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const T& A::méthode() { | |
T t; | |
return t; | |
} | |
int main() { | |
A a; | |
T h = a.méthode(); // On récupère la référence const | |
h.getValue(); // On suppose que le type T a une méthode getValue(), | |
// erreur ou pas ? |
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;;;;;;;;;;;;;;;;;;;;;;;;; VERSION COMMENTEE ;;;;;;;;;;;;;;;;;;;;;;;;; | |
; Fonction de service permettant d'afficher le chemin menant à un état 'etat' | |
; | |
; Entrées : | |
; 'etat' : l'état final | |
; 'peres' : le tableau des pères : ce tableau contient des couples (fils;père) permettant de retrouver le père de chaque noeud | |
; 'racine' : la racine de l'arbre | |
; Sortie : affiche le chemin menant à l'état demandé |
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import numpy as np | |
import tensorlayer as tl | |
import tensorflow as tf | |
def cnn_network(inputs): | |
# =============================== GAME RULES =============================== | |
# 1. Only 2 Layers should be in the networks, no more, no less ! | |
# | |
# 2. You are only allowed to use convolution layers (No Dense, No Reshape, No Whatever else) | |
# |
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library(MASS) | |
distXY <- function(X, Y, M=diag(dim(X)[2])) | |
{ | |
if (!is.matrix(X)) | |
{ | |
X <- matrix(X, nrow=1) | |
} | |
if (!is.matrix(Y)) | |
{ |
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model Baril | |
uses "mmxprs"; !gain access to the Xpress-Optimizer solver | |
!sample declarations section | |
declarations | |
! ... | |
Objective:linctr | |
Items=1..3 ! Index range for items | |
VALUE: array(Items) of real ! Value of items | |
WEIGHT1: array(Items) of real ! Weight of items |