malkin1729

import torch as T
import numpy as np
import tqdm
import pickle

device = T.device('cpu')

horizon = 8
ndim = 2

ZhaofengWu

#!/bin/bash

set -e

# OPTIONAL: zsh will not install without ncurses. IF your machine doesn't have ncurses, you need to install it first.
export CXXFLAGS=" -fPIC" CFLAGS=" -fPIC" CPPFLAGS="-I${HOME}/include" LDFLAGS="-L${HOME}/lib"
wget https://ftp.gnu.org/pub/gnu/ncurses/ncurses-6.2.tar.gz
tar -xzvf ncurses-6.2.tar.gz
cd ncurses-6.2
./configure --prefix=$HOME --enable-shared

devin-petersohn

zhanwenchen

Updated 4/11/2018

Here's my experience of installing the NVIDIA CUDA kit 9.0 on a fresh install of Ubuntu Desktop 16.04.4 LTS.

Table of Contents

• Install NVIDIA Graphics Driver via apt-get
• Install CUDA
• Install cuDNN

Table of contents generated with markdown-toc

lpillmann

#!/usr/bin/env python
'''Crop an image to just the portions containing text.

Usage:

    ./crop_morphology.py path/to/image.jpg

This will place the cropped image in path/to/image.crop.png.

For details on the methodology, see

mjdietzx

#!/bin/bash

# install CUDA Toolkit v8.0
# instructions from https://developer.nvidia.com/cuda-downloads (linux -> x86_64 -> Ubuntu -> 16.04 -> deb (network))
CUDA_REPO_PKG="cuda-repo-ubuntu1604_8.0.61-1_amd64.deb"
wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/${CUDA_REPO_PKG}
sudo dpkg -i ${CUDA_REPO_PKG}
sudo apt-get update
sudo apt-get -y install cuda

andrewliao11

# modified from https://gist.github.com/sorenbouma/6502fbf55ecdf988aa247ef7f60a9546
import gym
import numpy as np
import matplotlib.pyplot as plt

env = gym.make('CartPole-v0')
env.render(close=True)
#vector of means(mu) and standard dev(sigma) for each paramater
mu=np.random.uniform(size=env.observation_space.shape)
sigma=np.random.uniform(low=0.001,size=env.observation_space.shape)

ipbastola

Safest way to clean up boot partition - Ubuntu 14.04LTS-x64, Ubuntu 16.04LTS-x64

Reference

Case I: if /boot is not 100% full and apt is working

1. Check the current kernel version

$ uname -r 

wangruohui

In this article, I will share some of my experience on installing NVIDIA driver and CUDA on Linux OS. Here I mainly use Ubuntu as example. Comments for CentOS/Fedora are also provided as much as I can.

Table of Contents

• Install NVIDIA Graphics Driver via apt-get
• Install NVIDIA Graphics Driver via runfile
  • Remove Previous Installations (Important)
  • Download the Driver
  • Install Dependencies
  • Creat Blacklist for Nouveau Driver

• Stop lightdm/gdm/kdm

shagunsodhani

Curriculum Learning

Introduction

• Curriculum Learning - When training machine learning models, start with easier subtasks and gradually increase the difficulty level of the tasks.
• Motivation comes from the observation that humans and animals seem to learn better when trained with a curriculum like a strategy.
• Link to the paper.

Contributions of the paper