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@AyoubOuddah
AyoubOuddah / Fashion_MNST.py
Last active November 26, 2019 17:30
CNN on Fashion-MNIST dataset with Pytorch
import argparse
import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision.transforms as transforms
import torchvision.datasets as datasets
import torch.optim
import torch.utils.data
CUDA = False
@AyoubOuddah
AyoubOuddah / Fashion_MNST.py
Created November 26, 2019 16:26
CNN on Fashion-MNIST dataset with Pytorch
import argparse
import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision.transforms as transforms
import torchvision.datasets as datasets
import torch.optim
import torch.utils.data
CUDA = False
Algorithme program4
var
posReineX, posReineY : entier;
posInitialDiag1, posInitialDiag2 : entier; // les position X initale du chaque diagonale
echiquier = tableu [8,8] : entier;
i , j : entier;
debut
ecrire("entrer la position initial de la reine :");
lire(posReineX, posReineY);
posInitialDiag1 <-- posReineX - (posReineY - 1);