memoryManager), CreateBackendSpecificModelContext(modelOptions));
89 }
90 
91 std::vector<ITensorHandleFactory::FactoryId> ClBackend::GetHandleFactoryPreferences() const
92 {
93  return std::vector<ITensorHandleFactory::FactoryId> {ClTensorHandleFactory::GetIdStatic()};
94 }
95 
97 {
98  auto mgr = std::make_shared<ClMemoryManager>(std::make_unique<arm_compute::CLBufferAllocator>());
99 
100  registry.RegisterMemoryManager(mgr);
101  registry.RegisterFactory(std::make_unique<ClTensorHandleFactory>(mgr));
102 }
103 
105 {
106  return IBackendContextPtr{new ClBackendContext{options}};
107 }
108 
111 {
113 }
114 
116 {
117  return Optimizations{};
118 }
119 
121  const ModelOptions& modelOptions) const
122 {
123  return IBackendSpecificModelContextPtr{new ClBackendModelContext{modelOptions}};
124 }
125 
127 {
128  static ILayerSupportSharedPtr layerSupport
129  {
131  };
132  return layerSupport;
133 }
134 
136 {
137  static ILayerSupportSharedPtr layerSupport
138  {
140  };
141  return layerSupport;
142 }
143 
145  const ModelOptions& modelOptions) const
146 {
147  OptimizationViews optimizationViews;
148 
149  auto it = subgraph.end();
150  bool isFastMathEnabled = false;
151  std::map<LayerGuid, Layer*> untouched;
152 
153  while (it != subgraph.begin())
154  {
155  --it;
156  Layer& base = **it;
157  untouched.insert({base.GetGuid(), &base});
158  }
159 
160  it = subgraph.end();
161 #if defined(ARMCOMPUTECL_ENABLED)
163 
164  if (modelContextPtr)
165  {
166  auto clModelOptions = dynamic_cast<ClBackendModelContext*>(modelContextPtr.get());
167  if (clModelOptions)
168  {
169  isFastMathEnabled = clModelOptions->IsFastMathEnabled();
170  }
171  }
172 #endif
173  while (it != subgraph.begin())
174  {
175  --it;
176  Layer& base = **it;
177 
181  || base.GetType() == LayerType::Subtraction || base.GetType() == LayerType::Division)
182  && (base.GetAdditionalInformation<ActivationDescriptor>() == nullptr))
183  {
184  for (auto output = base.BeginOutputSlots(); output != base.EndOutputSlots(); ++output)
185  {
186  if (output->GetNumConnections() == 1)
187  {
188  for (auto&& childInput : output->GetConnections())
189  {
190  if (childInput->GetOwningLayer().GetType() == LayerType::Activation)
191  {
192  Layer& child = childInput->GetOwningLayer();
193 
194  auto* activationLayer = PolymorphicDowncast<ActivationLayer*>(&child);
195 
196  const std::string name = std::string("fused-") + child.GetName() + std::string("-into-") +
197  base.GetName();
198 
199  // Get params from activation layer
200  ActivationDescriptor activationDesc = activationLayer->GetParameters();
201 
202  if (base.GetType() == LayerType::Convolution2d)
203  {
204  Convolution2dLayer* baseLayer = PolymorphicDowncast<Convolution2dLayer*>(&base);
205 
206  Optional<TensorInfo> biases;
207 
208  if (baseLayer->GetParameters().m_BiasEnabled)
209  {
210  biases = baseLayer->m_Bias->GetTensorInfo();
211  }
212 
215  activationLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo(),
216  baseLayer->GetParameters(),
217  baseLayer->m_Weight->GetTensorInfo(),
218  biases,
219  isFastMathEnabled,
220  &activationDesc);
221 
222  if (status)
223  {
224  FuseLayerWithWeightsAndBiases<Convolution2dLayer>(optimizationViews,
225  baseLayer,
226  activationLayer,
227  activationDesc,
228  name);
229  untouched.erase(baseLayer->GetGuid());
230  untouched.erase(activationLayer->GetGuid());
231  }
232  }
233  else if (base.GetType() == LayerType::DepthwiseConvolution2d)
234  {
235  DepthwiseConvolution2dLayer* baseLayer =
236  PolymorphicDowncast<DepthwiseConvolution2dLayer*>(&base);
237 
238  Optional<TensorInfo> biases;
239 
240  if (baseLayer->GetParameters().m_BiasEnabled)
241  {
242  biases = baseLayer->m_Bias->GetTensorInfo();
243  }
244 
247  activationLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo(),
248  baseLayer->GetParameters(),
249  baseLayer->m_Weight->GetTensorInfo(),
250  biases,
251  &activationDesc);
252 
253  if (status)
254  {
255  FuseLayerWithWeightsAndBiases<DepthwiseConvolution2dLayer>(optimizationViews,
256  baseLayer,
257  activationLayer,
258  activationDesc,
259  name);
260  untouched.erase(baseLayer->GetGuid());
261  untouched.erase(activationLayer->GetGuid());
262  }
263  }
264  else if (base.GetType() == LayerType::FullyConnected)
