[286] | 1 | // This file is a part of Framsticks SDK. http://www.framsticks.com/ |
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[972] | 2 | // Copyright (C) 1999-2020 Maciej Komosinski and Szymon Ulatowski. |
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[286] | 3 | // See LICENSE.txt for details. |
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[135] | 4 | |
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[382] | 5 | #include <common/virtfile/stdiofile.h> |
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[135] | 6 | #include <frams/util/sstringutils.h> |
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[145] | 7 | #include <frams/genetics/preconfigured.h> |
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[135] | 8 | #include <frams/model/model.h> |
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[391] | 9 | #include <common/loggers/loggertostdout.h> |
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[135] | 10 | #include <frams/canvas/nn_layout_model.h> |
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| 11 | |
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| 12 | #include <algorithm> |
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| 13 | |
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| 14 | /** |
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| 15 | @file |
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| 16 | Sample code: Neuron layout tester |
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| 17 | |
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[408] | 18 | Hint: Use loader_test to extract genotypes from Framsticks *.gen files: |
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[135] | 19 | loader_test "data/walking.gen" "Walking Lizard" | neuro_layout_test - |
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| 20 | */ |
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| 21 | |
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| 22 | // stl is fun? ;-) ForwardIterator implementation for element coordinates (required by min_element/max_element) |
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[972] | 23 | template <int MEMBER> struct NNIter : public std::iterator<std::forward_iterator_tag, int> //MEMBER: 0..3=x/y/w/h |
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[135] | 24 | { |
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[972] | 25 | NNLayoutState *nn; int index; |
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| 26 | NNIter() {} |
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| 27 | NNIter(NNLayoutState *_nn, int _index) :nn(_nn), index(_index) {} |
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| 28 | int operator*() { return nn->GetXYWH(index)[MEMBER]; } |
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| 29 | NNIter& operator++() { index++; return *this; } |
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| 30 | bool operator!=(const NNIter& it) { return index != it.index; } |
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| 31 | bool operator==(const NNIter& it) { return index == it.index; } |
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[135] | 32 | |
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[972] | 33 | static NNIter begin(NNLayoutState *_nn) { return NNIter(_nn, 0); } |
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| 34 | static NNIter end(NNLayoutState *_nn) { return NNIter(_nn, _nn->GetElements()); } |
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[135] | 35 | }; |
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| 36 | |
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| 37 | class Screen |
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| 38 | { |
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[972] | 39 | int min_x, max_x, min_y, max_y, scale_x, scale_y; |
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| 40 | int rows, columns; |
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| 41 | char* screen; |
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[135] | 42 | |
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| 43 | public: |
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| 44 | |
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[972] | 45 | Screen(int _min_x, int _max_x, int _min_y, int _max_y, int _scale_x, int _scale_y) |
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| 46 | :min_x(_min_x), max_x(_max_x), min_y(_min_y), max_y(_max_y), scale_x(_scale_x), scale_y(_scale_y) |
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| 47 | { |
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| 48 | columns = (max_x - min_x + scale_x - 1) / scale_x; |
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| 49 | rows = (max_y - min_y + scale_y - 1) / scale_y; |
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| 50 | screen = new char[rows * columns]; |
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| 51 | memset(screen, ' ', rows * columns); |
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| 52 | } |
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[135] | 53 | |
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[972] | 54 | ~Screen() |
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| 55 | { |
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[135] | 56 | delete[] screen; |
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[972] | 57 | } |
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[135] | 58 | |
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[972] | 59 | void put(int x, int y, const char *str) |
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[135] | 60 | { |
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[972] | 61 | x = (x - min_x) / scale_x; |
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| 62 | y = (y - min_y) / scale_y; |
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| 63 | if (x < 0) return; |
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| 64 | if (y < 0) return; |
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| 65 | if (y >= rows) return; |
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| 66 | for (; *str; str++, x++) |
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[135] | 67 | { |
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[972] | 68 | if (x >= columns) return; |
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| 69 | screen[columns * y + x] = *str; |
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[135] | 70 | } |
