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
|
//
// Copyright © 2017 Arm Ltd. All rights reserved.
// See LICENSE file in the project root for full license information.
//
#include "Layer.hpp"
#include "Graph.hpp"
#include "backends/WorkloadData.hpp"
#include <boost/cast.hpp>
#include <boost/format.hpp>
#include <boost/log/trivial.hpp>
#include <numeric>
namespace armnn
{
void InputSlot::Insert(Layer& layer)
{
BOOST_ASSERT(layer.GetNumOutputSlots() == 1);
OutputSlot* const prevSlot = GetConnectedOutputSlot();
if (prevSlot != nullptr)
{
// Disconnect parent from this
prevSlot->Disconnect(*this);
// Connect inserted layer to parent
BOOST_ASSERT(layer.GetNumInputSlots() == 1);
prevSlot->Connect(layer.GetInputSlot(0));
// Set tensor info for inserted layer
const TensorInfo& tensorInfo = prevSlot->GetTensorInfo();
layer.GetOutputHandler().SetTensorInfo(tensorInfo);
}
// Connect inserted layer to this
layer.GetOutputSlot(0).Connect(*this);
}
const InputSlot* OutputSlot::GetConnection(unsigned int index) const
{
ValidateConnectionIndex(index);
return m_Connections[index];
}
InputSlot* OutputSlot::GetConnection(unsigned int index)
{
ValidateConnectionIndex(index);
return m_Connections[index];
}
void OutputSlot::SetTensorInfo(const TensorInfo& tensorInfo)
{
GetOutputHandler().SetTensorInfo(tensorInfo);
}
const TensorInfo& OutputSlot::GetTensorInfo() const
{
return GetOutputHandler().GetTensorInfo();
}
bool OutputSlot::IsTensorInfoSet() const
{
return GetOutputHandler().IsTensorInfoSet();
}
bool OutputSlot::ValidateTensorShape(const TensorShape& shape) const
{
BOOST_ASSERT_MSG(IsTensorInfoSet(), "TensorInfo must be set in order to validate the shape.");
return shape == m_OutputHandler.GetTensorInfo().GetShape();
}
int OutputSlot::Connect(InputSlot& destination)
{
destination.SetConnection(this);
m_Connections.push_back(&destination);
return boost::numeric_cast<int>(m_Connections.size() - 1);
}
void OutputSlot::Disconnect(InputSlot& slot)
{
slot.SetConnection(nullptr);
m_Connections.erase(std::remove(m_Connections.begin(), m_Connections.end(), &slot), m_Connections.end());
}
void OutputSlot::DisconnectAll()
{
while (GetNumConnections() > 0)
{
InputSlot& connection = *GetConnection(0);
Disconnect(connection);
}
}
void OutputSlot::MoveAllConnections(OutputSlot& destination)
{
while (GetNumConnections() > 0)
{
InputSlot& connection = *GetConnection(0);
Disconnect(connection);
destination.Connect(connection);
}
}
void OutputSlot::ValidateConnectionIndex(unsigned int index) const
{
if (boost::numeric_cast<std::size_t>(index) >= m_Connections.size())
{
throw InvalidArgumentException(
boost::str(boost::format("GetConnection: Invalid index %1% provided") % index));
}
}
namespace {
LayerGuid GenerateLayerGuid()
{
//Note: Not thread safe.
static LayerGuid newGuid=0;
return newGuid++;
}
} //namespace
Layer::Layer(unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const char* name)
: m_OutputHandlers(numOutputSlots)
, m_LayerName(name ? name : "")
, m_Type(type)
, m_ComputeDevice(Compute::Undefined)
, m_Guid(GenerateLayerGuid())
{
m_InputSlots.reserve(numInputSlots);
for (unsigned int i = 0; i < numInputSlots; ++i)
{
m_InputSlots.emplace_back(*this, i);
}
m_OutputSlots.reserve(numOutputSlots);
for (unsigned int i = 0; i < numOutputSlots; ++i)
{
m_OutputSlots.emplace_back(*this, m_OutputHandlers[i]);
}
}
void Layer::CollectWorkloadInputs(WorkloadDataCollector& dataCollector, const Graph& graph) const
{
for (auto&& inputSlot : GetInputSlots())
{
// The graph must be well-formed at this point
BOOST_ASSERT(inputSlot.GetConnection());
const OutputHandler& outputHandler = inputSlot.GetConnectedOutputSlot()->GetOutputHandler();
dataCollector.Push(outputHandler.GetData(), outputHandler.GetTensorInfo());
}
}
void Layer::CollectWorkloadOutputs(WorkloadDataCollector& dataCollector, const Graph& graph) const
{
for (auto&& outputHandler : m_OutputHandlers)
{
outputHandler.CollectWorkloadOutputs(dataCollector);
}
}
void Layer::CreateTensorHandles(Graph& graph, const IWorkloadFactory& factory)
{
for (auto&& outputHandler : m_OutputHandlers)
{
outputHandler.CreateTensorHandles(factory);
}
}
DataType Layer::GetDataType() const
{
if (GetNumInputSlots() > 0) // Ignore the input layer
{
return GetInputSlot(0).GetConnection()->GetTensorInfo().GetDataType();
}
return DataType::Float32;
}
void Layer::ResetPriority() const
{
m_Priority = 0;
m_Visiting = false;
}
LayerPriority Layer::GetPriority() const
{
constexpr LayerPriority inputPrio = std::numeric_limits<LayerPriority>::lowest();
constexpr LayerPriority outputPrio = std::numeric_limits<LayerPriority>::max();
if (GetType() == LayerType::Input)
{
m_Priority = inputPrio;
}
else if (GetType() == LayerType::Output)
{
m_Priority = outputPrio;
}
else if (m_Priority == 0)
{
if (m_Visiting)
{
throw GraphValidationException("Graph has circular dependencies: cannot walk");
}
auto maxPrio = [](const LayerPriority prio, const InputSlot& slot) -> LayerPriority
{
const Layer& input = slot.GetConnectedOutputSlot()->GetOwningLayer();
return std::max(prio, input.GetPriority());
};
m_Visiting = true;
LayerPriority parentPrio = std::accumulate(GetInputSlots().cbegin(), GetInputSlots().cend(), 0U, maxPrio);
m_Visiting = false;
if (parentPrio >= outputPrio)
{
throw GraphValidationException("Graph has too many edges");
}
m_Priority = parentPrio + 1U;
}
return m_Priority;
}
} // namespace armnn
|