265  {
266  FullyConnectedLayer* baseLayer = PolymorphicDowncast<FullyConnectedLayer*>(&base);
267 
270  activationLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo(),
271  baseLayer->m_Weight->GetTensorInfo(),
272  baseLayer->m_Bias->GetTensorInfo(),
273  baseLayer->GetParameters(),
274  &activationDesc);
275 
276  if (status)
277  {
278  FuseLayerWithWeightsAndBiases<FullyConnectedLayer>(optimizationViews,
279  baseLayer,
280  activationLayer,
281  activationDesc,
282  name);
283  untouched.erase(baseLayer->GetGuid());
284  untouched.erase(activationLayer->GetGuid());
285  }
286  }
287  else if (base.GetType() == LayerType::BatchNormalization)
288  {
289  BatchNormalizationLayer* baseLayer =
290  PolymorphicDowncast<BatchNormalizationLayer*>(&base);
291 
294  activationLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo(),
295  baseLayer->m_Mean->GetTensorInfo(),
296  baseLayer->m_Variance->GetTensorInfo(),
297  baseLayer->m_Beta->GetTensorInfo(),
298  baseLayer->m_Gamma->GetTensorInfo(),
299  baseLayer->GetParameters(),
300  &activationDesc);
301 
302  if (status)
303  {
304  BatchNormalizationLayer* replacementLayer =
305  FuseLayerWithParameters<BatchNormalizationLayer>(optimizationViews,
306  baseLayer,
307  activationLayer,
308  activationDesc,
309  name);
310 
311  replacementLayer->m_Beta = std::move(baseLayer->m_Beta);
312  replacementLayer->m_Gamma = std::move(baseLayer->m_Gamma);
313  replacementLayer->m_Mean = std::move(baseLayer->m_Mean);
314  replacementLayer->m_Variance = std::move(baseLayer->m_Variance);
315  untouched.erase(baseLayer->GetGuid());
316  untouched.erase(activationLayer->GetGuid());
317  }
318  }
319  else if (base.GetType() == LayerType::Addition)
320  {
321  AdditionLayer* baseLayer = PolymorphicDowncast<AdditionLayer*>(&base);
322 
326  activationLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo(),
327  &activationDesc);
328 
329  if (status)
330  {
331  FuseLayerWithoutParameters<AdditionLayer>(optimizationViews,
332  baseLayer,
333  activationLayer,
334  activationDesc,
335  name);
336  untouched.erase(baseLayer->GetGuid());
337  untouched.erase(activationLayer->GetGuid());
338  }
339  }
340  else if (base.GetType() == LayerType::Division)
341  {
342  DivisionLayer* baseLayer = PolymorphicDowncast<DivisionLayer*>(&base);
343 
347  activationLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo(),
348  &activationDesc);
349 
350  if (status)
351  {
352  FuseLayerWithoutParameters<DivisionLayer>(optimizationViews,
353  baseLayer,
354  activationLayer,
355  activationDesc,
356  name);
357  untouched.erase(baseLayer->GetGuid());
358  untouched.erase(activationLayer->GetGuid());
359  }
360  }
361  else if (base.GetType() == LayerType::Multiplication)
362  {
363  MultiplicationLayer* baseLayer = PolymorphicDowncast<MultiplicationLayer*>(&base);
364 
368  activationLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo(),
369  &activationDesc);
370 
371  if (status)
372  {
373  FuseLayerWithoutParameters<MultiplicationLayer>(optimizationViews,
374  baseLayer,
375  activationLayer,
376  activationDesc,
377  name);
378  untouched.erase(baseLayer->GetGuid());
379  untouched.erase(activationLayer->GetGuid());
380  }
381  }
382  else if (base.GetType() == LayerType::Subtraction)
383  {
384  SubtractionLayer* baseLayer = PolymorphicDowncast<SubtractionLayer*>(&base);
385 
389  activationLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo(),
390  &activationDesc);
391 
392  if (status)
393  {
394  FuseLayerWithoutParameters<SubtractionLayer>(optimizationViews,
395  baseLayer,
396  activationLayer,
397  activationDesc,
398  name);
399  untouched.erase(baseLayer->GetGuid());
400  untouched.erase(activationLayer->GetGuid());
401  }
402  }
403  }
404  }
405  }
406  }
407  }
408  }
409 
410  if (optimizationViews.GetSubstitutions().empty())
411  {
412  optimizationViews.AddUntouchedSubgraph(SubgraphView(subgraph));
413  }
414  else
415  {
416  ReportUntouchedLayers(optimizationViews, untouched);
417  }
418 
419  return optimizationViews;
420 }
421 
422 } // namespace armnn
arm_compute::Status ClAdditionValidate(const TensorInfo &input0, const TensorInfo &input1, const TensorInfo &output, const ActivationDescriptor *activationDescriptor)
bool m_BiasEnabled
Enable/disable bias.
