Mercurial > hgrepos > Python2 > PyMuPDF

annotate mupdf-source/thirdparty/tesseract/src/lstm/networkscratch.h @ 17:dd9cdb856310

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Remove PKG-INFO from the because it is regenerated automatically for the sdist
author Franz Glasner <fzglas.hg@dom66.de>
date Thu, 18 Sep 2025 17:40:40 +0200
parents b50eed0cc0ef
children
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1 ///////////////////////////////////////////////////////////////////////
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2 // File: networkscratch.h
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3 // Description: Scratch space for Network layers that hides distinction
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4 // between float/int implementations.
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5 // Author: Ray Smith
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6 //
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7 // (C) Copyright 2014, Google Inc.
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8 // Licensed under the Apache License, Version 2.0 (the "License");
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9 // you may not use this file except in compliance with the License.
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10 // You may obtain a copy of the License at
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11 // http://www.apache.org/licenses/LICENSE-2.0
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12 // Unless required by applicable law or agreed to in writing, software
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13 // distributed under the License is distributed on an "AS IS" BASIS,
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14 // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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15 // See the License for the specific language governing permissions and
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16 // limitations under the License.
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17 ///////////////////////////////////////////////////////////////////////
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19 #ifndef TESSERACT_LSTM_NETWORKSCRATCH_H_
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20 #define TESSERACT_LSTM_NETWORKSCRATCH_H_
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21
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22 #include <mutex>
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23 #include "matrix.h"
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24 #include "networkio.h"
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26 namespace tesseract {
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27
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28 // Generic scratch space for network layers. Provides NetworkIO that can store
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29 // a complete set (over time) of intermediates, and vector<float>
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30 // scratch space that auto-frees after use. The aim here is to provide a set
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31 // of temporary buffers to network layers that can be reused between layers
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32 // and don't have to be reallocated on each call.
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33 class NetworkScratch {
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34 public:
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35 NetworkScratch() : int_mode_(false) {}
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36 ~NetworkScratch() = default;
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38 // Sets the network representation. If the representation is integer, then
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39 // default (integer) NetworkIOs are separated from the always-float variety.
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40 // This saves memory by having separate int-specific and float-specific
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41 // stacks. If the network representation is float, then all NetworkIOs go
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42 // to the float stack.
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43 void set_int_mode(bool int_mode) {
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44 int_mode_ = int_mode;
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45 }
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46
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47 // Class that acts like a NetworkIO (by having an implicit cast operator),
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48 // yet actually holds a pointer to NetworkIOs in the source NetworkScratch,
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49 // and knows how to unstack the borrowed pointers on destruction.
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50 class IO {
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51 public:
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52 // The NetworkIO should be sized after construction.
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53 IO(const NetworkIO &src, NetworkScratch *scratch)
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54 : int_mode_(scratch->int_mode_ && src.int_mode()), scratch_space_(scratch) {
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55 network_io_ =
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56 int_mode_ ? scratch_space_->int_stack_.Borrow() : scratch_space_->float_stack_.Borrow();
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57 }
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58 // Default constructor for arrays. Use one of the Resize functions
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59 // below to initialize and size.
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60 IO() : int_mode_(false), network_io_(nullptr), scratch_space_(nullptr) {}
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61
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62 ~IO() {
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63 if (scratch_space_ == nullptr) {
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64 ASSERT_HOST(network_io_ == nullptr);
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65 } else if (int_mode_) {
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66 scratch_space_->int_stack_.Return(network_io_);
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67 } else {
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68 scratch_space_->float_stack_.Return(network_io_);
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69 }
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70 }
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71 // Resizes the array (and stride), avoiding realloc if possible, to the
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72 // size from various size specs:
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73 // Same time size, given number of features.
