tesseract  5.0.0
convolve.cpp
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1 // File: convolve.cpp
3 // Description: Convolutional layer that stacks the inputs over its rectangle
4 // and pulls in random data to fill out-of-input inputs.
5 // Output is therefore same size as its input, but deeper.
6 // Author: Ray Smith
7 //
8 // (C) Copyright 2014, Google Inc.
9 // Licensed under the Apache License, Version 2.0 (the "License");
10 // you may not use this file except in compliance with the License.
11 // You may obtain a copy of the License at
12 // http://www.apache.org/licenses/LICENSE-2.0
13 // Unless required by applicable law or agreed to in writing, software
14 // distributed under the License is distributed on an "AS IS" BASIS,
15 // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
16 // See the License for the specific language governing permissions and
17 // limitations under the License.
19 
20 #ifdef HAVE_CONFIG_H
21 # include "config_auto.h"
22 #endif
23 
24 #include "convolve.h"
25 
26 #include "networkscratch.h"
27 #include "serialis.h"
28 
29 namespace tesseract {
30 
31 Convolve::Convolve(const std::string &name, int ni, int half_x, int half_y)
32  : Network(NT_CONVOLVE, name, ni, ni * (2 * half_x + 1) * (2 * half_y + 1))
33  , half_x_(half_x)
34  , half_y_(half_y) {}
35 
36 // Writes to the given file. Returns false in case of error.
37 bool Convolve::Serialize(TFile *fp) const {
38  return Network::Serialize(fp) && fp->Serialize(&half_x_) && fp->Serialize(&half_y_);
39 }
40 
41 // Reads from the given file. Returns false in case of error.
43  if (!fp->DeSerialize(&half_x_)) {
44  return false;
45  }
46  if (!fp->DeSerialize(&half_y_)) {
47  return false;
48  }
49  no_ = ni_ * (2 * half_x_ + 1) * (2 * half_y_ + 1);
50  return true;
51 }
52 
53 // Runs forward propagation of activations on the input line.
54 // See NetworkCpp for a detailed discussion of the arguments.
55 void Convolve::Forward(bool debug, const NetworkIO &input, const TransposedArray *input_transpose,
56  NetworkScratch *scratch, NetworkIO *output) {
57  output->Resize(input, no_);
58  int y_scale = 2 * half_y_ + 1;
59  StrideMap::Index dest_index(output->stride_map());
60  do {
61  // Stack x_scale groups of y_scale * ni_ inputs together.
62  int t = dest_index.t();
63  int out_ix = 0;
64  for (int x = -half_x_; x <= half_x_; ++x, out_ix += y_scale * ni_) {
65  StrideMap::Index x_index(dest_index);
66  if (!x_index.AddOffset(x, FD_WIDTH)) {
67  // This x is outside the image.
68  output->Randomize(t, out_ix, y_scale * ni_, randomizer_);
69  } else {
70  int out_iy = out_ix;
71  for (int y = -half_y_; y <= half_y_; ++y, out_iy += ni_) {
72  StrideMap::Index y_index(x_index);
73  if (!y_index.AddOffset(y, FD_HEIGHT)) {
74  // This y is outside the image.
75  output->Randomize(t, out_iy, ni_, randomizer_);
76  } else {
77  output->CopyTimeStepGeneral(t, out_iy, ni_, input, y_index.t(), 0);
78  }
79  }
80  }
81  }
82  } while (dest_index.Increment());
83 #ifndef GRAPHICS_DISABLED
84  if (debug) {
85  DisplayForward(*output);
86  }
87 #endif
88 }
89 
90 // Runs backward propagation of errors on the deltas line.
91 // See NetworkCpp for a detailed discussion of the arguments.
92 bool Convolve::Backward(bool debug, const NetworkIO &fwd_deltas, NetworkScratch *scratch,
93  NetworkIO *back_deltas) {
94  back_deltas->Resize(fwd_deltas, ni_);
95  NetworkScratch::IO delta_sum;
96  delta_sum.ResizeFloat(fwd_deltas, ni_, scratch);
97  delta_sum->Zero();
98  int y_scale = 2 * half_y_ + 1;
99  StrideMap::Index src_index(fwd_deltas.stride_map());
100  do {
101  // Stack x_scale groups of y_scale * ni_ inputs together.
102  int t = src_index.t();
103  int out_ix = 0;
104  for (int x = -half_x_; x <= half_x_; ++x, out_ix += y_scale * ni_) {
105  StrideMap::Index x_index(src_index);
106  if (x_index.AddOffset(x, FD_WIDTH)) {
107  int out_iy = out_ix;
108  for (int y = -half_y_; y <= half_y_; ++y, out_iy += ni_) {
109  StrideMap::Index y_index(x_index);
110  if (y_index.AddOffset(y, FD_HEIGHT)) {
111  fwd_deltas.AddTimeStepPart(t, out_iy, ni_, delta_sum->f(y_index.t()));
112  }
113  }
114  }
115  }
116  } while (src_index.Increment());
117  back_deltas->CopyAll(*delta_sum);
118  return true;
119 }
120 
121 } // namespace tesseract.
@ NT_CONVOLVE
Definition: network.h:45
@ FD_WIDTH
Definition: stridemap.h:35
@ FD_HEIGHT
Definition: stridemap.h:34
bool DeSerialize(std::string &data)
Definition: serialis.cpp:94
bool Serialize(const std::string &data)
Definition: serialis.cpp:107
void Forward(bool debug, const NetworkIO &input, const TransposedArray *input_transpose, NetworkScratch *scratch, NetworkIO *output) override
Definition: convolve.cpp:55
bool Serialize(TFile *fp) const override
Definition: convolve.cpp:37
bool Backward(bool debug, const NetworkIO &fwd_deltas, NetworkScratch *scratch, NetworkIO *back_deltas) override
Definition: convolve.cpp:92
TESS_API Convolve(const std::string &name, int ni, int half_x, int half_y)
Definition: convolve.cpp:31
bool DeSerialize(TFile *fp) override
Definition: convolve.cpp:42
void DisplayForward(const NetworkIO &matrix)
Definition: network.cpp:333
virtual bool Serialize(TFile *fp) const
Definition: network.cpp:158
TRand * randomizer_
Definition: network.h:312
void Resize(const NetworkIO &src, int num_features)
Definition: networkio.h:45
const StrideMap & stride_map() const
Definition: networkio.h:129
void CopyTimeStepGeneral(int dest_t, int dest_offset, int num_features, const NetworkIO &src, int src_t, int src_offset)
Definition: networkio.cpp:405
void AddTimeStepPart(int t, int offset, int num_features, float *inout) const
Definition: networkio.cpp:650
float * f(int t)
Definition: networkio.h:111
void Randomize(int t, int offset, int num_features, TRand *randomizer)
Definition: networkio.cpp:425
void CopyAll(const NetworkIO &src)
Definition: networkio.cpp:834
void ResizeFloat(const NetworkIO &src, int num_features, NetworkScratch *scratch)
bool AddOffset(int offset, FlexDimensions dimension)
Definition: stridemap.cpp:67