jagregory

So you've cloned somebody's repo from github, but now you want to fork it and contribute back. Never fear!

Technically, when you fork "origin" should be your fork and "upstream" should be the project you forked; however, if you're willing to break this convention then it's easy.

* Off the top of my head *

1. Fork their repo on Github
2. In your local, add a new remote to your fork; then fetch it, and push your changes up to it

    git remote add my-fork [email protected]

bastman

Docker - How to cleanup (unused) resources

Once in a while, you may need to cleanup resources (containers, volumes, images, networks) ...

delete volumes

// see: https://github.com/chadoe/docker-cleanup-volumes

$ docker volume rm $(docker volume ls -qf dangling=true)

$ docker volume ls -qf dangling=true | xargs -r docker volume rm

blole

#!/usr/bin/env python2
import os
import gym
import sys
import random
import itertools
from time import time
from copy import copy
from math import sqrt, log

poolio

def _phase_shift(I, r):
    bsize, a, b, c = I.get_shape().as_list()
    X = tf.reshape(I, (bsize, a, b, r, r))
    X = tf.transpose(X, (0, 1, 2, 4, 3))  # bsize, a, b, 1, 1
    X = tf.split(1, a, X)  # a, [bsize, b, r, r]
    X = tf.concat(2, [tf.squeeze(x, [1]) for x in X])  # bsize, b, a*r, r
    X = tf.split(1, b, X)  # b, [bsize, a*r, r]
    X = tf.concat(2, [tf.squeeze(x, [1]) for x in X])  # bsize, a*r, b*r
    return tf.reshape(X, (bsize, a*r, b*r, 1))

robdvr

1. Remove qt4,5 poppler, cairo

brew uninstall cairo
brew poppler
brew qt
brew qt5

2. Install qt4 on Sierra & link qt (this will take about 20 mins)

Adriel-M

# REINFORCE: Monte Carlo Policy Gradient Implementation
# Learn more from Reinforcement Learning: An Introduction (p271)
# by Sutton & Barto

import tensorflow as tf
import gym
import numpy as np
from gym import wrappers

apaszke

from graphviz import Digraph
import torch
from torch.autograd import Variable, Function

def iter_graph(root, callback):
    queue = [root]
    seen = set()
    while queue:
        fn = queue.pop()
        if fn in seen:

machinaut

FROM ubuntu:18.04

# Install python and utils
RUN apt-get update && apt-get install -y python3-pip curl unzip \
    libosmesa-dev libglew-dev patchelf libglfw3-dev

# Download mujoco
RUN curl https://www.roboti.us/download/mjpro150_linux.zip --output /tmp/mujoco.zip && \
    mkdir -p /root/.mujoco && \
    unzip /tmp/mujoco.zip -d /root/.mujoco && \

sparkydogX

import os
import torch
from tqdm import tqdm
import time

# declare which gpu device to use
cuda_device = '0'

def check_mem(cuda_device):
    devices_info = os.popen('"/usr/bin/nvidia-smi" --query-gpu=memory.total,memory.used --format=csv,nounits,noheader').read().strip().split("\n")

paul-krohn

Preamble

There is a longstanding issue/missing feature/bug with sockets on Docker on macOS; it may never work; you'll need to use a network connection between Docker containers and X11 on macOS for the foreseeable future.

I started from this gist and made some adjustments:

• the volume mappings aren't relevant/used, due to the socket issue above.
• this method only allows X11 connections from your Mac, not the entire local network, which would include everyone on the café/airport WiFi.
• updated to include using the host.docker.internal name for the the container host, instead.
• you have to restart XQuartz after the config change.