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74 void Resize(const NetworkIO &src, int num_features, NetworkScratch *scratch) {
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75 if (scratch_space_ == nullptr) {
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76 int_mode_ = scratch->int_mode_ && src.int_mode();
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77 scratch_space_ = scratch;
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78 network_io_ =
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79 int_mode_ ? scratch_space_->int_stack_.Borrow() : scratch_space_->float_stack_.Borrow();
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80 }
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81 network_io_->Resize(src, num_features);
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82 }
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83 // Resizes to a specific size as a temp buffer. No batches, no y-dim.
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84 void Resize2d(bool int_mode, int width, int num_features, NetworkScratch *scratch) {
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85 if (scratch_space_ == nullptr) {
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86 int_mode_ = scratch->int_mode_ && int_mode;
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87 scratch_space_ = scratch;
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88 network_io_ =
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89 int_mode_ ? scratch_space_->int_stack_.Borrow() : scratch_space_->float_stack_.Borrow();
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90 }
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91 network_io_->Resize2d(int_mode, width, num_features);
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92 }
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93 // Resize forcing a float representation with the width of src and the given
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94 // number of features.
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95 void ResizeFloat(const NetworkIO &src, int num_features, NetworkScratch *scratch) {
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96 if (scratch_space_ == nullptr) {
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97 int_mode_ = false;
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98 scratch_space_ = scratch;
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99 network_io_ = scratch_space_->float_stack_.Borrow();
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100 }
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101 network_io_->ResizeFloat(src, num_features);
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102 }
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103
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104 // Returns a ref to a NetworkIO that enables *this to be treated as if
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105 // it were just a NetworkIO*.
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106 NetworkIO &operator*() {
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107 return *network_io_;
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108 }
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109 NetworkIO *operator->() {
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110 return network_io_;
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111 }
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112 operator NetworkIO *() {
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113 return network_io_;
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114 }
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115
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116 private:
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117 // True if this is from the always-float stack, otherwise the default stack.
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118 bool int_mode_;
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119 // The NetworkIO that we have borrowed from the scratch_space_.
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120 NetworkIO *network_io_;
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121 // The source scratch_space_. Borrowed pointer, used to free the
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122 // NetworkIO. Don't delete!
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123 NetworkScratch *scratch_space_;
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124 }; // class IO.
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125
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126 // Class that acts like a fixed array of float, yet actually uses space
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127 // from a vector<float> in the source NetworkScratch, and knows how
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128 // to unstack the borrowed vector on destruction.
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129 class FloatVec {
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130 public:
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131 // The array will have size elements in it, uninitialized.
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132 FloatVec(int size, NetworkScratch *scratch) : vec_(nullptr), scratch_space_(scratch) {
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133 Init(size, scratch);
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134 }
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135 // Default constructor is for arrays. Use Init to setup.
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136 FloatVec() : vec_(nullptr), data_(nullptr), scratch_space_(nullptr) {}
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137 ~FloatVec() {
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138 if (scratch_space_ != nullptr) {
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139 scratch_space_->vec_stack_.Return(vec_);
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140 }
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141 }
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142
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143 void Init(int /*size*/, int reserve, NetworkScratch *scratch) {
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144 if (scratch_space_ != nullptr && vec_ != nullptr) {
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145 scratch_space_->vec_stack_.Return(vec_);
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146 }
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147 scratch_space_ = scratch;
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148 vec_ = scratch_space_->vec_stack_.Borrow();
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149 // TODO: optimize.
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150 vec_->resize(reserve);
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151 data_ = &(*vec_)[0];
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152 }
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153
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154 void Init(int size, NetworkScratch *scratch) {
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155 Init(size, size, scratch);
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156 }
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157
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158 // Use the cast operator instead of operator[] so the FloatVec can be used
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159 // as a TFloat* argument to a function call.
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160 operator TFloat *() const {
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161 return data_;
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162 }
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163 TFloat *get() {
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164 return data_;
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165 }
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166
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167 private:
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168 // Vector borrowed from the scratch space. Use Return to free it.
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169 std::vector<TFloat> *vec_;
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170 // Short-cut pointer to the underlying array.
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171 TFloat *data_;
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172 // The source scratch_space_. Borrowed pointer, used to free the
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173 // vector. Don't delete!
