oraclewalid

trait Tag[+TAG]{}
type Intersection[+TYPE,+TAG] =  TYPE with Tag[TAG]
type Intersection3[+TYPE, +TAG1, +TAG2] =  TYPE with Tag[TAG1] with Tag[TAG2]
type ::[+TYPE,+TAG] = Intersection[TYPE,TAG]

implicit class Tagger[TYPE](val t: TYPE) extends AnyVal {
  def taggedWith[U]: TYPE :: U = t.asInstanceOf[TYPE :: U]
  def ::[U]: TYPE :: U = t.asInstanceOf[TYPE :: U]

}

oraclewalid

Keybase proof

I hereby claim:

• I am oraclewalid on github.
• I am walidchergui (https://keybase.io/walidchergui) on keybase.
• I have a public key ASDBlORDstuDQRJAFTwF9Zos9VY0slc67nAKjnRNBmRCGwo

To claim this, I am signing this object:

oraclewalid

# put the file in /etc/systemd/user or /etc/systemd/system with name myapp.service
# then you can start the application with : 
#      systemctl start myapp.service
#to see the logs : journalctl -u myapp.service
[Unit]
Description=myapp
After=network.target

[Service]
EnvironmentFile=/etc/myapp/env.prop

oraclewalid

import org.slf4j.LoggerFactory

/**
  * A wrapper class to make Slf4j more Scala friendly
  * with lazy evaluation of parameters
  *
  * use:
  * val logger = LoggerFactory.getLogger(this.getClass)
  * logger.info("Hello log  with parameter : {}", parameter)
  *

oraclewalid

public static void main(String[] args) throws Exception {
        
        int outputNum = 10;
        int batchSize = 128;
        int iterations = 1;
        int seed = 123;

        CifarDataSetIterator cifarTrain = new CifarDataSetIterator(batchSize, CifarLoader.NUM_TRAIN_IMAGES, true);

        MultiLayerConfiguration.Builder builder = new NeuralNetConfiguration.Builder()

oraclewalid

import numpy as np
from lasagne.nonlinearities import softmax

from lasagne import layers
from lasagne.updates import nesterov_momentum
from nolearn.lasagne import NeuralNet

N = 1000

def load_dataset():