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Estados

Modificado (modified);
Preparado (staged/index)
Consolidado (comitted);

Ajuda

Code is clean if it can be understood easily – by everyone on the team. Clean code can be read and enhanced by a developer other than its original author. With understandability comes readability, changeability, extensibility and maintainability.

General rules

Follow standard conventions.
Keep it simple stupid. Simpler is always better. Reduce complexity as much as possible.
Boy scout rule. Leave the campground cleaner than you found it.
Always find root cause. Always look for the root cause of a problem.

	import tiktoken
	import langdetect
	T = tiktoken.get_encoding("o200k_base")

	length_dict = {}

	for i in range(T.n_vocab):
	try:
	length_dict[i] = len(T.decode([i]))
	except:

	local HttpService = game:GetService("HttpService")

	local API = "https://api.github.com/gists"

	export type JSONString = string

	-- Function to encode data into JSON format
	-- @param data The data to be encoded
	-- @return The encoded data
	local function encode(data: table?): JSONString?

	# this GIST is a follow-up to this previous GIST: https://gist.github.com/morgangiraud/ffa45e76b6891cd4e37e90d75b8be37b
	# See the article here: https://morgangiraud.medium.com/multi-gpu-nvidia-p2p-capabilities-and-debugging-tips-fb7597b4e2b5

	# It provides some tips and tricks to install Tinygrad patched nvidia open kernel to give P2P capabilities
	# to the 40** series!

	### Transitioning into complex operations, our aim is to minimize potential issues.
	### Important: Verify that the version from nvidia-smi matches exactly what we intend to use.
	### At the time of this writing, the reported version is 550.78.

	impl Solution {
	pub fn is_palindrome(x: i32) -> bool {
	if x < 0 {
	return false;
	}

	let mut x_copy = x;
	let mut reverse: i32 = 0;
	while x_copy > 0 {
	reverse = (reverse * 10) + (x_copy % 10);

	# Script for Ubuntu: Nvidia Multi-GPU Installation and Testing (Adaptable for other distros)

	# Step 0: Clean Nvidia Installation
	# If you need to completely remove a previous Nvidia installation, use these commands.
	# This ensures that you start with a clean slate for a new installation.
	sudo apt-get --purge remove "nvidia"
	sudo apt-get --purge remove "cuda" "cudnn" "cublas" "cufft" "cufile" "curand" "cusolver" "cusparse" "gds-tools" "npp" "nvjpeg" "nsight" "nvvm" "libnccl*"

	# Verify that the removal is complete by checking if any Nvidia, CUDA, or cuDNN packages are still installed.
	apt list --installed \| grep cuda

Discover gists

GIT

Estados

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General rules

Design rules

Table of Contents

set -e, -u, -x, -o pipefail

	// Source: http://codereview.stackexchange.com/questions/95464/is-the-copy-swap-idiom-implemented-here-correctly

	class Array
	{
	int size;
	int* data;
	public:
	Array(Array const& copy)
	: size(copy.size)
	, data(new int[size])

	# setup dbus
	if test -z "$DBUS_SESSION_BUS_ADDRESS"; then
	eval $(dbus-launch --exit-with-session --sh-syntax)
	fi
	systemctl --user import-environment DISPLAY XAUTHORITY

	if command -v dbus-update-activation-environment >/dev/null 2>&1; then
	dbus-update-activation-environment DISPLAY XAUTHORITY
	fi