Lipschitz-constrained Unsupervised Skill Discovery

Related tags

Deep LearningLSD
Overview

Lipschitz-constrained Unsupervised Skill Discovery

This repository is the official implementation of

The implementation is based on Unsupervised Skill Discovery with Bottleneck Option Learning and garage.

Visit our project page for more results including videos.

Requirements

Examples

Install requirements:

pip install -r requirements.txt
pip install -e .
pip install -e garaged

Ant with 2-D continuous skills:

python tests/main.py --run_group EXP --env ant --max_path_length 200 --dim_option 2 --common_lr 0.0001 --seed 0 --normalizer_type ant_preset --use_gpu 1 --traj_batch_size 20 --n_parallel 8 --n_epochs_per_eval 5000 --n_thread 1 --model_master_dim 1024 --record_metric_difference 0 --n_epochs_per_tb 100 --n_epochs_per_save 50000 --n_epochs_per_pt_save 5000 --n_epochs_per_pkl_update 1000 --eval_record_video 1 --n_epochs 200001 --spectral_normalization 1 --n_epochs_per_log 50 --discrete 0 --num_random_trajectories 200 --sac_discount 0.99 --alpha 0.01 --sac_lr_a -1 --lr_te 3e-05 --sac_scale_reward 0 --max_optimization_epochs 1 --trans_minibatch_size 2048 --trans_optimization_epochs 4 --eval_plot_axis -50 50 -50 50

Ant with 16 discrete skills:

python tests/main.py --run_group EXP --env ant --max_path_length 200 --dim_option 16 --common_lr 0.0001 --seed 0 --normalizer_type ant_preset --use_gpu 1 --traj_batch_size 20 --n_parallel 8 --n_epochs_per_eval 5000 --n_thread 1 --model_master_dim 1024 --record_metric_difference 0 --n_epochs_per_tb 100 --n_epochs_per_save 50000 --n_epochs_per_pt_save 5000 --n_epochs_per_pkl_update 1000 --eval_record_video 1 --n_epochs 200001 --spectral_normalization 1 --n_epochs_per_log 50 --discrete 1 --num_random_trajectories 200 --sac_discount 0.99 --alpha 0.003 --sac_lr_a -1 --lr_te 3e-05 --sac_scale_reward 0 --max_optimization_epochs 1 --trans_minibatch_size 2048 --trans_optimization_epochs 4 --eval_plot_axis -50 50 -50 50

Humanoid with 2-D continuous skills:

python tests/main.py --run_group EXP --env humanoid --max_path_length 1000 --dim_option 2 --common_lr 0.0003 --seed 0 --normalizer_type humanoid_preset --use_gpu 1 --traj_batch_size 5 --n_parallel 8 --n_epochs_per_eval 5000 --n_thread 1 --model_master_dim 1024 --record_metric_difference 0 --n_epochs_per_tb 100 --n_epochs_per_save 50000 --n_epochs_per_pt_save 5000 --n_epochs_per_pkl_update 1000 --eval_record_video 1 --n_epochs 200001 --spectral_normalization 1 --n_epochs_per_log 50 --discrete 0 --video_skip_frames 3 --num_random_trajectories 200 --sac_discount 0.99 --alpha 0.03 --sac_lr_a -1 --lr_te 0.0001 --lsd_alive_reward 0.03 --sac_scale_reward 0 --max_optimization_epochs 1 --trans_minibatch_size 2048 --trans_optimization_epochs 4 --sac_replay_buffer 1 --te_max_optimization_epochs 1 --te_trans_optimization_epochs 2

Humanoid with 16 discrete skills:

python tests/main.py --run_group EXP --env humanoid --max_path_length 1000 --dim_option 16 --common_lr 0.0003 --seed 0 --normalizer_type humanoid_preset --use_gpu 1 --traj_batch_size 5 --n_parallel 8 --n_epochs_per_eval 5000 --n_thread 1 --model_master_dim 1024 --record_metric_difference 0 --n_epochs_per_tb 100 --n_epochs_per_save 50000 --n_epochs_per_pt_save 5000 --n_epochs_per_pkl_update 1000 --eval_record_video 1 --n_epochs 200001 --spectral_normalization 1 --n_epochs_per_log 50 --discrete 1 --video_skip_frames 3 --num_random_trajectories 200 --sac_discount 0.99 --alpha 0.03 --sac_lr_a -1 --lr_te 0.0001 --lsd_alive_reward 0.03 --sac_scale_reward 0 --max_optimization_epochs 1 --trans_minibatch_size 2048 --trans_optimization_epochs 4 --sac_replay_buffer 1 --te_max_optimization_epochs 1 --te_trans_optimization_epochs 2

HalfCheetah with 8 discrete skills:

python tests/main.py --run_group EXP --env half_cheetah --max_path_length 200 --dim_option 8 --common_lr 0.0001 --seed 0 --normalizer_type half_cheetah_preset --use_gpu 1 --traj_batch_size 20 --n_parallel 8 --n_epochs_per_eval 5000 --n_thread 1 --model_master_dim 1024 --record_metric_difference 0 --n_epochs_per_tb 100 --n_epochs_per_save 50000 --n_epochs_per_pt_save 5000 --n_epochs_per_pkl_update 1000 --eval_record_video 1 --n_epochs 200001 --spectral_normalization 1 --n_epochs_per_log 50 --discrete 1 --num_random_trajectories 200 --sac_discount 0.99 --alpha 0.01 --sac_lr_a -1 --lr_te 3e-05 --sac_scale_reward 0 --max_optimization_epochs 1 --trans_minibatch_size 2048 --trans_optimization_epochs 4
Owner
Seohong Park
Seohong Park
High-Resolution 3D Human Digitization from A Single Image.

PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization (CVPR 2020) News: [2020/06/15] Demo with Google Colab (i

Meta Research 8.4k Dec 29, 2022
The final project for "Applying AI to Wearable Device Data" course from "AI for Healthcare" - Udacity.

Motion Compensated Pulse Rate Estimation Overview This project has 2 main parts. Develop a Pulse Rate Algorithm on the given training data. Then Test

Omar Laham 2 Oct 25, 2022
This repository contains an implementation of ConvMixer for the ICLR 2022 submission "Patches Are All You Need?".

Patches Are All You Need? 🤷 This repository contains an implementation of ConvMixer for the ICLR 2022 submission "Patches Are All You Need?". Code ov

ICLR 2022 Author 934 Dec 30, 2022
Repository aimed at compiling code, papers, demos etc.. related to my PhD on 3D vision and machine learning for fruit detection and shape estimation at the university of Lincoln

PhD_3DPerception Repository aimed at compiling code, papers, demos etc.. related to my PhD on 3D vision and machine learning for fruit detection and s

lelouedec 2 Oct 06, 2022
Knowledge Distillation Toolbox for Semantic Segmentation

SegDistill: Toolbox for Knowledge Distillation on Semantic Segmentation Networks This repo contains the supported code and configuration files for Seg

9 Dec 12, 2022
Code for "PVNet: Pixel-wise Voting Network for 6DoF Pose Estimation" CVPR 2019 oral

Good news! We release a clean version of PVNet: clean-pvnet, including how to train the PVNet on the custom dataset. Use PVNet with a detector. The tr

ZJU3DV 722 Dec 27, 2022
A PyTorch-based open-source framework that provides methods for improving the weakly annotated data and allows researchers to efficiently develop and compare their own methods.

Knodle (Knowledge-supervised Deep Learning Framework) - a new framework for weak supervision with neural networks. It provides a modularization for se

93 Nov 06, 2022
Equivariant layers for RC-complement symmetry in DNA sequence data

Equi-RC Equivariant layers for RC-complement symmetry in DNA sequence data This is a repository that implements the layers as described in "Reverse-Co

7 May 19, 2022
Code for visualizing the loss landscape of neural nets

Visualizing the Loss Landscape of Neural Nets This repository contains the PyTorch code for the paper Hao Li, Zheng Xu, Gavin Taylor, Christoph Studer

Tom Goldstein 2.2k Jan 09, 2023
DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image Segmentation

DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image Segmentation By Qing Xu, Wenting Duan and Na He Requirements pytorch==1.1

Qing Xu 20 Dec 09, 2022
Code for the paper "Query Embedding on Hyper-relational Knowledge Graphs"

Query Embedding on Hyper-Relational Knowledge Graphs This repository contains the code used for the experiments in the paper Query Embedding on Hyper-

DimitrisAlivas 19 Jul 26, 2022
This is RFA-Toolbox, a simple and easy-to-use library that allows you to optimize your neural network architectures using receptive field analysis (RFA) and create graph visualizations of your architecture.

ReceptiveFieldAnalysisToolbox This is RFA-Toolbox, a simple and easy-to-use library that allows you to optimize your neural network architectures usin

84 Nov 23, 2022
[3DV 2020] PeeledHuman: Robust Shape Representation for Textured 3D Human Body Reconstruction

PeeledHuman: Robust Shape Representation for Textured 3D Human Body Reconstruction International Conference on 3D Vision, 2020 Sai Sagar Jinka1, Rohan

Rohan Chacko 39 Oct 12, 2022
Off-policy continuous control in PyTorch, with RDPG, RTD3 & RSAC

arXiv technical report soon available. we are updating the readme to be as comprehensive as possible Please ask any questions in Issues, thanks. Intro

Zhihan 31 Dec 30, 2022
Neural network for recognizing the gender of people in photos

Neural Network For Gender Recognition How to test it? Install requirements.txt file using pip install -r requirements.txt command Run nn.py using pyth

Valery Chapman 1 Sep 18, 2022
Consensus score for tripadvisor

ContripScore ContripScore is essentially a score that combines an Internet platform rating and a consensus rating from sentiment analysis (For instanc

Pepe 1 Jan 13, 2022
Collects many various multi-modal transformer architectures, including image transformer, video transformer, image-language transformer, video-language transformer and related datasets

The repository collects many various multi-modal transformer architectures, including image transformer, video transformer, image-language transformer, video-language transformer and related datasets

Jun Chen 139 Dec 21, 2022
Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning

SkFlow has been moved to Tensorflow. SkFlow has been moved to http://github.com/tensorflow/tensorflow into contrib folder specifically located here. T

3.2k Dec 29, 2022
Voice Gender Recognition

In this project it was used some different Machine Learning models to identify the gender of a voice (Female or Male) based on some specific speech and voice attributes.

Anne Livia 1 Jan 27, 2022
Towards Rolling Shutter Correction and Deblurring in Dynamic Scenes (CVPR2021)

RSCD (BS-RSCD & JCD) Towards Rolling Shutter Correction and Deblurring in Dynamic Scenes (CVPR2021) by Zhihang Zhong, Yinqiang Zheng, Imari Sato We co

81 Dec 15, 2022