ipbastola

Safest way to clean up boot partition - Ubuntu 14.04LTS-x64, Ubuntu 16.04LTS-x64

Reference

Case I: if /boot is not 100% full and apt is working

1. Check the current kernel version

$ uname -r 

numberwhun

Taken from:  https://hackerlists.com/hacking-sites/

22 Hacking Sites, CTFs and Wargames To Practice Your Hacking Skills
InfoSec skills are in such high demand right now. As the world continues to turn everything into an app and connect even the most basic devices to the internet, the demand is only going to grow, so it’s no surprise everyone wants to learn hacking these days.


However, almost every day I come across a forum post where someone is asking where they should begin to learn hacking or how to practice hacking. I’ve compiled this list of some of the best hacking sites to hopefully be a valuable resource for those wondering how they can build and practice their hacking skill set. I hope you find this list helpful, and if you know of any other quality hacking sites, please let me know in the comments, so I can add them to the list.

1. CTF365 https://ctf365.com/

evantoli

Configure Git to use a proxy

In Brief

You may need to configure a proxy server if you're having trouble cloning or fetching from a remote repository or getting an error like unable to access '...' Couldn't resolve host '...'.

Consider something like:

cdmwebs

Friendly URLs

By default, Rails applications build URLs based on the primary key -- the id column from the database. Imagine we have a Person model and associated controller. We have a person record for Bob Martin that has id number 6. The URL for his show page would be:

/people/6

But, for aesthetic or SEO purposes, we want Bob's name in the URL. The last segment, the 6 here, is called the "slug". Let's look at a few ways to implement better slugs.

iangreenleaf

Rails naming conventions

General Ruby conventions

Class names are CamelCase.

Methods and variables are snake_case.

Methods with a ? suffix will return a boolean.

omoindrot

"""
Example TensorFlow script for finetuning a VGG model on your own data.
Uses tf.contrib.data module which is in release v1.2
Based on PyTorch example from Justin Johnson
(https://gist.github.com/jcjohnson/6e41e8512c17eae5da50aebef3378a4c)

Required packages: tensorflow (v1.2)
Download the weights trained on ImageNet for VGG:
```
wget http://download.tensorflow.org/models/vgg_16_2016_08_28.tar.gz

carlthome

Fweeb

Rendering in Blender on a machine with multiple GPUs

So here's the premise: For scenes that take around a minute or less to render, performance is actually worse if you render on all of the cards with a single instance of Blender. This is because (AFAIK) there's a bit of additional time necessary to collect the render results from each card and stitch them together. That time is a fixed short duration, so it's negligible on larger/longer render jobs. However, on shorter render jobs, the 'stitch time' has a much more significant impact.

I ran into this with a machine I render on that has 4 Quadro K6000s in it. To render animations, I ended up writing a few little scripts to facilitate launching 4 separate instances of Blender, each one tied to one GPU. Overall rendertime was much shorter with that setup than one instance of Blender using all 4 GPUs.

The setup works basically like this... I have a the following Python script (it can be anywhere on your hard drive, so long as you remember the path to it).

AdilsonFuxe

If your pods are showing ErrImagePull, ErrImageNeverPull, or ImagePullBackOff errors after running kubectl apply, the simplest solution is to provide an imagePullPolicy to the pod.

First, run kubectl delete -f infra/k8s/

Then, update your pod manifest:

spec:
  containers:
    - name: posts
      image: cygnet/posts:0.0.1

jubjamie

import tensorflow as tf
from tensorflow.python.platform import gfile
with tf.Session() as sess:
    model_filename ='PATH_TO_PB.pb'
    with gfile.FastGFile(model_filename, 'rb') as f:
        graph_def = tf.GraphDef()
        graph_def.ParseFromString(f.read())
        g_in = tf.import_graph_def(graph_def)
LOGDIR='/logs/tests/1/'
train_writer = tf.summary.FileWriter(LOGDIR)