void RegisterMemoryManager(std::shared_ptr< IMemoryManager > memoryManger)
Register a memory manager with shared ownership.
arm_compute::Status ClFullyConnectedWorkloadValidate(const TensorInfo &input, const TensorInfo &output, const TensorInfo &weights, const TensorInfo &biases, const FullyConnectedDescriptor &descriptor, const ActivationDescriptor *activationDescriptor)
static const FactoryId & GetIdStatic()
This layer represents a batch normalization operation.
std::unique_ptr< IWorkloadFactory > IWorkloadFactoryPtr
bool m_BiasEnabled
Enable/disable bias.
std::vector< OptimizationPtr > Optimizations
arm_compute::Status ClDivisionWorkloadValidate(const TensorInfo &input0, const TensorInfo &input1, const TensorInfo &output, const ActivationDescriptor *activationDescriptor)
const Parameters & GetParameters() const
std::unique_ptr< ScopedCpuTensorHandle > m_Weight
A unique pointer to store Weight values.
This layer represents a depthwise convolution 2d operation.
std::unique_ptr< ScopedCpuTensorHandle > m_Bias
A unique pointer to store Bias values.
constexpr const char * ClBackendId()
Definition: ClBackendId.hpp:10
std::unique_ptr< ScopedCpuTensorHandle > m_Bias
A unique pointer to store Bias values.
std::vector< BackendOptions > ModelOptions
void RegisterFactory(std::unique_ptr< ITensorHandleFactory > allocator)
Register a TensorHandleFactory and transfer ownership.
void ReportUntouchedLayers(OptimizationViews &optimizationViews, std::map< LayerGuid, Layer *> untouched)
arm_compute::Status ClSubtractionValidate(const TensorInfo &input0, const TensorInfo &input1, const TensorInfo &output, const ActivationDescriptor *activationDescriptor)
std::unique_ptr< ScopedCpuTensorHandle > m_Gamma
A unique pointer to store Gamma values.
std::unique_ptr< ScopedCpuTensorHandle > m_Variance
A unique pointer to store Variance values.
Copyright (c) 2020 ARM Limited.
arm_compute::Status ClConvolution2dWorkloadValidate(const TensorInfo &input, const TensorInfo &output, const Convolution2dDescriptor &descriptor, const TensorInfo &weights, const Optional< TensorInfo > &biases, bool isFastMathEnabled, const ActivationDescriptor *activationDescriptor)
std::unique_ptr< IMemoryManager > IMemoryManagerUniquePtr
IBackendInternal::IMemoryManagerUniquePtr CreateMemoryManager() const override
Definition: ClBackend.cpp:48
void RegisterTensorHandleFactories(TensorHandleFactoryRegistry &registry) override
(Optional) Register TensorHandleFactories Either this method or CreateMemoryManager() and IWorkloadFa...
Definition: ClBackend.cpp:96
std::unique_ptr< ScopedCpuTensorHandle > m_Beta
A unique pointer to store Beta values.
The SubgraphView class represents a subgraph of a Graph.