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174 NetworkScratch *scratch_space_;
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175 }; // class FloatVec
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176
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177 // Class that acts like a 2-D array of TFloat, yet actually uses space
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178 // from the source NetworkScratch, and knows how to unstack the borrowed
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179 // array on destruction.
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180 class GradientStore {
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181 public:
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182 // Default constructor is for arrays. Use Init to setup.
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183 GradientStore() : array_(nullptr), scratch_space_(nullptr) {}
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184 ~GradientStore() {
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185 if (scratch_space_ != nullptr) {
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186 scratch_space_->array_stack_.Return(array_);
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187 }
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188 }
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189
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190 void Init(int size1, int size2, NetworkScratch *scratch) {
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191 if (scratch_space_ != nullptr && array_ != nullptr) {
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192 scratch_space_->array_stack_.Return(array_);
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193 }
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194 scratch_space_ = scratch;
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195 array_ = scratch_space_->array_stack_.Borrow();
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196 array_->Resize(size1, size2, 0.0);
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197 }
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198
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199 // Accessors to get to the underlying TransposedArray.
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200 TransposedArray *get() const {
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201 return array_;
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202 }
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203 const TransposedArray &operator*() const {
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204 return *array_;
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205 }
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206
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207 private:
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208 // Array borrowed from the scratch space. Use Return to free it.
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209 TransposedArray *array_;
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210 // The source scratch_space_. Borrowed pointer, used to free the
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211 // vector. Don't delete!
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212 NetworkScratch *scratch_space_;
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213 }; // class GradientStore
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214
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215 // Class that does the work of holding a stack of objects, a stack pointer
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216 // and a vector of in-use flags, so objects can be returned out of order.
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217 // It is safe to attempt to Borrow/Return in multiple threads.
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218 template <typename T>
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219 class Stack {
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220 public:
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221 Stack() = default;
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222
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223 ~Stack() {
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224 for (auto data : stack_) {
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225 delete data;
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226 }
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227 }
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228
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229 // Lends out the next free item, creating one if none available, sets
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230 // the used flags and increments the stack top.
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231 T *Borrow() {
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232 std::lock_guard<std::mutex> lock(mutex_);
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233 if (stack_top_ == stack_.size()) {
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234 stack_.push_back(new T);
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235 flags_.push_back(false);
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236 }
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237 flags_[stack_top_] = true;
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238 return stack_[stack_top_++];
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239 }
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240 // Takes back the given item, and marks it free. Item does not have to be
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241 // the most recently lent out, but free slots don't get re-used until the
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242 // blocking item is returned. The assumption is that there will only be
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243 // small, temporary variations from true stack use. (Determined by the order
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244 // of destructors within a local scope.)
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245 void Return(T *item) {
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246 std::lock_guard<std::mutex> lock(mutex_);
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247 // Linear search will do.
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248 int index = stack_top_;
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249 while (--index >= 0 && stack_[index] != item) {
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250 }
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251 if (index >= 0) {
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252 flags_[index] = false;
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253 }
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254 while (stack_top_ > 0 && !flags_[stack_top_ - 1]) {
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255 --stack_top_;
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256 }
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257 }
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258
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259 private:
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260 std::vector<T *> stack_;
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261 std::vector<bool> flags_;
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262 unsigned stack_top_ = 0;
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263 std::mutex mutex_;
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264 }; // class Stack.
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265
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266 private:
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267 // If true, the network weights are int8_t, if false, float.
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268 bool int_mode_;
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269 // Stacks of NetworkIO and vector<float>. Once allocated, they are not
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270 // deleted until the NetworkScratch is deleted.
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271 Stack<NetworkIO> int_stack_;
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272 Stack<NetworkIO> float_stack_;
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273 Stack<std::vector<TFloat>> vec_stack_;
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274 Stack<TransposedArray> array_stack_;
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275 };
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276
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277 } // namespace tesseract.
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278
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279 #endif // TESSERACT_LSTM_NETWORKSCRATCH_H_