Another way is to use Git's "filter-branch" command. It allows you to batch-process a (potentially large) number of commits with a script.
You can run the below sample script in your repository (filling in real values for the old and new email and name):
$ git filter-branch --env-filter '
WRONG_EMAIL="wrong@example.com"
NEW_NAME="New Name Value"
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- Karabiner-Elements: A powerful and stable keyboard customizer for macOS.
- atd. How to start/stop/restart launchd services from the command line?
sudo launchctl load -w /System/Library/LaunchDaemons/com.apple.atrun.plist
- ROLES - All the user roles in our application.
- SCOPES - Scopes we pass to our gating wrapper.
- PERMISSIONS - The map defines the set of scopes each user role possesses.
export const ROLES = {
viewer: "VIEWER",
editor: "EDITOR",
#!/bin/bash | |
cd /var/www/html/biz | |
ssh -vT git@github.com # https://docs.github.com/en/authentication/troubleshooting-ssh/error-permission-denied-publickey#always-use-the-git-user | |
git fetch --prune | |
git checkout origin/test | |
git pull origin test |
https://geohot.github.io//blog/jekyll/update/2021/10/29/an-architecture-for-life.html
A representation function takes in the sensor data and transforms the manifold to something more learnable, referred to as the “hidden state”. It may discard non task relevant information. This can be a VAE, GAN, pretrained ImageNet, custom trained conv net, or in the case of GPT-3, handcoded as BPE.
A dynamics function deals with long term temporal correspondences. It functions as both a summarizer of the past and a predictor of the future, in the same way a Kalman filter does. This can be a couple dense layers, a transformer, or an RNN/GRU/LSTM. I guess it even could be a Kalman filter itself.
A prediction function tells you how to act in a state. It can do this by directly outputting an action or by outputting a value of this state allowing you to search.
- Include The Purpose Of The Pull Request
- Share Screenshots Of Visual Changes
- Provide Feature Requirements
- Elaborate On New Dependencies
- choosing a library to add to the codebase is an elaborate process requiring a lot of decisions
- Avoid Complex JavaScript Constructions
- Provide Additional Instructions On How To Review
If you're running a high-profile user-facing web application, caches and CDNs are absolutely critical to providing good performance for end users at a reasonable cost. Caches and CDNs sit in front of your web server, acting as a reverse proxy to ensure that:
- Content is cached, so your backend server only receives occasional requests for static content, not one request direct from every visitor.
- Content delivery is resilient to traffic spikes, because static caches scale far more easily than application servers.
- Content requests are batched, so 1000 simultaneous cache misses become just a single request to your backend.