tesseract 4.1.1
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tesseract::Parallel Class Reference

#include <parallel.h>

Inheritance diagram for tesseract::Parallel:
tesseract::Plumbing tesseract::Network

Public Member Functions

 Parallel (const STRING &name, NetworkType type)
 
 ~Parallel () override=default
 
StaticShape OutputShape (const StaticShape &input_shape) const override
 
STRING spec () const override
 
void Forward (bool debug, const NetworkIO &input, const TransposedArray *input_transpose, NetworkScratch *scratch, NetworkIO *output) override
 
bool Backward (bool debug, const NetworkIO &fwd_deltas, NetworkScratch *scratch, NetworkIO *back_deltas) override
 
- Public Member Functions inherited from tesseract::Plumbing
 Plumbing (const STRING &name)
 
 ~Plumbing () override=default
 
StaticShape InputShape () const override
 
STRING spec () const override
 
bool IsPlumbingType () const override
 
void SetEnableTraining (TrainingState state) override
 
void SetNetworkFlags (uint32_t flags) override
 
int InitWeights (float range, TRand *randomizer) override
 
int RemapOutputs (int old_no, const std::vector< int > &code_map) override
 
void ConvertToInt () override
 
void SetRandomizer (TRand *randomizer) override
 
virtual void AddToStack (Network *network)
 
bool SetupNeedsBackprop (bool needs_backprop) override
 
int XScaleFactor () const override
 
void CacheXScaleFactor (int factor) override
 
void DebugWeights () override
 
const PointerVector< Network > & stack () const
 
void EnumerateLayers (const STRING *prefix, GenericVector< STRING > *layers) const
 
NetworkGetLayer (const char *id) const
 
float LayerLearningRate (const char *id) const
 
void ScaleLayerLearningRate (const char *id, double factor)
 
float * LayerLearningRatePtr (const char *id) const
 
bool Serialize (TFile *fp) const override
 
bool DeSerialize (TFile *fp) override
 
void Update (float learning_rate, float momentum, float adam_beta, int num_samples) override
 
void CountAlternators (const Network &other, double *same, double *changed) const override
 
- Public Member Functions inherited from tesseract::Network
 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 ()=0
 
virtual bool Serialize (TFile *fp) const
 
virtual bool DeSerialize (TFile *fp)=0
 
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)=0
 
virtual bool Backward (bool debug, const NetworkIO &fwd_deltas, NetworkScratch *scratch, NetworkIO *back_deltas)=0
 
void DisplayForward (const NetworkIO &matrix)
 
void DisplayBackward (const NetworkIO &matrix)
 

Additional Inherited Members

- Static Public Member Functions inherited from tesseract::Network
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 inherited from tesseract::Network
double Random (double range)
 
- Protected Attributes inherited from tesseract::Plumbing
PointerVector< Networkstack_
 
GenericVector< float > learning_rates_
 
- Protected Attributes inherited from tesseract::Network
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_
 

Detailed Description

Definition at line 27 of file parallel.h.

Constructor & Destructor Documentation

◆ Parallel()

tesseract::Parallel::Parallel ( const STRING name,
NetworkType  type 
)

Definition at line 31 of file parallel.cpp.

31 : Plumbing(name) {
32 type_ = type;
33}
NetworkType type_
Definition: network.h:293
const STRING & name() const
Definition: network.h:138
NetworkType type() const
Definition: network.h:112
Plumbing(const STRING &name)
Definition: plumbing.cpp:25

◆ ~Parallel()

tesseract::Parallel::~Parallel ( )
overridedefault

Member Function Documentation

◆ Backward()

bool tesseract::Parallel::Backward ( bool  debug,
const NetworkIO fwd_deltas,
NetworkScratch scratch,
NetworkIO back_deltas 
)
overridevirtual

Implements tesseract::Network.

Definition at line 110 of file parallel.cpp.

