A Closer Look at Invalid Action Masking in Policy Gradient Algorithms

Overview

A Closer Look at Invalid Action Masking in Policy Gradient Algorithms

This repo contains the source code to reproduce the results in the paper A Closer Look at Invalid Action Masking in Policy Gradient Algorithms.

Steps to reproduce the experiments

Our experiments use docker containers to run and Weight and Biases (https://www.wandb.com/) to record the experiments, so the first step is to register a wandb account and get an API key, which we refer to as YOUR_WANDB_KEY

# build the docker container
docker build -t invalid_action_masking:latest -f sharedmemory.Dockerfile .
# build docker run commands. replace `{YOUR_WANDB_KEY}` with your own
WANDB_KEY={YOUR_WANDB_KEY} python docker.py > docker.sh
# run experiments (96 in total)
# if you have limited computational resources, consider not running all of them at a time.
# in addition, notice the commands have --cpuset-cpus="0", --cpuset-cpus="1" for different runs
# to make sure each container is only using one core. By default I assume your machine has 40 cores,
# but feel free to modify the `cores` variable in `docker.py`
bash docker.sh

Steps to reproduce the figures

Record your wandb username, which we will refer to as YOUR_WANDB_ENTITY

cd plots
WANDB_ENTITY={YOUR_WANDB_ENTITY} python episode_reward.py
WANDB_ENTITY={YOUR_WANDB_ENTITY} python approx_kl.py

These command should reproduce the PDFs in plots that are attached to the repo.

Reproduction without WANDB

Although it would be possible, it would require a significant amount of effort to properly log metrics and redo the plotting, so at this time we would not have intructions to do reproduction without WANDB. Note that it is possible to use wandb locally by following https://docs.wandb.com/self-hosted/local.

If you have an issue reproducing the results

We have tested these scripts to reproduce but it is possible that there is a bug and maybe we are assuming something specific regarding the environment. If you couldn't reproduce our results, please file an issue and we will address it as soon as the double-blind review is over.

Owner
Costa Huang
Computer Science Ph.D student at Drexel University researching Game Artificial Intelligence
Costa Huang
PROJECT - Az Residential Real Estate Analysis

AZ RESIDENTIAL REAL ESTATE ANALYSIS -Decided on libraries to import. Includes pa

2 Jul 05, 2022
Official Implementation for Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation

Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation We present a generic image-to-image translation framework, pixel2style2pixel (pSp

2.8k Dec 30, 2022
FluidNet re-written with ATen tensor lib

fluidnet_cxx: Accelerating Fluid Simulation with Convolutional Neural Networks. A PyTorch/ATen Implementation. This repository is based on the paper,

JoliBrain 50 Jun 07, 2022
AQP is a modular pipeline built to enable the comparison and testing of different quality metric configurations.

Audio Quality Platform - AQP An Open Modular Python Platform for Objective Speech and Audio Quality Metrics AQP is a highly modular pipeline designed

Jack Geraghty 24 Oct 01, 2022
PyTorch code for 'Efficient Single Image Super-Resolution Using Dual Path Connections with Multiple Scale Learning'

Efficient Single Image Super-Resolution Using Dual Path Connections with Multiple Scale Learning This repository is for EMSRDPN introduced in the foll

7 Feb 10, 2022
Music Source Separation; Train & Eval & Inference piplines and pretrained models we used for 2021 ISMIR MDX Challenge.

Music Source Separation with Channel-wise Subband Phase Aware ResUnet (CWS-PResUNet) Introduction This repo contains the pretrained Music Source Separ

Lau 100 Dec 25, 2022
MobileNetV1-V2,MobileNeXt,GhostNet,AdderNet,ShuffleNetV1-V2,Mobile+ViT etc.

MobileNetV1-V2,MobileNeXt,GhostNet,AdderNet,ShuffleNetV1-V2,Mobile+ViT etc. ⭐⭐⭐⭐⭐

568 Jan 04, 2023
JORLDY an open-source Reinforcement Learning (RL) framework provided by KakaoEnterprise

Repository for Open Source Reinforcement Learning Framework JORLDY

Kakao Enterprise Corp. 330 Dec 30, 2022
Multi-modal Vision Transformers Excel at Class-agnostic Object Detection

Multi-modal Vision Transformers Excel at Class-agnostic Object Detection

Muhammad Maaz 206 Jan 04, 2023
Proximal Backpropagation - a neural network training algorithm that takes implicit instead of explicit gradient steps

Proximal Backpropagation Proximal Backpropagation (ProxProp) is a neural network training algorithm that takes implicit instead of explicit gradient s

Thomas Frerix 40 Dec 17, 2022
Prefix-Tuning: Optimizing Continuous Prompts for Generation

Prefix Tuning Files: . ├── gpt2 # Code for GPT2 style autoregressive LM │ ├── train_e2e.py # high-level script

530 Jan 04, 2023
ADOP: Approximate Differentiable One-Pixel Point Rendering

ADOP: Approximate Differentiable One-Pixel Point Rendering Abstract: We present a novel point-based, differentiable neural rendering pipeline for scen

Darius Rückert 1.9k Jan 06, 2023
Generative Autoregressive, Normalized Flows, VAEs, Score-based models (GANVAS)

GANVAS-models This is an implementation of various generative models. It contains implementations of the following: Autoregressive Models: PixelCNN, G

MRSAIL (Mini Robotics, Software & AI Lab) 6 Nov 26, 2022
Spatially-Adaptive Pixelwise Networks for Fast Image Translation, CVPR 2021

Image Translation with ASAPNets Spatially-Adaptive Pixelwise Networks for Fast Image Translation, CVPR 2021 Webpage | Paper | Video Installation insta

Tamar Rott Shaham 100 Dec 28, 2022
This repository contains the reference implementation for our proposed Convolutional CRFs.

ConvCRF This repository contains the reference implementation for our proposed Convolutional CRFs in PyTorch (Tensorflow planned). The two main entry-

Marvin Teichmann 553 Dec 07, 2022
Neural-net-from-scratch - A simple Neural Network from scratch in Python using the Pymathrix library

A Simple Neural Network from scratch A Simple Neural Network from scratch in Pyt

Youssef Chafiqui 2 Jan 07, 2022
RADIal is available now! Check the download section

Latest news: RADIal is available now! Check the download section. However, because we are currently working on the data anonymization, we provide for

valeo.ai 55 Jan 03, 2023
Supporting code for "Autoregressive neural-network wavefunctions for ab initio quantum chemistry".

naqs-for-quantum-chemistry This repository contains the codebase developed for the paper Autoregressive neural-network wavefunctions for ab initio qua

Tom Barrett 24 Dec 23, 2022
Fast Soft Color Segmentation

Fast Soft Color Segmentation

3 Oct 29, 2022
Experiments and code to generate the GINC small-scale in-context learning dataset from "An Explanation for In-context Learning as Implicit Bayesian Inference"

GINC small-scale in-context learning dataset GINC (Generative In-Context learning Dataset) is a small-scale synthetic dataset for studying in-context

P-Lambda 29 Dec 19, 2022