andrewssobral

# https://doc.ubuntu-fr.org/wakeonlan

# check if your target pc is wake-on-lan enabled:
sudo ethtool enp8s0  | egrep "^[[:blank:]]*Wake-on: (g|d)"
# you should have:
# Wake-on: g

# get target pc mac address
ifconfig enp8s0

andrewssobral

---

YouTube Channel https://www.youtube.com/c/jerrylokjianming

---

How to Crack Sublime Text 3.2.2 Build 3211 with Hex Editor (Windows | Without License) ↓

1. Download & Install Sublime Text 3.2.2 Build 3211
2. Visit https://hexed.it/

andrewssobral

sudo apt install xorg-dev libssl-dev qtbase5-dev libgdk-pixbuf2.0-dev libnotify-dev qttools5-dev-tools qttools5-dev
git clone https://github.com/symless/synergy-core.git
cd synergy-core
mkdir build
cd build
cmake ..
make
# https://github.com/symless/synergy-core/wiki/Command-Line
# ./bin/synergyc $SYNERGY_SERVER_IP

andrewssobral

import os
import multiprocessing

import torch
import torch.nn.functional as F
import torchmetrics
import pytorch_lightning as pl

from argparse import ArgumentParser
from torch import nn

andrewssobral

# https://github.com/ShigekiKarita/pytorch-distributed-slurm-example/blob/master/main_distributed.py
# lauch 2 gpus x 2 nodes (= 4 gpus)
# srun -N2 -p gpu --gres gpu:2 python main_distributed.py --dist-backend nccl --multiprocessing-distributed --dist-file dist_file
import argparse
import os
import random
import shutil
import time
import warnings
import sys

andrewssobral

from __future__ import print_function

import argparse
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim

from torchvision import datasets, transforms

andrewssobral

import tensorflow as tf
import numpy as np
import time

from tensorflow.contrib.rnn import BasicLSTMCell

# https://github.com/tensorflow/tensorflow/issues/24828
try:
    from tensorflow.compat.v1 import ConfigProto
    from tensorflow.compat.v1 import InteractiveSession

andrewssobral

import os, json, shutil

import keras
from keras.callbacks import TensorBoard
from keras.datasets import cifar10
from keras.preprocessing.image import ImageDataGenerator
from keras.models import Sequential
from keras.layers import Dense, Dropout, Activation, Flatten
from keras.layers import Conv2D, MaxPooling2D

andrewssobral

'''Trains a simple convnet on the MNIST dataset.

Gets to 99.25% test accuracy after 12 epochs
(there is still a lot of margin for parameter tuning).
16 seconds per epoch on a GRID K520 GPU.
'''

import keras
from keras.datasets import mnist
from keras.models import Sequential

andrewssobral

"""
Created on Sat Sep 28 00:47:38 2019
@author: Kenan Kilictepe (Entegral / www.entegral.com.tr)
"""

import numba
from numba import cuda
import numpy as np
from pdb import set_trace