Largely based on the Tensorflow 1.6 gist, and Tensorflow 1.7 gist for xcode, this should hopefully simplify things a bit.
- NVIDIA Web-Drivers 387.10.10.10.30.103 for 10.13.4
- CUDA-Drivers 387.178
- CUDA 9.1 Toolkit
# make sure you don't have any soon to be forgotten version of vim installed | |
$ sudo apt-get remove --purge vim vim-runtime vim-gnome vim-tiny vim-gui-common | |
# Install Deps | |
$ sudo apt-get install build-essential cmake | |
$ sudo apt-get install python3-dev | |
#Optional: so vim can be uninstalled again via `dpkg -r vim` | |
$ sudo apt-get install checkinstall |
pragma solidity ^0.4.24; | |
// ---------------------------------------------------------------------------- | |
// Sample token contract | |
// | |
// Symbol : LCST | |
// Name : LCS Token | |
// Total supply : 100000 | |
// Decimals : 2 | |
// Owner Account : 0xde0B295669a9FD93d5F28D9Ec85E40f4cb697BAe |
Largely based on the Tensorflow 1.6 gist, and Tensorflow 1.7 gist for xcode, this should hopefully simplify things a bit.
Ninj0r admin, [Oct 20, 2017, 9:18:55 AM]: | |
It's a three step process: | |
1) Start listening to the stream and buffering the messages | |
2) Get a depth snapshot | |
3) replay the buffered messages and the live messges. | |
Depth updates have two variables, u and U | |
U is the initial updateId, and u is the final updateId. There can be multiple updates "compressed" into a single update that comes out via the web socket stream. |
https://github.com/aancel/admin/wiki/VirtualGL-on-Ubuntu
https://virtualgl.org/About/Introduction
When you use ssh with X forwarding, you might have noticed that you cannot execute programs that require 3D acceleration. That's where VirtualGL comes into play.
If you work across many computers (and even otherwise!), it's a good idea to keep a copy of your setup on the cloud, preferably in a git repository, and clone it on another machine when you need.
Thus, you should keep the .vim
directory along with your .vimrc
version-controlled.
But when you have plugins installed inside .vim/bundle
(if you use pathogen), or inside .vim/pack
(if you use Vim 8's packages), keeping a copy where you want to be able to update the plugins (individual git repositories), as well as your vim-configuration as a whole, requires you to use git submodules.
Initialize a git repository inside your .vim
directory, add everything (including the vimrc), commit and push to a GitHub/BitBucket/GitLab repository:
cd ~/.vim
from tensorflow.python.client import device_lib | |
def get_available_gpus(): | |
local_device_protos = device_lib.list_local_devices() | |
return [x.name for x in local_device_protos if x.device_type == 'GPU'] | |
get_available_gpus() |
# Working example for my blog post at: | |
# https://danijar.github.io/structuring-your-tensorflow-models | |
import functools | |
import tensorflow as tf | |
from tensorflow.examples.tutorials.mnist import input_data | |
def doublewrap(function): | |
""" | |
A decorator decorator, allowing to use the decorator to be used without |