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| 71 | } |
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| 72 | |
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[972] | 73 | void print() |
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[135] | 74 | { |
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[972] | 75 | for (int y = 0; y < rows; y++) |
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[135] | 76 | { |
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[972] | 77 | fwrite(&screen[columns * y], 1, columns, stdout); |
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| 78 | printf("\n"); |
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[135] | 79 | } |
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| 80 | } |
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| 81 | }; |
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| 82 | |
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[972] | 83 | int main(int argc, char*argv[]) |
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[135] | 84 | { |
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[972] | 85 | LoggerToStdout messages_to_stdout(LoggerBase::Enable); |
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| 86 | PreconfiguredGenetics genetics; |
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[145] | 87 | |
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[972] | 88 | if (argc <= 1) |
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[135] | 89 | { |
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| 90 | puts("Parameters:\n" |
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[972] | 91 | " 1. Genotype (or - character indicating the genotype will be read from stdin)\n" |
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| 92 | " 2. (Optional) layout type (the only useful layout is 2, which is the default, see nn_simple_layout.cpp"); |
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| 93 | return 10; |
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[135] | 94 | } |
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[972] | 95 | SString gen(argv[1]); |
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| 96 | if (!strcmp(gen.c_str(), "-")) |
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[135] | 97 | { |
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[972] | 98 | gen = 0; |
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| 99 | StdioFILEDontClose in(stdin); |
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| 100 | loadSString(&in, gen); |
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[135] | 101 | } |
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[972] | 102 | int layout_type = 2; |
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| 103 | if (argc > 2) layout_type = atol(argv[2]); |
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| 104 | Geno g(gen); |
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| 105 | if (!g.isValid()) { puts("invalid genotype"); return 5; } |
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| 106 | Model m(g, Model::SHAPE_UNKNOWN); |
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| 107 | if (!m.getNeuroCount()) { puts("no neural network"); return 1; } |
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| 108 | printf("%d neurons,", m.getNeuroCount()); |
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[135] | 109 | |
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[972] | 110 | NNLayoutState_Model nn_layout(&m); |
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| 111 | struct NNLayoutFunction &nnfun = nn_layout_functions[layout_type]; |
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| 112 | printf(" using layout type=%d (%s)\n", layout_type, nnfun.name); |
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| 113 | nnfun.doLayout(&nn_layout); |
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[135] | 114 | |
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[972] | 115 | for (int i = 0; i < nn_layout.GetElements(); i++) |
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[135] | 116 | { |
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[972] | 117 | int *xywh = nn_layout.GetXYWH(i); |
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| 118 | printf("#%-3d %s\t%d,%d\t%dx%d\n", i, m.getNeuro(i)->getClassName().c_str(), |
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| 119 | xywh[0], xywh[1], xywh[2], xywh[3]); |
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[135] | 120 | } |
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| 121 | |
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[972] | 122 | Screen screen(*std::min_element(NNIter<0>::begin(&nn_layout), NNIter<0>::end(&nn_layout)) - 30, |
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| 123 | *std::max_element(NNIter<0>::begin(&nn_layout), NNIter<0>::end(&nn_layout)) + 70, |
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| 124 | *std::min_element(NNIter<1>::begin(&nn_layout), NNIter<1>::end(&nn_layout)), |
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| 125 | *std::max_element(NNIter<1>::begin(&nn_layout), NNIter<1>::end(&nn_layout)) + 30, |
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| 126 | 10, 35); |
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[135] | 127 | |
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[972] | 128 | printf("===========================================\n"); |
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| 129 | for (int i = 0; i < nn_layout.GetElements(); i++) |
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[135] | 130 | { |
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[972] | 131 | int *xywh = nn_layout.GetXYWH(i); |
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| 132 | SString label = SString::sprintf("%d:%s", i, m.getNeuro(i)->getClassName().c_str()); |
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| 133 | screen.put(xywh[0], xywh[1], label.c_str()); |
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[135] | 134 | } |
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[972] | 135 | screen.print(); |
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| 136 | printf("===========================================\n"); |
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[135] | 137 | |
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| 138 | } |
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