Hyperparameter tuning and training optimisation using RLlib, Tune and Neptune.
This scripts implements a basic Logger for Tune in order to send training data to neptune.ai
| 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>, |
| #!/bin/bash | |
| mkdir -p $HOME/diego-install | |
| cd $HOME/diego-install | |
| # Installing utilities | |
| echo "--------------------------------------------------------------------" | |
| echo "> Updating apt" | |
| sudo apt update | |
| echo "--------------------------------------------------------------------" |
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