When hosting our web applications, we often have one public IP
address (i.e., an IP address visible to the outside world)
using which we want to host multiple web apps. For example, one
may wants to host three different web apps respectively for
example1.com, example2.com, and example1.com/images on
the same machine using a single IP address.
How can we do that? Well, the good news is Internet browsers
| import express from "express"; | |
| /** | |
| * Takes a route handling function and returns a function | |
| * that wraps it after first checking that the strings in | |
| * `reserved` are not part of `req.body`. Used for ensuring | |
| * create and update requests do not overwrite server-generated | |
| * values. | |
| */ | |
| function checkReservedParams(routeHandler, ...reserved) { |
| """ | |
| Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy) | |
| BSD License | |
| """ | |
| import numpy as np | |
| # data I/O | |
| data = open('input.txt', 'r').read() # should be simple plain text file | |
| chars = list(set(data)) | |
| data_size, vocab_size = len(data), len(chars) |
| import { CALL_API } from 'redux-api-middleware' | |
| export function fetchLocations() { | |
| return { | |
| [CALL_API]: { | |
| endpoint: 'http://api.somesite.com/api/locations', | |
| method: 'GET', | |
| // Don't have to manually add the Authorization header to every request. | |
| headers: { 'Content-Type': 'application/json' }, | |
| types: ['REQUEST', 'SUCCESS', 'FAILURE'] |
CloudFlare is an awesome reverse cache proxy and CDN that provides DNS, free HTTPS (TLS) support, best-in-class performance settings (gzip, SDCH, HTTP/2, sane Cache-Control and E-Tag headers, etc.), minification, etc.
The official instructions on installing TensorFlow are here: https://www.tensorflow.org/install. If you want to install TensorFlow just using pip, you are running a supported Ubuntu LTS distribution, and you're happy to install the respective tested CUDA versions (which often are outdated), by all means go ahead. A good alternative may be to run a Docker image.
I am usually unhappy with installing what in effect are pre-built binaries. These binaries are often not compatible with the Ubuntu version I am running, the CUDA version that I have installed, and so on. Furthermore, they may be slower than binaries optimized for the target architecture, since certain instructions are not being used (e.g. AVX2, FMA).
So installing TensorFlow from source becomes a necessity. The official instructions on building TensorFlow from source are here: ht
| version: "3" | |
| services: | |
| sonarqube: | |
| image: sonarqube | |
| expose: | |
| - 9000 | |
| ports: | |
| - "127.0.0.1:9000:9000" | |
| networks: |
| Hi All! | |
| I've recently launched a tool that wraps many of the commands here with a user interface. This desktop application is currently available for macOS. There's a roadmap outlining planned features for the near future. | |
| Feel free to request any features you'd like to see, and I'll prioritize them accordingly. | |
| One of the most important aspects of this application is that every command executed behind the scenes is displayed in a special log section. This allows you to see exactly what’s happening and learn from it. | |
| Here's the link to the repository: https://github.com/Pulimet/ADBugger | |
| App Description: | |
| ADBugger is a desktop tool designed for debugging and QA of Android devices and emulators. It simplifies testing, debugging, and performance analysis by offering device management, automated testing, log analysis, and remote control capabilities. This ensures smooth app performance across various setups. |
