luthfianto

import tensorflow as tf
import numpy as np
import keras
import keras.backend as K
from functools import reduce
from keras.models import Model
import keras.callbacks as cbks
from keras.applications import ResNet50
from keras.layers import Conv2D
import threading

luthfianto

from keras.layers.core import Layer  
from keras import initializers, regularizers, constraints  
from keras import backend as K

class Attention(Layer):
    def __init__(self,
                 kernel_regularizer=None, bias_regularizer=None,
                 kernel_constraint=None, bias_constraint=None,
                 use_bias=True, **kwargs):
        """

luthfianto

"""
A keras attention layer that wraps RNN layers.

Based on tensorflows [attention_decoder](https://github.com/tensorflow/tensorflow/blob/c8a45a8e236776bed1d14fd71f3b6755bd63cc58/tensorflow/python/ops/seq2seq.py#L506) 
and [Grammar as a Foreign Language](https://arxiv.org/abs/1412.7449).

date: 20161101
author: wassname
url: https://gist.github.com/wassname/5292f95000e409e239b9dc973295327a
"""

luthfianto

"""A stripped-down MLP example, using Theano.

Based on the tutorial here: http://deeplearning.net/tutorial/mlp.html

This example trims away some complexities, and makes it easier to see how Theano works.

Design changes:

* Model compiled in a distinct function, so that symbolic variables are not in run-time scope.
* No classes. Network shown by chained function calls.

luthfianto

package quickcheck

import common._

import org.scalacheck._
import Arbitrary._
import Gen._
import Prop._
import Math._

luthfianto

# 1. Delete all existing rules
iptables -F

# 2. Set default chain policies
iptables -P INPUT DROP
iptables -P FORWARD DROP
iptables -P OUTPUT DROP

# 4. Allow ALL incoming SSH
iptables -A INPUT -i eth0 -p tcp --dport 22 -m state --state NEW,ESTABLISHED -j ACCEPT