112 {
113 // If this parallel is a replicator of convolvers, or holds a 1-d LSTM pair,
114 // or a 2-d LSTM quad, do debug locally, and don't pass the flag on.
115 if (debug && type_ != NT_PARALLEL) {
116 DisplayBackward(fwd_deltas);
117 debug = false;
118 }
119 int stack_size = stack_.size();
120 if (type_ == NT_PAR_2D_LSTM) {
121 // Special case, run parallel in parallel.
122 GenericVector<NetworkScratch::IO> in_deltas, out_deltas;
123 in_deltas.init_to_size(stack_size, NetworkScratch::IO());
124 out_deltas.init_to_size(stack_size, NetworkScratch::IO());
125 // Split the forward deltas for each stack element.
126 int feature_offset = 0;
127 for (int i = 0; i < stack_.size(); ++i) {
128 int num_features = stack_[i]->NumOutputs();
129 in_deltas[i].Resize(fwd_deltas, num_features, scratch);
130 out_deltas[i].Resize(fwd_deltas, stack_[i]->NumInputs(), scratch);
131 in_deltas[i]->CopyUnpacking(fwd_deltas, feature_offset, num_features);
132 feature_offset += num_features;
133 }
134#ifdef _OPENMP
135#pragma omp parallel for num_threads(stack_size)
136#endif
137 for (int i = 0; i < stack_size; ++i) {
138 stack_[i]->Backward(debug, *in_deltas[i], scratch,
139 i == 0 ? back_deltas : out_deltas[i]);
140 }
141 if (needs_to_backprop_) {
142 for (int i = 1; i < stack_size; ++i) {
143 back_deltas->AddAllToFloat(*out_deltas[i]);
144 }
145 }
146 } else {
147 // Revolving partial deltas.
148 NetworkScratch::IO in_deltas(fwd_deltas, scratch);
149 // The sum of deltas from different sources, which will eventually go into
150 // back_deltas.
151 NetworkScratch::IO out_deltas;
152 int feature_offset = 0;
153 for (int i = 0; i < stack_.size(); ++i) {
154 int num_features = stack_[i]->NumOutputs();
155 in_deltas->CopyUnpacking(fwd_deltas, feature_offset, num_features);
156 feature_offset += num_features;
157 if (stack_[i]->Backward(debug, *in_deltas, scratch, back_deltas)) {
158 if (i == 0) {
159 out_deltas.ResizeFloat(*back_deltas, back_deltas->NumFeatures(),
160 scratch);
161 out_deltas->CopyAll(*back_deltas);
162 } else if (back_deltas->NumFeatures() == out_deltas->NumFeatures()) {
163 // Widths are allowed to be different going back, as we may have
164 // input nets, so only accumulate the deltas if the widths are the
165 // same.
166 out_deltas->AddAllToFloat(*back_deltas);
167 }
168 }
169 }
170 if (needs_to_backprop_) back_deltas->CopyAll(*out_deltas);
171 }
172 if (needs_to_backprop_) back_deltas->ScaleFloatBy(1.0f / stack_size);
173 return needs_to_backprop_;
174}
@ NT_PARALLEL
Definition: network.h:49
@ NT_PAR_2D_LSTM
Definition: network.h:53
void init_to_size(int size, const T &t)
bool needs_to_backprop_
Definition: network.h:295
void DisplayBackward(const NetworkIO &matrix)
Definition: network.cpp:299
int NumInputs() const
Definition: network.h:120
bool Backward(bool debug, const NetworkIO &fwd_deltas, NetworkScratch *scratch, NetworkIO *back_deltas) override
Definition: parallel.cpp:110
PointerVector< Network > stack_
Definition: plumbing.h:136

◆ Forward()

void tesseract::Parallel::Forward ( bool  debug,
const NetworkIO input,
const TransposedArray input_transpose,
NetworkScratch scratch,
NetworkIO output 
)
overridevirtual

Implements tesseract::Network.

Definition at line 49 of file parallel.cpp.

