jaassoon’s gists

jaassoon / meraki_strongswan_notes.md

Created December 1, 2018 11:20 — forked from psanford/meraki_strongswan_notes.md

connect to meraki client vpn from strongswan (ubuntu 16.04 edition)

These are my notes for connecting to a meraki client vpn from ubuntu 16.04. This configuration assumes you are using a psk for the ipsec auth.

Install the following packages:

apt-get install -y strongswan xl2tpd

Configure strong swan

jaassoon / train_on_batch_with_tensorboard.py

Created November 12, 2018 12:55 — forked from erenon/train_on_batch_with_tensorboard.py

	# This example shows how to use keras TensorBoard callback
	# with model.train_on_batch

	import tensorflow.keras as keras

	# Setup the model
	model = keras.models.Sequential()
	model.add(...) # Add your layers
	model.compile(...) # Compile as usual

jaassoon / demo.py

Created November 12, 2018 12:51 — forked from joelthchao/demo.py

Keras uses TensorBoard Callback with train_on_batch

	import numpy as np
	import tensorflow as tf
	from keras.callbacks import TensorBoard
	from keras.layers import Input, Dense
	from keras.models import Model


	def write_log(callback, names, logs, batch_no):
	for name, value in zip(names, logs):
	summary = tf.Summary()

jaassoon / cuda-with-cudnn.sh

Created July 1, 2018 01:43

	# cuda.sh
	# check if GPU ready
	lspci \| grep -i nvidia
	# If NVIDIA driver was installed via the *.run file:
	# sudo nvidia-uninstall
	yum install -y gcc gcc-c++ kernel-devel kernel-headers
	yum install -y libXmu libXmu-devel mesa-libGLU mesa-libGLU-devel \
	libX11-common.noarch libX11-devel libX11 \
	libXi libXi-devel
	yum -y update

jaassoon / buildcv2.sh

Created June 30, 2018 07:02

	# buildcv2.sh
	#!/bin/bash
	yum -y install gcc gcc-c++ freetype-devel glib2-devel cairo-devel libtool
	basePath=/mnt/Data/jason
	python36Path=/mnt/Data/jason/env36

	#install colm
	cd {basePath}/jp-ocr/3rdparty/{colm}
	./autogen.sh
	./configure

jaassoon / squeezeNet-by-deeplearnjs.html

Last active January 16, 2018 12:20

squeezeNet-by-deeplearnjs

	<!DOCTYPE html>
	<html>
	<script src="https://cdn.jsdelivr.net/npm/deeplearn"></script>
	<script src='https://unpkg.com/deeplearn-squeezenet'></script>
	<div id='target' ondrop='dropit(event);' ondragover='dragoverit(event);'>
	Drag another image onto this image to predict (make sure browser window is focused).
	<br><br>
	If you have cross origin problems, download the image to your computer
	first, then drag it here.
	<div id='img'><img id='cat' src='https://storage.googleapis.com/learnjs-data/images/cat.jpeg' crossorigin></div>

jaassoon / docker_ubuntu17.1_tensorflow_build_from_src.Dockerfile

Last active July 20, 2017 14:42

build tensorflow 1.2.1 from source in ubuntu17.1 by bazel

	FROM ubuntu:17.10
	ENV container docker
	WORKDIR /opt

	# ##### Configure the build for configuration.
	ENV TF_NEED_GCP 0
	ENV TF_NEED_HDFS 0
	ENV TF_ENABLE_XLA 0
	ENV TF_NEED_CUDA 0
	ENV TF_NEED_OPENCL 0

jaassoon / tf_serving.sh

Created July 15, 2017 00:04 — forked from jarutis/tf_serving.sh

Install Tensorflow Serving on Centos 7 (CPU)

	sudo su

	# Java
	yum -y install java-1.8.0-openjdk-devel

	# Build Esentials (minimal)
	yum -y install gcc gcc-c++ kernel-devel make automake autoconf swig git unzip libtool binutils

	# Extra Packages for Enterprise Linux (EPEL) (for pip, zeromq3)
	yum -y install epel-release