tesseract  4.0.0-1-g2a2b
tesseract::Network Class Reference

#include <network.h>

Inheritance diagram for tesseract::Network:
tesseract::Convolve tesseract::FullyConnected tesseract::Input tesseract::LSTM tesseract::Plumbing tesseract::Reconfig tesseract::Parallel tesseract::Reversed tesseract::Series tesseract::Maxpool

Public Member Functions

 Network ()
 
 Network (NetworkType type, const STRING &name, int ni, int no)
 
virtual ~Network ()=default
 
NetworkType type () const
 
bool IsTraining () const
 
bool needs_to_backprop () const
 
int num_weights () const
 
int NumInputs () const
 
int NumOutputs () const
 
virtual StaticShape InputShape () const
 
virtual StaticShape OutputShape (const StaticShape &input_shape) const
 
const STRINGname () const
 
virtual STRING spec () const
 
bool TestFlag (NetworkFlags flag) const
 
virtual bool IsPlumbingType () const
 
virtual void SetEnableTraining (TrainingState state)
 
virtual void SetNetworkFlags (uint32_t flags)
 
virtual int InitWeights (float range, TRand *randomizer)
 
virtual int RemapOutputs (int old_no, const std::vector< int > &code_map)
 
virtual void ConvertToInt ()
 
virtual void SetRandomizer (TRand *randomizer)
 
virtual bool SetupNeedsBackprop (bool needs_backprop)
 
virtual int XScaleFactor () const
 
virtual void CacheXScaleFactor (int factor)
 
virtual void DebugWeights ()
 
virtual bool Serialize (TFile *fp) const
 
virtual bool DeSerialize (TFile *fp)
 
virtual void Update (float learning_rate, float momentum, float adam_beta, int num_samples)
 
virtual void CountAlternators (const Network &other, double *same, double *changed) const
 
virtual void Forward (bool debug, const NetworkIO &input, const TransposedArray *input_transpose, NetworkScratch *scratch, NetworkIO *output)
 
virtual bool Backward (bool debug, const NetworkIO &fwd_deltas, NetworkScratch *scratch, NetworkIO *back_deltas)
 
void DisplayForward (const NetworkIO &matrix)
 
void DisplayBackward (const NetworkIO &matrix)
 

Static Public Member Functions

static NetworkCreateFromFile (TFile *fp)
 
static void ClearWindow (bool tess_coords, const char *window_name, int width, int height, ScrollView **window)
 
static int DisplayImage (Pix *pix, ScrollView *window)
 

Protected Member Functions

double Random (double range)
 

Protected Attributes

NetworkType type_
 
TrainingState training_
 
bool needs_to_backprop_
 
int32_t network_flags_
 
int32_t ni_
 
int32_t no_
 
int32_t num_weights_
 
STRING name_
 
ScrollViewforward_win_
 
ScrollViewbackward_win_
 
TRandrandomizer_
 

Static Protected Attributes

static char const *const kTypeNames [NT_COUNT]
 

Detailed Description

Definition at line 105 of file network.h.

Constructor & Destructor Documentation

◆ Network() [1/2]

tesseract::Network::Network ( )

Definition at line 76 of file network.cpp.

77  : type_(NT_NONE),
79  needs_to_backprop_(true),
80  network_flags_(0),
81  ni_(0),
82  no_(0),
83  num_weights_(0),
84  forward_win_(nullptr),
85  backward_win_(nullptr),
86  randomizer_(nullptr) {}
int32_t num_weights_
Definition: network.h:305
ScrollView * forward_win_
Definition: network.h:309
TrainingState training_
Definition: network.h:300
NetworkType type_
Definition: network.h:299
bool needs_to_backprop_
Definition: network.h:301
TRand * randomizer_
Definition: network.h:311
ScrollView * backward_win_
Definition: network.h:310
int32_t network_flags_
Definition: network.h:302

◆ Network() [2/2]

tesseract::Network::Network ( NetworkType  type,
const STRING name,
int  ni,
int  no 
)

Definition at line 87 of file network.cpp.