51 {
52 bool parallel_debug = false;
53 // If this parallel is a replicator of convolvers, or holds a 1-d LSTM pair,
54 // or a 2-d LSTM quad, do debug locally, and don't pass the flag on.
55 if (debug && type_ != NT_PARALLEL) {
56 parallel_debug = true;
57 debug = false;
58 }
59 int stack_size = stack_.size();
60 if (type_ == NT_PAR_2D_LSTM) {
61 // Special case, run parallel in parallel.
63 results.init_to_size(stack_size, NetworkScratch::IO());
64 for (int i = 0; i < stack_size; ++i) {
65 results[i].Resize(input, stack_[i]->NumOutputs(), scratch);
66 }
67#ifdef _OPENMP
68#pragma omp parallel for num_threads(stack_size)
69#endif
70 for (int i = 0; i < stack_size; ++i) {
71 stack_[i]->Forward(debug, input, nullptr, scratch, results[i]);
72 }
73 // Now pack all the results (serially) into the output.
74 int out_offset = 0;
75 output->Resize(*results[0], NumOutputs());
76 for (int i = 0; i < stack_size; ++i) {
77 out_offset = output->CopyPacking(*results[i], out_offset);
78 }
79 } else {
80 // Revolving intermediate result.
81 NetworkScratch::IO result(input, scratch);
82 // Source for divided replicated.
83 NetworkScratch::IO source_part;
84 TransposedArray* src_transpose = nullptr;
85 if (IsTraining() && type_ == NT_REPLICATED) {
86 // Make a transposed copy of the input.
87 input.Transpose(&transposed_input_);
88 src_transpose = &transposed_input_;
89 }
90 // Run each network, putting the outputs into result.
91 int out_offset = 0;
92 for (int i = 0; i < stack_size; ++i) {
93 stack_[i]->Forward(debug, input, src_transpose, scratch, result);
94 // All networks must have the same output width
95 if (i == 0) {
96 output->Resize(*result, NumOutputs());
97 } else {
98 ASSERT_HOST(result->Width() == output->Width());
99 }
100 out_offset = output->CopyPacking(*result, out_offset);
101 }
102 }
103 if (parallel_debug) {
104 DisplayForward(*output);
105 }
106}
#define ASSERT_HOST(x)
Definition: errcode.h:88
@ NT_REPLICATED
Definition: network.h:50
int NumOutputs() const
Definition: network.h:123
void DisplayForward(const NetworkIO &matrix)
Definition: network.cpp:288
bool IsTraining() const
Definition: network.h:115

◆ OutputShape()

StaticShape tesseract::Parallel::OutputShape ( const StaticShape input_shape) const
overridevirtual

Reimplemented from tesseract::Network.

Definition at line 37 of file parallel.cpp.

37 {
38 StaticShape result = stack_[0]->OutputShape(input_shape);
39 int stack_size = stack_.size();
40 for (int i = 1; i < stack_size; ++i) {
41 StaticShape shape = stack_[i]->OutputShape(input_shape);
42 result.set_depth(result.depth() + shape.depth());
43 }
44 return result;
45}

◆ spec()

STRING tesseract::Parallel::spec ( ) const
inlineoverridevirtual

Reimplemented from tesseract::Network.

Definition at line 37 of file parallel.h.

37 {
39 if (type_ == NT_PAR_2D_LSTM) {
40 // We have 4 LSTMs operating in parallel here, so the size of each is
41 // the number of outputs/4.
42 spec.add_str_int("L2xy", no_ / 4);
43 } else if (type_ == NT_PAR_RL_LSTM) {
44 // We have 2 LSTMs operating in parallel here, so the size of each is
45 // the number of outputs/2.
46 if (stack_[0]->type() == NT_LSTM_SUMMARY)
47 spec.add_str_int("Lbxs", no_ / 2);
48 else
49 spec.add_str_int("Lbx", no_ / 2);
50 } else {
51 if (type_ == NT_REPLICATED) {
52 spec.add_str_int("R", stack_.size());
53 spec += "(";
54 spec += stack_[0]->spec();
55 } else {
56 spec = "(";
57 for (int i = 0; i < stack_.size(); ++i) spec += stack_[i]->spec();
58 }
59 spec += ")";
60 }
61 return spec;
62 }
@ NT_LSTM_SUMMARY
Definition: network.h:61
@ NT_PAR_RL_LSTM
Definition: network.h:51
Definition: strngs.h:45
void add_str_int(const char *str, int number)
Definition: strngs.cpp:377
STRING spec() const override
Definition: parallel.h:37

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