Update: As of 11 January 2022, git.io no longer accepts new URLs.
Command:
curl https://git.io/ -i -F "url=https://github.com/YOUR_GITHUB_URL" -F "code=YOUR_CUSTOM_NAME"
URLs that can be created is from:
https://github.com/*
https://*.github.com
#!/bin/sh | |
[ -x /etc/vnc/xstartup ] && exec /etc/vnc/xstartup | |
[ -r $HOME/.Xresources ] && xrdb $HOME/.Xresources | |
vncconfig -iconic & | |
export DESKTOP_SESSION=/usr/share/xsessions/ubuntu.desktop | |
export XDG_CURRENT_DESKTOP=ubuntu:GNOME | |
export GNOME_SHELL_SESSION_MODE=ubuntu | |
export XDG_DATA_DIRS=/usr/share/ubuntu:/usr/local/share/:/usr/share/:/var/lib/snapd/desktop | |
dbus-launch --exit-with-session /usr/bin/gnome-session --systemd --session=ubuntu |
import numpy as np | |
import gym | |
from gym.envs.mujoco import mujoco_env | |
from mujoco_py.generated import const | |
from scipy.spatial.transform import Rotation | |
""" Marker types in const | |
GEOM_PLANE = 0 |
#![feature(arbitrary_self_types)] | |
use pyo3::prelude::*; | |
use pyo3::pyclass::PyClassShell; | |
use pyo3::types::{PyBytes, PyTuple}; | |
use pyo3::ToPyObject; | |
use bincode::{deserialize, serialize}; | |
use serde::{Deserialize, Serialize}; | |
#[derive(Serialize, Deserialize)] |
import jax | |
import jax.numpy as np | |
from jax import grad, jit | |
from jax.scipy.special import logsumexp | |
def dadashi_fig2d(): | |
""" Figure 2 d) of | |
''The Value Function Polytope in Reinforcement Learning'' | |
by Dadashi et al. (2019) https://arxiv.org/abs/1901.11524 |
Update: As of 11 January 2022, git.io no longer accepts new URLs.
Command:
curl https://git.io/ -i -F "url=https://github.com/YOUR_GITHUB_URL" -F "code=YOUR_CUSTOM_NAME"
URLs that can be created is from:
https://github.com/*
https://*.github.com
[global_config] | |
window_state = maximise | |
handle_size = 0 | |
title_hide_sizetext = True | |
title_transmit_fg_color = "#bd93f9" | |
title_inactive_fg_color = "#f8f8f2" | |
title_receive_bg_color = "#282a36" | |
title_transmit_bg_color = "#282a36" | |
title_receive_fg_color = "#8be9fd" |
https://github.com/aancel/admin/wiki/VirtualGL-on-Ubuntu
https://virtualgl.org/About/Introduction
When you use ssh with X forwarding, you might have noticed that you cannot execute programs that require 3D acceleration. That's where VirtualGL comes into play.
""" | |
A bare bones examples of optimizing a black-box function (f) using | |
Natural Evolution Strategies (NES), where the parameter distribution is a | |
gaussian of fixed standard deviation. | |
""" | |
import numpy as np | |
np.random.seed(0) | |
# the function we want to optimize |
# License: | |
# I hereby state this snippet is below "threshold of originality" where applicable (public domain). | |
# | |
# Otherwise, since initially posted on Stackoverflow, use as: | |
# CC-BY-SA 3.0 skyking, Glenn Maynard, Axel Huebl | |
# http://stackoverflow.com/a/31047259/2719194 | |
# http://stackoverflow.com/a/4858123/2719194 | |
import types |
""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """ | |
import numpy as np | |
import cPickle as pickle | |
import gym | |
# hyperparameters | |
H = 200 # number of hidden layer neurons | |
batch_size = 10 # every how many episodes to do a param update? | |
learning_rate = 1e-4 | |
gamma = 0.99 # discount factor for reward |