88  : type_(type),
90  needs_to_backprop_(true),
91  network_flags_(0),
92  ni_(ni),
93  no_(no),
94  num_weights_(0),
95  name_(name),
96  forward_win_(nullptr),
97  backward_win_(nullptr),
98  randomizer_(nullptr) {}
int32_t num_weights_
Definition: network.h:305
ScrollView * forward_win_
Definition: network.h:309
TrainingState training_
Definition: network.h:300
NetworkType type_
Definition: network.h:299
bool needs_to_backprop_
Definition: network.h:301
TRand * randomizer_
Definition: network.h:311
const STRING & name() const
Definition: network.h:138
NetworkType type() const
Definition: network.h:112
ScrollView * backward_win_
Definition: network.h:310
int32_t network_flags_
Definition: network.h:302

◆ ~Network()

virtual tesseract::Network::~Network ( )
virtualdefault

Member Function Documentation

◆ Backward()

virtual bool tesseract::Network::Backward ( bool  debug,
const NetworkIO fwd_deltas,
NetworkScratch scratch,
NetworkIO back_deltas 
)
inlinevirtual

Reimplemented in tesseract::LSTM, tesseract::FullyConnected, tesseract::Reversed, tesseract::Series, tesseract::Input, tesseract::Parallel, tesseract::Reconfig, tesseract::Convolve, and tesseract::Maxpool.

Definition at line 273 of file network.h.

275  {
276  tprintf("Must override Network::Backward for type %d\n", type_);
277  return false;
278  }
NetworkType type_
Definition: network.h:299
DLLSYM void tprintf(const char *format,...)
Definition: tprintf.cpp:37

◆ CacheXScaleFactor()

virtual void tesseract::Network::CacheXScaleFactor ( int  factor)
inlinevirtual

Reimplemented in tesseract::Plumbing, tesseract::Series, and tesseract::Input.

Definition at line 215 of file network.h.

215 {}

◆ ClearWindow()

void tesseract::Network::ClearWindow ( bool  tess_coords,
const char *  window_name,
int  width,
int  height,
ScrollView **  window 
)
static

Definition at line 306 of file network.cpp.

307  {
308  if (*window == nullptr) {
309  int min_size = std::min(width, height);
310  if (min_size < kMinWinSize) {
311  if (min_size < 1) min_size = 1;
312  width = width * kMinWinSize / min_size;
313  height = height * kMinWinSize / min_size;
314  }
315  width += kXWinFrameSize;
316  height += kYWinFrameSize;
317  if (width > kMaxWinSize) width = kMaxWinSize;
318  if (height > kMaxWinSize) height = kMaxWinSize;
319  *window = new ScrollView(window_name, 80, 100, width, height, width, height,
320  tess_coords);
321  tprintf("Created window %s of size %d, %d\n", window_name, width, height);
322  } else {
323  (*window)->Clear();
324  }
325 }
const int kMaxWinSize
Definition: network.cpp:51
const int kMinWinSize
Definition: network.cpp:50
const int kXWinFrameSize
Definition: network.cpp:53
DLLSYM void tprintf(const char *format,...)
Definition: tprintf.cpp:37
const int kYWinFrameSize
Definition: network.cpp:54

◆ ConvertToInt()

virtual void tesseract::Network::ConvertToInt ( )
inlinevirtual

Reimplemented in tesseract::LSTM, tesseract::FullyConnected, and tesseract::Plumbing.

Definition at line 191 of file network.h.

191 {}

◆ CountAlternators()

virtual void tesseract::Network::CountAlternators ( const Network other,
double *  same,
double *  changed 
) const
inlinevirtual

Reimplemented in tesseract::Plumbing, tesseract::FullyConnected, and tesseract::LSTM.

Definition at line 236 of file network.h.

237  {}

◆ CreateFromFile()

Network * tesseract::Network::CreateFromFile ( TFile fp)
static

Definition at line 199 of file network.cpp.

