- 경사스러운 일입니다. 이제 이 곳에 달리는 댓글을 막을 수 있어 그리 하게 되었습니다. 그래도 이전에 달렸던 댓글들은 아무래도 볼 수 있는 다른 방법이 인터넷 상에 존재하긴 하는 모양입니다.
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(U+2026),⋯
(U+22EF),⋮
(U+22EE)는 모두.
(U+002E)가 3번 연속으로 나열된 것과 같은 것으로 봅니다.- "한글 음절 문자"는 가(U+AC00) 이상 힣(U+D7A3) 이하의 유니코드 문자들을 의미합니다.
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(U+2026), ⋯
(U+22EF), ⋮
(U+22EE)는 모두 .
(U+002E)가 3번 연속으로 나열된 것과 같은 것으로 봅니다.Modern Cocoa development involves a lot of asynchronous programming using closures and completion handlers, but these APIs are hard to use. This gets particularly problematic when many asynchronous operations are used, error handling is required, or control flow between asynchronous calls gets complicated. This proposal describes a language extension to make this a lot more natural and less error prone.
This paper introduces a first class Coroutine model to Swift. Functions can opt into to being async, allowing the programmer to compose complex logic involving asynchronous operations, leaving the compiler in charge of producing the necessary closures and state machines to implement that logic.
# tap brew | |
tap "homebrew/bundle" | |
tap "homebrew/services" | |
tap "hashicorp/tap" | |
# need to check | |
#tap "homebrew/cask-versions" | |
#tap "homebrew/cask-fonts" | |
tap "buo/cask-upgrade" |
Author: Chris Lattner
from PIL import Image, ImageOps | |
import cv2 | |
desired_size = 368 | |
im_pth = "/home/jdhao/test.jpg" | |
# im = Image.open(im_pth) | |
# old_size = im.size # old_size[0] is in (width, height) format | |
# ratio = float(desired_size)/max(old_size) |
In open Ubuntu 18.04 machine click Parallels Actions -> "Install Parallels Tools"
A "Parallels Tools" CD will popup on your Ubuntu desktop.
Open it by double mouse click, copy all the content to a new, empty directory on a desktop, name it for e.g. "parallels_fixed"
Open terminal, change directory to parallels_fixed (cd ~/Desktop/parallels_fixed
)
Make command line installer executable (chmod +x install
)
Change directory to "installer" (cd installer
)
Make few other scripts executable: chmod +x installer.* *.sh prl_*
Being new to training ML models using Google Cloud VM instances, I faced issues where my ssh connection to the cloud instance (using either the clound web-based ssh client or using cloud shell) would disconnect from time to time (for example when I power off my laptop or the network gets disconnected) which would terminate the model training process. Therefore I searched for a ssh client that can handle disconnection and can resume connection without disrupting the process running on the server and came across with Mosh mobile shell, a remote terminal app that supports roaming.
It took me a while to figure out how to set up a third party ssh terminal using the google cloud OAuth. Here's a step-by-step guide:
Since this writing, another Mosh user kindly advised me that using terminal multiplexer co
import click | |
import difflib | |
import numpy as np | |
import random | |
import sys | |
import time | |
from os import name, system | |
from scipy.ndimage import convolve |
import Foundation | |
import SwiftUI | |
import Combine | |
import TinyNetworking | |
final class RemoteValue<A>: BindableObject { | |
let didChange = MyPublisher() | |
let endpoint: Endpoint<A> | |
var value: A? { | |
didSet { |
#!/usr/bin/env python3 | |
import time | |
from http.cookiejar import Cookie | |
from re import search, findall | |
from urllib.parse import urlencode | |
from urllib.request import ( | |
HTTPCookieProcessor, | |
HTTPRedirectHandler, | |
Request, |