Shenghang Tsai jackalcooper

Using Swift Package Manager with iOS

Step 1:

File > New > Project...

Step 2:

Create a Package.swift file in your root project directory, add dependencies, then run swift package fetch on the command line in the same directory. We’re not going to run swift build because it will just complain.

How to create a custom Caffe layer in Python?

This tutorial will guide through the steps to create a simple custom layer for Caffe using python. By the end of it, there are some examples of custom layers.

- Why would I want to do that?

Usually you would create a custom layer to implement a funcionality that isn't available in Caffe, tuning it for your requirements.

- What will I need?

Probably just Python and Caffe installed.

- Is there any downside?

Ubuntu 18.04 VFIO GPU passthrough with a single GPU (onboard automatically disables itself)

Hardware

https://www.reddit.com/r/JDM_WAAAT/comments/8zgkfj/server_build_nas_killer_v_20_the_terminator_dual/ 2x X5650 from this thread Aside from that build guide, a generic USB3 card and an AMD R9-200

Grub

Modify /etc/default/grub and add vfio-pci.ids=dead:beef video=efifb:off to GRUB_CMDLINE_LINUX_DEFAULT (use the PCI vid/pid of your primary GPU, not dead:beef)

	import Graphics.Element exposing (Element, show)
	import Task exposing (Task, andThen)
	import Json.Decode exposing (Decoder, int, string, object3, (:=), at, keyValuePairs)

	import Http

	type alias Languages =
	List (String, Int)

	mailbox =

	#!/bin/sh
	# Usage:
	# wget -O- https://gist.githubusercontent.com/ifduyue/dea03b4e139c5758ca114770027cf65c/raw/install-proxychains-ng.sh \| sudo bash -s

	set -eu

	version=4.14
	wget https://github.com/rofl0r/proxychains-ng/archive/v$version.tar.gz
	tar xf v$version.tar.gz

	# - Find Intel MKL
	# modified for AMBER
	# Find the MKL libraries
	#
	# NOTE: MKL_MULTI_THREADED requires the patched FindOpenMPFixed module from the Amber-MD/cmake-buildscripts repository.
	#
	# Options:
	#
	# MKL_STATIC : use static linking. Requires linker support for the -Wl,--start-group flag.
	# MKL_MULTI_THREADED: use multi-threading. Requires the FindOpenMP module

	from __future__ import division, print_function, absolute_import, \
	unicode_literals

	import tensorflow as tf
	from tensorflow.examples.tutorials.mnist import input_data as mnist_data
	from tensorflow.contrib import slim
	from tensorflow.contrib.learn import ModeKeys
	from tensorflow.contrib.learn.python.learn import learn_runner

	import matplotlib.pyplot as plt
	#for plotting
	import numpy as np

	# create plot
	fig, ax = plt.subplots()
	bar_width = 0.15
	opacity = 0.8

	xlabel= np.array([8, 16, 32, 64])

	#! /usr/bin/env bash
	#
	# Run parallel commands and fail if any of them fails.
	#

	set -eu

	pids=()

	for x in 1 2 3; do

	import SwiftUI
	import Combine
	import AlamofireImage

	let imageDownloader = ImageDownloader(
	configuration: ImageDownloader.defaultURLSessionConfiguration(),
	downloadPrioritization: .fifo,
	maximumActiveDownloads: 4,
	imageCache: AutoPurgingImageCache()
	)