199  {
200  Network stub;
201  if (!stub.DeSerialize(fp)) return nullptr;
202  Network* network = nullptr;
203  switch (stub.type_) {
204  case NT_CONVOLVE:
205  network = new Convolve(stub.name_, stub.ni_, 0, 0);
206  break;
207  case NT_INPUT:
208  network = new Input(stub.name_, stub.ni_, stub.no_);
209  break;
210  case NT_LSTM:
211  case NT_LSTM_SOFTMAX:
213  case NT_LSTM_SUMMARY:
214  network =
215  new LSTM(stub.name_, stub.ni_, stub.no_, stub.no_, false, stub.type_);
216  break;
217  case NT_MAXPOOL:
218  network = new Maxpool(stub.name_, stub.ni_, 0, 0);
219  break;
220  // All variants of Parallel.
221  case NT_PARALLEL:
222  case NT_REPLICATED:
223  case NT_PAR_RL_LSTM:
224  case NT_PAR_UD_LSTM:
225  case NT_PAR_2D_LSTM:
226  network = new Parallel(stub.name_, stub.type_);
227  break;
228  case NT_RECONFIG:
229  network = new Reconfig(stub.name_, stub.ni_, 0, 0);
230  break;
231  // All variants of reversed.
232  case NT_XREVERSED:
233  case NT_YREVERSED:
234  case NT_XYTRANSPOSE:
235  network = new Reversed(stub.name_, stub.type_);
236  break;
237  case NT_SERIES:
238  network = new Series(stub.name_);
239  break;
240  case NT_TENSORFLOW:
241 #ifdef INCLUDE_TENSORFLOW
242  network = new TFNetwork(stub.name_);
243 #else
244  tprintf("TensorFlow not compiled in! -DINCLUDE_TENSORFLOW\n");
245 #endif
246  break;
247  // All variants of FullyConnected.
248  case NT_SOFTMAX:
249  case NT_SOFTMAX_NO_CTC:
250  case NT_RELU:
251  case NT_TANH:
252  case NT_LINEAR:
253  case NT_LOGISTIC:
254  case NT_POSCLIP:
255  case NT_SYMCLIP:
256  network = new FullyConnected(stub.name_, stub.ni_, stub.no_, stub.type_);
257  break;
258  default:
259  break;
260  }
261  if (network) {
262  network->training_ = stub.training_;
263  network->needs_to_backprop_ = stub.needs_to_backprop_;
264  network->network_flags_ = stub.network_flags_;
265  network->num_weights_ = stub.num_weights_;
266  if (!network->DeSerialize(fp)) {
267  delete network;
268  network = nullptr;
269  }
270  }
271  return network;
272 }
DLLSYM void tprintf(const char *format,...)
Definition: tprintf.cpp:37

◆ DebugWeights()

virtual void tesseract::Network::DebugWeights ( )
inlinevirtual

Reimplemented in tesseract::Plumbing, tesseract::LSTM, and tesseract::FullyConnected.

Definition at line 218 of file network.h.

218  {
219  tprintf("Must override Network::DebugWeights for type %d\n", type_);
220  }
NetworkType type_
Definition: network.h:299
DLLSYM void tprintf(const char *format,...)
Definition: tprintf.cpp:37

◆ DeSerialize()

bool tesseract::Network::DeSerialize ( TFile fp)
virtual

Reimplemented in tesseract::Plumbing, tesseract::LSTM, tesseract::FullyConnected, tesseract::Reconfig, tesseract::Input, tesseract::Convolve, and tesseract::Maxpool.

Definition at line 170 of file network.cpp.

170  {
171  int8_t data;
172  if (!fp->DeSerialize(&data)) return false;
173  if (data == NT_NONE) {
174  STRING type_name;
175  if (!type_name.DeSerialize(fp)) return false;
176  for (data = 0; data < NT_COUNT && type_name != kTypeNames[data]; ++data) {
177  }
178  if (data == NT_COUNT) {
179  tprintf("Invalid network layer type:%s\n", type_name.string());
180  return false;
181  }
182  }
183  type_ = static_cast<NetworkType>(data);
184  if (!fp->DeSerialize(&data)) return false;
186  if (!fp->DeSerialize(&data)) return false;
187  needs_to_backprop_ = data != 0;
188  if (!fp->DeSerialize(&network_flags_)) return false;
189  if (!fp->DeSerialize(&ni_)) return false;
190  if (!fp->DeSerialize(&no_)) return false;
191  if (!fp->DeSerialize(&num_weights_)) return false;
192  if (!name_.DeSerialize(fp)) return false;
193  return true;
194 }
int32_t num_weights_
Definition: network.h:305
bool DeSerialize(bool swap, FILE *fp)
Definition: strngs.cpp:161
const char * string() const
Definition: strngs.cpp:196
NetworkType
Definition: network.h:43
TrainingState training_
Definition: network.h:300
NetworkType type_
Definition: network.h:299
bool needs_to_backprop_
Definition: network.h:301
static char const *const kTypeNames[NT_COUNT]
Definition: network.h:314
DLLSYM void tprintf(const char *format,...)
Definition: tprintf.cpp:37
Definition: strngs.h:45
int32_t network_flags_
Definition: network.h:302

◆ DisplayBackward()

void tesseract::Network::DisplayBackward ( const NetworkIO matrix)

Definition at line 293 of file network.cpp.