IBackendInternal::IBackendSpecificModelContextPtr CreateBackendSpecificModelContext(const ModelOptions &modelOptions) const override
Definition: ClBackend.cpp:120
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:313
std::unique_ptr< armnn::profiling::IBackendProfiling > IBackendProfilingPtr
OptimizationViews OptimizeSubgraphView(const SubgraphView &subgraph, const ModelOptions &modelOptions) const override
Definition: ClBackend.cpp:144
This layer represents a fully connected operation.
std::unique_ptr< ScopedCpuTensorHandle > m_Mean
A unique pointer to store Mean values.
std::shared_ptr< IBackendModelContext > IBackendSpecificModelContextPtr
std::shared_ptr< IMemoryManager > IMemoryManagerSharedPtr
IBackendInternal::IBackendContextPtr CreateBackendContext(const IRuntime::CreationOptions &) const override
Create the runtime context of the backend.
Definition: ClBackend.cpp:104
std::unique_ptr< ScopedCpuTensorHandle > m_Weight
A unique pointer to store Weight values.
arm_compute::Status ClMultiplicationWorkloadValidate(const TensorInfo &input0, const TensorInfo &input1, const TensorInfo &output, const ActivationDescriptor *activationDescriptor)
std::vector< ITensorHandleFactory::FactoryId > GetHandleFactoryPreferences() const override
(Optional) Returns a vector of supported TensorHandleFactory ids in preference order.
Definition: ClBackend.cpp:91
Status
enumeration
Definition: Types.hpp:26
const OutputSlot * GetConnectedOutputSlot() const
Definition: Layer.hpp:55
An ActivationDescriptor for the ActivationLayer.
Definition: Descriptors.hpp:20
void AddUntouchedSubgraph(SubgraphView &&subgraph)
IBackendInternal::IWorkloadFactoryPtr CreateWorkloadFactory(const IBackendInternal::IMemoryManagerSharedPtr &memoryManager=nullptr) const override
Definition: ClBackend.cpp:53
This layer represents an addition operation.
std::shared_ptr< ILayerSupport > ILayerSupportSharedPtr
const Substitutions & GetSubstitutions() const
This layer represents a subtraction operation.
std::vector< OutputSlot >::iterator BeginOutputSlots()
Definition: Layer.hpp:242
IBackendInternal::ILayerSupportSharedPtr GetLayerSupport() const override
Definition: ClBackend.cpp:126
IBackendInternal::IBackendProfilingContextPtr CreateBackendProfilingContext(const IRuntime::CreationOptions &, IBackendProfilingPtr &backendProfiling) override
Create context specifically used for profiling interaction from backends.
Definition: ClBackend.cpp:109
std::unique_ptr< ScopedCpuTensorHandle > m_Bias
A unique pointer to store Bias values.
This layer represents a division operation.
std::vector< OutputSlot >::iterator EndOutputSlots()
Definition: Layer.hpp:243
LayerType GetType() const
Definition: Layer.hpp:262
arm_compute::Status ClBatchNormalizationValidate(const TensorInfo &input, const TensorInfo &output, const TensorInfo &mean, const TensorInfo &var, const TensorInfo &beta, const TensorInfo &gamma, const BatchNormalizationDescriptor &desc, const ActivationDescriptor *activationDescriptor)
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:308
This layer represents a convolution 2d operation.
std::unique_ptr< ScopedCpuTensorHandle > m_Weight
A unique pointer to store Weight values.
The ClBackendModelContext is used to pass in CL specific backend ModelOptions.
This layer represents a multiplication operation.
IBackendInternal::Optimizations GetOptimizations() const override
Definition: ClBackend.cpp:115
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:63
static const BackendId & GetIdStatic()
Definition: ClBackend.cpp:42
arm_compute::Status ClDepthwiseConvolutionWorkloadValidate(const TensorInfo &input, const TensorInfo &output, const DepthwiseConvolution2dDescriptor &descriptor, const TensorInfo &weights, const Optional< TensorInfo > &biases, const ActivationDescriptor *activationDescriptor)
std::shared_ptr< armnn::profiling::IBackendProfilingContext > IBackendProfilingContextPtr
This is the bridge between backend and backend profiling we&#39;ll keep it in the backend namespace...
std::shared_ptr< T > GetAdditionalInformation() const
Definition: Layer.hpp:339
LayerGuid GetGuid() const final
Returns the unique id of the layer.
Definition: Layer.hpp:319
std::unique_ptr< IBackendContext > IBackendContextPtr