István Ketykó ketyi

Nvidia Repo Setup

NVIDIA_GPGKEY_SUM=d1be581509378368edeec8c1eb2958702feedf3bc3d17011adbf24efacce4ab5 && \
NVIDIA_GPGKEY_FPR=ae09fe4bbd223a84b2ccfce3f60f4b3d7fa2af80 && \
apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86_64/7fa2af80.pub && \
apt-key adv --export --no-emit-version -a $NVIDIA_GPGKEY_FPR | tail -n +2 > cudasign.pub && \
echo "$NVIDIA_GPGKEY_SUM  cudasign.pub" | sha256sum -c --strict - && rm cudasign.pub && \
echo "deb http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86_64 /" > /etc/apt/sources.list.d/cuda.list

Install mosquitto with websockets

This is a guide how to install mosquitto on Ubuntu with websockets enabled.

It is more or less the same as explained in the article "Six Steps to install mosquitto 1.4.2 with websockets on debian whezy" http://www.xappsoftware.com/wordpress/2015/05/18/six-steps-to-install-mosquitto-1-4-2-with-websockets-on-debian-wheezy/comment-page-1/

Exceptions:

mosquitto version 1.4.10 is used.

	import tensorflow as tf
	import numpy as np


	def gaussian_noise_layer(input_layer, std):
	noise = tf.random_normal(shape=tf.shape(input_layer), mean=0.0, stddev=std, dtype=tf.float32)
	return input_layer + noise


	inp = tf.placeholder(tf.float32, shape=[None, 8], name='input')


	from keras import backend as K, initializers, regularizers, constraints
	from keras.engine.topology import Layer


	def dot_product(x, kernel):
	"""
	Wrapper for dot product operation, in order to be compatible with both
	Theano and Tensorflow
	Args:

	"""
	Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
	BSD License
	"""
	import numpy as np

	# data I/O
	data = open('input.txt', 'r').read() # should be simple plain text file
	chars = list(set(data))
	data_size, vocab_size = len(data), len(chars)