293  {
294 #ifndef GRAPHICS_DISABLED // do nothing if there's no graphics
295  Pix* image = matrix.ToPix();
296  STRING window_name = name_ + "-back";
297  ClearWindow(false, window_name.string(), pixGetWidth(image),
298  pixGetHeight(image), &backward_win_);
299  DisplayImage(image, backward_win_);
301 #endif // GRAPHICS_DISABLED
302 }
const char * string() const
Definition: strngs.cpp:196
static void Update()
Definition: scrollview.cpp:711
static void ClearWindow(bool tess_coords, const char *window_name, int width, int height, ScrollView **window)
Definition: network.cpp:306
static int DisplayImage(Pix *pix, ScrollView *window)
Definition: network.cpp:329
ScrollView * backward_win_
Definition: network.h:310
Definition: strngs.h:45

◆ DisplayForward()

void tesseract::Network::DisplayForward ( const NetworkIO matrix)

Definition at line 282 of file network.cpp.

282  {
283 #ifndef GRAPHICS_DISABLED // do nothing if there's no graphics
284  Pix* image = matrix.ToPix();
285  ClearWindow(false, name_.string(), pixGetWidth(image),
286  pixGetHeight(image), &forward_win_);
287  DisplayImage(image, forward_win_);
288  forward_win_->Update();
289 #endif // GRAPHICS_DISABLED
290 }
const char * string() const
Definition: strngs.cpp:196
ScrollView * forward_win_
Definition: network.h:309
static void Update()
Definition: scrollview.cpp:711
static void ClearWindow(bool tess_coords, const char *window_name, int width, int height, ScrollView **window)
Definition: network.cpp:306
static int DisplayImage(Pix *pix, ScrollView *window)
Definition: network.cpp:329

◆ DisplayImage()

int tesseract::Network::DisplayImage ( Pix *  pix,
ScrollView window 
)
static

Definition at line 329 of file network.cpp.

329  {
330  int height = pixGetHeight(pix);
331  window->Image(pix, 0, 0);
332  pixDestroy(&pix);
333  return height;
334 }
void Image(struct Pix *image, int x_pos, int y_pos)
Definition: scrollview.cpp:768

◆ Forward()

virtual void tesseract::Network::Forward ( bool  debug,
const NetworkIO input,
const TransposedArray input_transpose,
NetworkScratch scratch,
NetworkIO output 
)
inlinevirtual

Reimplemented in tesseract::LSTM, tesseract::FullyConnected, tesseract::Reversed, tesseract::Series, tesseract::Input, tesseract::Parallel, tesseract::Reconfig, tesseract::Convolve, and tesseract::Maxpool.

Definition at line 262 of file network.h.

264  {
265  tprintf("Must override Network::Forward for type %d\n", type_);
266  }
NetworkType type_
Definition: network.h:299
DLLSYM void tprintf(const char *format,...)
Definition: tprintf.cpp:37

◆ InitWeights()

int tesseract::Network::InitWeights ( float  range,
TRand randomizer 
)
virtual

Reimplemented in tesseract::LSTM, tesseract::FullyConnected, tesseract::Plumbing, and tesseract::Series.

Definition at line 130 of file network.cpp.

130  {
131  randomizer_ = randomizer;
132  return 0;
133 }
TRand * randomizer_
Definition: network.h:311

◆ InputShape()

virtual StaticShape tesseract::Network::InputShape ( ) const
inlinevirtual

Reimplemented in tesseract::Input, and tesseract::Plumbing.

Definition at line 127 of file network.h.

127  {
128  StaticShape result;
129  return result;
130  }

◆ IsPlumbingType()

virtual bool tesseract::Network::IsPlumbingType ( ) const
inlinevirtual

Reimplemented in tesseract::Plumbing.

Definition at line 152 of file network.h.

152 { return false; }

◆ IsTraining()

bool tesseract::Network::IsTraining ( ) const
inline

Definition at line 115 of file network.h.

