RodrigoCMoraes RodrigoCMoraes

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Original revision: 1.26

Paul Armstrong
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Installing Arch linux with EFI

Change keyboard layout:
- loadkeys no
Verify boot mode:
- ls /sys/firmware/efi/efivars (If the directory exist your computer supports EFI)
Ping some site on the Internet to verify connection:

ping archlinux.org

I use tmux splits (panes). Inside one of these panes there's a Vim process, and it has its own splits (windows).

In Vim I have key bindings C-h/j/k/l set to switch windows in the given direction. (Vim default mappings for windows switching are the same, but prefixed with C-W.) I'd like to use the same keystrokes for switching tmux panes.

An extra goal that I've solved with a dirty hack is to toggle between last active panes with C-\.

Here's how it should work:

	# Set vi key bindings mode
	set -g mode-keys vi
	set -g status-keys vi

	# Set new panes to open in current directory
	bind c new-window -c "#{pane_current_path}"
	bind '"' split-window -c "#{pane_current_path}"
	bind % split-window -h -c "#{pane_current_path}"

	# List of plugins

	#!/usr/bin/env bash

	# https://docs.docker.com/install/linux/docker-ce/ubuntu/
	sudo apt-get install apt-transport-https ca-certificates curl software-properties-common
	curl -fsSL https://download.docker.com/linux/ubuntu/gpg \| sudo apt-key add -
	sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu xenial stable"
	sudo apt-get update
	sudo apt-get install docker-ce

	# https://docs.docker.com/compose/install/

	#!/bin/bash

	# install CUDA Toolkit v9.0
	# instructions from https://developer.nvidia.com/cuda-downloads (linux -> x86_64 -> Ubuntu -> 16.04 -> deb)
	CUDA_REPO_PKG="cuda-repo-ubuntu1604-9-0-local_9.0.176-1_amd64-deb"
	wget https://developer.nvidia.com/compute/cuda/9.0/Prod/local_installers/${CUDA_REPO_PKG}
	sudo dpkg -i ${CUDA_REPO_PKG}
	sudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub
	sudo apt-get update
	sudo apt-get -y install cuda-9-0

	from tqdm import tqdm
	import requests

	chunk_size = 1024

	url = "http://www.nervenet.org/pdf/python3handson.pdf"

	r = requests.get(url, stream = True)

	total_size = int(r.headers['content-length'])

	'''Train a Siamese MLP on pairs of digits from the MNIST dataset.

	It follows Hadsell-et-al.'06 [1] by computing the Euclidean distance on the
	output of the shared network and by optimizing the contrastive loss (see paper
	for mode details).

	[1] "Dimensionality Reduction by Learning an Invariant Mapping"
	http://yann.lecun.com/exdb/publis/pdf/hadsell-chopra-lecun-06.pdf

	Run on GPU: THEANO_FLAGS=mode=FAST_RUN,device=gpu,floatX=float32 python mnist_siamese_graph.py

	"""An example of a cache decorator."""

	import json
	from functools import wraps
	from redis import StrictRedis


	redis = StrictRedis()

	def cached(func):

	#!/bin/bash

	#
	# This script should do:
	#
	# 1) test if nfs folder is mounted and exit 0 if yes
	# 2) try to mount it and exit 0 if success
	# 3) try to wake the server if not possible to mount
	# 4) wait while its not woked (pinging)
	# 5) try againt 2-4 several times