ryin

#!/bin/bash

# Script for installing tmux on systems where you don't have root access.
# tmux will be installed in $HOME/local/bin.
# It's assumed that wget and a C/C++ compiler are installed.

# exit on error
set -e

TMUX_VERSION=1.8

takuma7

OpenCV Video Writer on Mac OS X

Fourcc tests:

• x : not worked
• o: worked (able to open in quicktime but need conversion)
• oo: worked well (preview worked but wrong aspect ratio)
• ooo: worked very well (preview worked, and aspect ratio’s right)

(Codecs are extracted from https://web.archive.org/web/20120722124832/http://opencv.willowgarage.com/wiki/QuickTimeCodecs )

jfpuget

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

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

MatthiasWinkelmann

# This extracts png images from the 
# packed/pickle'd cifar-100 dataset 
# available at http://www.cs.toronto.edu/~kriz/cifar.html
#
# No Rights Reserved/ CC0
# Say thanks @whereismatthi on Twitter if it's useful
#
# probably requires python3
# definitely requires PyPNG: pip3 install pypng

fmassa

# this is the main entrypoint
# as we describe in the paper, we compute the flops over the first 100 images
# on COCO val2017, and report the average result
import torch
import time
import torchvision

import numpy as np
import tqdm