115 { return training_ == TS_ENABLED; }
TrainingState training_
Definition: network.h:300

◆ name()

const STRING& tesseract::Network::name ( ) const
inline

Definition at line 138 of file network.h.

138  {
139  return name_;
140  }

◆ needs_to_backprop()

bool tesseract::Network::needs_to_backprop ( ) const
inline

Definition at line 116 of file network.h.

116  {
117  return needs_to_backprop_;
118  }
bool needs_to_backprop_
Definition: network.h:301

◆ num_weights()

int tesseract::Network::num_weights ( ) const
inline

Definition at line 119 of file network.h.

119 { return num_weights_; }
int32_t num_weights_
Definition: network.h:305

◆ NumInputs()

int tesseract::Network::NumInputs ( ) const
inline

Definition at line 120 of file network.h.

120  {
121  return ni_;
122  }

◆ NumOutputs()

int tesseract::Network::NumOutputs ( ) const
inline

Definition at line 123 of file network.h.

123  {
124  return no_;
125  }

◆ OutputShape()

virtual StaticShape tesseract::Network::OutputShape ( const StaticShape input_shape) const
inlinevirtual

Reimplemented in tesseract::LSTM, tesseract::Input, tesseract::Reconfig, tesseract::FullyConnected, tesseract::Parallel, tesseract::Reversed, and tesseract::Series.

Definition at line 133 of file network.h.

133  {
134  StaticShape result(input_shape);
135  result.set_depth(no_);
136  return result;
137  }

◆ Random()

double tesseract::Network::Random ( double  range)
protected

Definition at line 275 of file network.cpp.

275  {
276  ASSERT_HOST(randomizer_ != nullptr);
277  return randomizer_->SignedRand(range);
278 }
TRand * randomizer_
Definition: network.h:311
double SignedRand(double range)
Definition: helpers.h:61
#define ASSERT_HOST(x)
Definition: errcode.h:84

◆ RemapOutputs()

virtual int tesseract::Network::RemapOutputs ( int  old_no,
const std::vector< int > &  code_map 
)
inlinevirtual

Reimplemented in tesseract::LSTM, tesseract::FullyConnected, tesseract::Plumbing, and tesseract::Series.

Definition at line 186 of file network.h.

186  {
187  return 0;
188  }

◆ Serialize()

bool tesseract::Network::Serialize ( TFile fp) const
virtual

Reimplemented in tesseract::Plumbing, tesseract::LSTM, tesseract::FullyConnected, tesseract::Reconfig, tesseract::Input, and tesseract::Convolve.

Definition at line 151 of file network.cpp.

151  {
152  int8_t data = NT_NONE;
153  if (!fp->Serialize(&data)) return false;
154  STRING type_name = kTypeNames[type_];
155  if (!type_name.Serialize(fp)) return false;
156  data = training_;
157  if (!fp->Serialize(&data)) return false;
158  data = needs_to_backprop_;
159  if (!fp->Serialize(&data)) return false;
160  if (!fp->Serialize(&network_flags_)) return false;
161  if (!fp->Serialize(&ni_)) return false;
162  if (!fp->Serialize(&no_)) return false;
163  if (!fp->Serialize(&num_weights_)) return false;
164  if (!name_.Serialize(fp)) return false;
165  return true;
166 }
bool Serialize(FILE *fp) const
Definition: strngs.cpp:148
int32_t num_weights_
Definition: network.h:305
TrainingState training_
Definition: network.h:300
NetworkType type_
Definition: network.h:299
bool needs_to_backprop_
Definition: network.h:301
static char const *const kTypeNames[NT_COUNT]
Definition: network.h:314
Definition: strngs.h:45
int32_t network_flags_
Definition: network.h:302

◆ SetEnableTraining()

void tesseract::Network::SetEnableTraining ( TrainingState  state)
virtual

Reimplemented in tesseract::LSTM, tesseract::FullyConnected, and tesseract::Plumbing.

Definition at line 110 of file network.cpp.

110  {
111  if (state == TS_RE_ENABLE) {
112  // Enable only from temp disabled.
114  } else if (state == TS_TEMP_DISABLE) {
115  // Temp disable only from enabled.
116  if (training_ == TS_ENABLED) training_ = state;
117  } else {
118  training_ = state;
119  }
120 }
TrainingState training_
Definition: network.h:300

◆ SetNetworkFlags()

void tesseract::Network::SetNetworkFlags ( uint32_t  flags)
virtual

Reimplemented in tesseract::Plumbing.

