Mercurial > ift6266

annotate demo/mlp_conv.c @ 623:d44c78c90669

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entered revisions for AMT and SVMs
author Yoshua Bengio <bengioy@iro.umontreal.ca>
date Sun, 09 Jan 2011 22:00:39 -0500
parents 269c39f55134
children
rev   line source
540
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1
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2 #include "AS3.h"
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3 #include <math.h>
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4
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5 typedef struct {
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6 int n,x,y;
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7 float *w, *b;
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8 int nonlin; // 0aucune,1sigm,2tanh,3softmax
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9 int maxpool; // 01
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10 } LAYER;
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11
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12 LAYER models[] = { {500,32,32,0,0,2,0},{62,1,1,0,0,3,0}, {1000,32,32,0,0,1,0},{1000,1,1,0,0,1,0},{1000,1,1,0,0,1,0},{62,1,1,0,0,1,0} };
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13 int mod_i[] = {0,2,6};
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14
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15 LAYER *L;
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16 int nl;
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17
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18 float *data, *o;
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19 #define BUF_SIZE 20000
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20
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21 static AS3_Val initparam(void* self, AS3_Val args) {
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22 AS3_Val tmp = AS3_Undefined();
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23 int il, len;
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24
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25 for (il=0; il < sizeof(models)/sizeof(LAYER); ++il) {
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26 tmp = AS3_Get(args, AS3_Int(2*il));
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27 len = AS3_IntValue(AS3_GetS(tmp, "length"));
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28 models[il].w = (float*) malloc(len);
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29 AS3_ByteArray_readBytes(models[il].w, tmp, len);
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30
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31 tmp = AS3_Get(args, AS3_Int(2*il+1));
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32 len = AS3_IntValue(AS3_GetS(tmp, "length"));
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33 models[il].b = (float*) malloc(len);
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34 AS3_ByteArray_readBytes(models[il].b, tmp, len);
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35 }
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36
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37 data = (float*) malloc(BUF_SIZE);
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38 o = (float*) malloc(BUF_SIZE);
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39
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40 return AS3_Int(0);
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41 }
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42
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43 static AS3_Val choosemodel(void* self, AS3_Val args) {
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44 int il;
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45
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46 AS3_ArrayValue( args, "IntType", &il );
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47
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48 L = models + mod_i[il];
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49 nl = mod_i[il+1] - mod_i[il];
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50
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51 return AS3_Int(0);
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52 }
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53
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54 static AS3_Val prediction(void* self, AS3_Val args) {
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55 AS3_Val in_arr = AS3_Undefined(), out_arr = AS3_Array(0);
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56 float *tmp, d, e;
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57 int i,j,k,l, n,x,y, newx,newy, il, dx,dy;
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58 LAYER *pL;
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59
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60 AS3_ArrayValue( args, "AS3ValType", &in_arr );
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61
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62 for(i=0; i < 1024; ++i)
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63 data[i] = AS3_IntValue(AS3_Get(in_arr, AS3_Int(4*i+1))) /255.0;
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64
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65 n = 1;
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66 x = 32;
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67 y = 32;
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68
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69 #define DATA(l,j,i) data[((l)*y + (j))*x + (i)]
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70 #define O(k,dy,dx) o[((k)*newy + (dy))*newx + (dx)]
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71 #define W(k,l,j,i) pL->w[(((k)*n + (l))*pL->y + (j))*pL->x + (i)]
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72
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73 for (il=0; il < nl; ++il) {
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74 flyield();
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75 pL = L+il;
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76 newx = x+1-pL->x;
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77 newy = y+1-pL->y;
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78
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79 for (dx=0; dx < newx; ++dx)
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80 for (dy=0; dy < newy; ++dy)
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81 for (k=0; k < pL->n; ++k) {
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82 d = pL->b[k];
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83 for (l=0; l < n; ++l)
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84 for(j=0; j < pL->y; ++j)
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85 for(i=0; i < pL->x; ++i)
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86 d += DATA(l,j+dy,i+dx)*W(k,l,j,i);
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87 O(k,dy,dx) = d;
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88 }
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89
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90 if(pL->maxpool) {
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91 for (k=0; k < pL->n; ++k)
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92 for (dx=0; dx < newx; dx+=2)
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93 for (dy=0; dy < newy; dy+=2) {
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94 d=O(k,dy,dx);
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95 e=O(k,dy,dx+1); if(e>d) d=e;
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96 e=O(k,dy+1,dx); if(e>d) d=e;
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97 e=O(k,dy+1,dx+1); if(e>d) d=e;
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98 O(k,dy/2,dx/2)=d;
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99 }
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100 newx /= 2;
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101 newy /= 2;
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102 }
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103
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104 for (dx=0; dx < newx; ++dx)
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105 for (dy=0; dy < newy; ++dy) {
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106 e = 0;
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107 for (k=0; k < pL->n; ++k) {
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108 d = O(k,dy,dx);
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109 if(pL->nonlin==1) d=1.0/(1.0 + exp(-d));
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110 else if(pL->nonlin==2) d=tanh(d);
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111 else if(pL->nonlin==3) { d=exp(d); e += d; }
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112 O(k,dy,dx) = d;
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113 }
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114 if(pL->nonlin==3 && e)
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115 for (k=0; k < pL->n; ++k)
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116 O(k,dy,dx) /= e;
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117 }
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118
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119 tmp = data;
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120 data = o;
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121 o = tmp;
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122
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123 x = newx;
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124 y = newy;
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125 n = pL->n;
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126 }
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127
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128 for(i=0; i < n*x*y; ++i)
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129 AS3_Set(out_arr, AS3_Int(i), AS3_Number(data[i]));
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130
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131 return out_arr;
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132 }
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133
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134 int main() {
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135 AS3_Val initparamMethod = AS3_Function( NULL, initparam );
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136 AS3_Val choosemodelMethod = AS3_Function( NULL, choosemodel );
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137 AS3_Val predictionMethod = AS3_FunctionAsync( NULL, prediction );
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138
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139 AS3_Val result = AS3_Object( "initparam: AS3ValType, choosemodel: AS3ValType, prediction: AS3ValType", initparamMethod, choosemodelMethod, predictionMethod );
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140
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141 AS3_Release( initparamMethod );
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142 AS3_Release( choosemodelMethod );
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143 AS3_Release( predictionMethod );
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144
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145 AS3_LibInit( result );
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146
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147 return 0;
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148 }