Antoine M-P antoineMoPa

Normalization functions

Sometimes when coding, we discover a few different representations of the same data.

It can be tempting to write a function to combine these different representations.

Example:

function normalizeSku(sku: string|number) {

Can you do a first pass of cleanups? Pay attention to:

Leaked keys
Indirectly leaked keys
Overly defensive programming and hiding failures instead of letting errors bubble up, also while adding too much code.
- This is perhaps the most common and annoying. The AI wants to build trust by making code that can’t fail, but that ultimately is just gaslighting us into thinking it works / is robust. It’s delaying finding issues and making unmaintainable code.
Here is an example:

Inlining SVG styles easily with svgo

npm install -g svgo

This is a complete example of using candle to train a simple neural network on a XOR dataset.

Hopefully, this helps some folks trying candle for the first time!

Please report any issues

fn position_in_camera_plane(p: vec3<f32>) -> vec2<f32> {
 return vec2(dot(p, camera_right.xyz), dot(p, camera_up.xyz));

Some time-sensitive test may be easier to reproduce on slower machines.

-resource_class: large
+resource_class: medium

	#!/bin/bash

	if [ $# -lt 1 ]; then
	echo "Usage: $0 <search_pattern>"
	echo " Searches for pattern in file contents and filenames"
	exit 1
	fi

	search_pattern=$1

	const object_to_watch = obj; // Change to the object you are inspecting
	const property_to_watch = 'example'; // Change to the property name in the object you are inspecting (here obj.example)

	// Store the original value
	object_to_watch.__storedValue = object_to_watch[property_to_watch];

	Object.defineProperty(object_to_watch, property_to_watch, {
	get() {
	return this.__storedValue;
	},

	# Add this to your .gitconfig and use `git recent-branches`

	[alias]
	recent-branches = branch -v --sort=-committerdate