Definition at line 124 of file network.cpp.

124  {
125  network_flags_ = flags;
126 }
int32_t network_flags_
Definition: network.h:302

◆ SetRandomizer()

void tesseract::Network::SetRandomizer ( TRand randomizer)
virtual

Reimplemented in tesseract::Plumbing.

Definition at line 138 of file network.cpp.

138  {
139  randomizer_ = randomizer;
140 }
TRand * randomizer_
Definition: network.h:311

◆ SetupNeedsBackprop()

bool tesseract::Network::SetupNeedsBackprop ( bool  needs_backprop)
virtual

Reimplemented in tesseract::Plumbing, and tesseract::Series.

Definition at line 145 of file network.cpp.

145  {
146  needs_to_backprop_ = needs_backprop;
147  return needs_backprop || num_weights_ > 0;
148 }
int32_t num_weights_
Definition: network.h:305
bool needs_to_backprop_
Definition: network.h:301

◆ spec()

virtual STRING tesseract::Network::spec ( ) const
inlinevirtual

◆ TestFlag()

bool tesseract::Network::TestFlag ( NetworkFlags  flag) const
inline

Definition at line 144 of file network.h.

144  {
145  return (network_flags_ & flag) != 0;
146  }
int32_t network_flags_
Definition: network.h:302

◆ type()

NetworkType tesseract::Network::type ( ) const
inline

Definition at line 112 of file network.h.

112  {
113  return type_;
114  }
NetworkType type_
Definition: network.h:299

◆ Update()

virtual void tesseract::Network::Update ( float  learning_rate,
float  momentum,
float  adam_beta,
int  num_samples 
)
inlinevirtual

Reimplemented in tesseract::Plumbing, tesseract::FullyConnected, and tesseract::LSTM.

Definition at line 231 of file network.h.

232  {}

◆ XScaleFactor()

virtual int tesseract::Network::XScaleFactor ( ) const
inlinevirtual

Reimplemented in tesseract::Plumbing, tesseract::Series, tesseract::Input, and tesseract::Reconfig.

Definition at line 209 of file network.h.

209  {
210  return 1;
211  }

Member Data Documentation

◆ backward_win_

ScrollView* tesseract::Network::backward_win_
protected

Definition at line 310 of file network.h.

◆ forward_win_

ScrollView* tesseract::Network::forward_win_
protected

Definition at line 309 of file network.h.

◆ kTypeNames

char const *const tesseract::Network::kTypeNames
staticprotected
Initial value:
= {
"Invalid", "Input",
"Convolve", "Maxpool",
"Parallel", "Replicated",
"ParBidiLSTM", "DepParUDLSTM",
"Par2dLSTM", "Series",
"Reconfig", "RTLReversed",
"TTBReversed", "XYTranspose",
"LSTM", "SummLSTM",
"Logistic", "LinLogistic",
"LinTanh", "Tanh",
"Relu", "Linear",
"Softmax", "SoftmaxNoCTC",
"LSTMSoftmax", "LSTMBinarySoftmax",
"TensorFlow",
}

Definition at line 314 of file network.h.

◆ name_

STRING tesseract::Network::name_
protected

Definition at line 306 of file network.h.

◆ needs_to_backprop_

bool tesseract::Network::needs_to_backprop_
protected

Definition at line 301 of file network.h.

◆ network_flags_

int32_t tesseract::Network::network_flags_
protected

Definition at line 302 of file network.h.

◆ ni_

int32_t tesseract::Network::ni_
protected

Definition at line 303 of file network.h.

◆ no_

int32_t tesseract::Network::no_
protected

Definition at line 304 of file network.h.

◆ num_weights_

int32_t tesseract::Network::num_weights_
protected

Definition at line 305 of file network.h.

◆ randomizer_

TRand* tesseract::Network::randomizer_
protected

Definition at line 311 of file network.h.

◆ training_

TrainingState tesseract::Network::training_
protected

Definition at line 300 of file network.h.

◆ type_

NetworkType tesseract::Network::type_
protected

Definition at line 299 of file network.h.


The documentation for this class was generated from the following files: