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comparison mupdf-source/thirdparty/tesseract/src/lstm/fullyconnected.h @ 3:2c135c81b16c

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MERGE: upstream PyMuPDF 1.26.4 with MuPDF 1.26.7
author Franz Glasner <fzglas.hg@dom66.de>
date Mon, 15 Sep 2025 11:44:09 +0200
parents b50eed0cc0ef
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0:6015a75abc2d 3:2c135c81b16c
1 ///////////////////////////////////////////////////////////////////////
2 // File: fullyconnected.h
3 // Description: Simple feed-forward layer with various non-linearities.
4 // Author: Ray Smith
5 //
6 // (C) Copyright 2014, Google Inc.
7 // Licensed under the Apache License, Version 2.0 (the "License");
8 // you may not use this file except in compliance with the License.
9 // You may obtain a copy of the License at
10 // http://www.apache.org/licenses/LICENSE-2.0
11 // Unless required by applicable law or agreed to in writing, software
12 // distributed under the License is distributed on an "AS IS" BASIS,
13 // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 // See the License for the specific language governing permissions and
15 // limitations under the License.
16 ///////////////////////////////////////////////////////////////////////
17
18 #ifndef TESSERACT_LSTM_FULLYCONNECTED_H_
19 #define TESSERACT_LSTM_FULLYCONNECTED_H_
20
21 #include "network.h"
22 #include "networkscratch.h"
23 #include "tesstypes.h"
24
25 namespace tesseract {
26
27 // C++ Implementation of the Softmax (output) class from lstm.py.
28 class FullyConnected : public Network {
29 public:
30 TESS_API
31 FullyConnected(const std::string &name, int ni, int no, NetworkType type);
32 ~FullyConnected() override = default;
33
34 // Returns the shape output from the network given an input shape (which may
35 // be partially unknown ie zero).
36 StaticShape OutputShape(const StaticShape &input_shape) const override;
37
38 std::string spec() const override {
39 std::string spec;
40 if (type_ == NT_TANH) {
41 spec += "Ft" + std::to_string(no_);
42 } else if (type_ == NT_LOGISTIC) {
43 spec += "Fs" + std::to_string(no_);
44 } else if (type_ == NT_RELU) {
45 spec += "Fr" + std::to_string(no_);
46 } else if (type_ == NT_LINEAR) {
47 spec += "Fl" + std::to_string(no_);
48 } else if (type_ == NT_POSCLIP) {
49 spec += "Fp" + std::to_string(no_);
50 } else if (type_ == NT_SYMCLIP) {
51 spec += "Fn" + std::to_string(no_);
52 } else if (type_ == NT_SOFTMAX) {
53 spec += "Fc" + std::to_string(no_);
54 } else {
55 spec += "Fm" + std::to_string(no_);
56 }
57 return spec;
58 }
59
60 // Changes the type to the given type. Used to commute a softmax to a
61 // non-output type for adding on other networks.
62 void ChangeType(NetworkType type) {
63 type_ = type;
64 }
65
66 // Suspends/Enables training by setting the training_ flag. Serialize and
67 // DeSerialize only operate on the run-time data if state is false.
68 void SetEnableTraining(TrainingState state) override;
69
70 // Sets up the network for training. Initializes weights using weights of
71 // scale `range` picked according to the random number generator `randomizer`.
72 int InitWeights(float range, TRand *randomizer) override;
73 // Recursively searches the network for softmaxes with old_no outputs,
74 // and remaps their outputs according to code_map. See network.h for details.
75 int RemapOutputs(int old_no, const std::vector<int> &code_map) override;
76
77 // Converts a float network to an int network.
78 void ConvertToInt() override;
79
80 // Provides debug output on the weights.
81 void DebugWeights() override;
82
83 // Writes to the given file. Returns false in case of error.
84 bool Serialize(TFile *fp) const override;
85 // Reads from the given file. Returns false in case of error.
86 bool DeSerialize(TFile *fp) override;
87
88 // Runs forward propagation of activations on the input line.
89 // See Network for a detailed discussion of the arguments.
90 void Forward(bool debug, const NetworkIO &input, const TransposedArray *input_transpose,
91 NetworkScratch *scratch, NetworkIO *output) override;
92 // Components of Forward so FullyConnected can be reused inside LSTM.
93 void SetupForward(const NetworkIO &input, const TransposedArray *input_transpose);
94 void ForwardTimeStep(int t, TFloat *output_line);
95 void ForwardTimeStep(const TFloat *d_input, int t, TFloat *output_line);
96 void ForwardTimeStep(const int8_t *i_input, int t, TFloat *output_line);
97
98 // Runs backward propagation of errors on the deltas line.
99 // See Network for a detailed discussion of the arguments.
100 bool Backward(bool debug, const NetworkIO &fwd_deltas, NetworkScratch *scratch,
101 NetworkIO *back_deltas) override;
102 // Components of Backward so FullyConnected can be reused inside LSTM.
103 void BackwardTimeStep(const NetworkIO &fwd_deltas, int t, TFloat *curr_errors,
104 TransposedArray *errors_t, TFloat *backprop);
105 void FinishBackward(const TransposedArray &errors_t);
106
107 // Updates the weights using the given learning rate, momentum and adam_beta.
108 // num_samples is used in the adam computation iff use_adam_ is true.
109 void Update(float learning_rate, float momentum, float adam_beta, int num_samples) override;
110 // Sums the products of weight updates in *this and other, splitting into
111 // positive (same direction) in *same and negative (different direction) in
112 // *changed.
113 void CountAlternators(const Network &other, TFloat *same, TFloat *changed) const override;
114
115 protected:
116 // Weight arrays of size [no, ni + 1].
117 WeightMatrix weights_;
118 // Transposed copy of input used during training of size [ni, width].
119 TransposedArray source_t_;
120 // Pointer to transposed input stored elsewhere. If not null, this is used
121 // in preference to calculating the transpose and storing it in source_t_.
122 const TransposedArray *external_source_;
123 // Activations from forward pass of size [width, no].
124 NetworkIO acts_;
125 // Memory of the integer mode input to forward as softmax always outputs
126 // float, so the information is otherwise lost.
127 bool int_mode_;
128 };
129
130 } // namespace tesseract.
131
132 #endif // TESSERACT_LSTM_FULLYCONNECTED_H_