ugo-nama-kun

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

ethanhs

#![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)]

pierrelux

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

dikiaap

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

mswell

[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"

cyberang3l

https://github.com/aancel/admin/wiki/VirtualGL-on-Ubuntu

https://virtualgl.org/About/Introduction

https://www.turbovnc.org

VirtualGL

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.

karpathy

"""
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

ax3l

# 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

karpathy

""" 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

karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)