rojas-diego

use ropey::{Rope, RopeSlice};
use serde::{Deserialize, Serialize};
use std::fmt;
use thiserror::Error;
use tower_lsp::lsp_types::{Position, TextDocumentContentChangeEvent};
use tree_sitter::{InputEdit, Parser, Point, Tree};

pub struct TextDocument {
    pub rope: Rope,
    pub tree: Option<Tree>,

rojas-diego

#!/bin/bash

mkdir -p $HOME/diego-install
cd $HOME/diego-install

# Installing utilities
echo "--------------------------------------------------------------------"
echo "> Updating apt"
sudo apt update
echo "--------------------------------------------------------------------"

rojas-diego

Neptune.ai Introduction with RLlib and Tune

Hyperparameter tuning and training optimisation using RLlib, Tune and Neptune.

Description

This scripts implements a basic Logger for Tune in order to send training data to neptune.ai

Usage

rojas-diego

Ray - Distributed training in Python

This Gist serves the sole purpose of condensing the Ray documentation in regards to Ray Core, Tune and RLlib. It was originally written for my personal use: as some quick notes to skim through. Moreover, the code is heavily if not entirely based on the Documentation snippets which can be found here

Ray Core

Description