w-e-w

from datetime import datetime
import urllib.request
import base64
import json
import time
import os

webui_server_url = 'http://127.0.0.1:7860'

out_dir = 'api_out'

jokkebk

william8th

# Set the control character to Ctrl+Spacebar (instead of Ctrl+B)
set -g prefix C-space
unbind-key C-b
bind-key C-space send-prefix

# Set new panes to open in current directory
bind c new-window -c "#{pane_current_path}"
bind '"' split-window -c "#{pane_current_path}"
bind % split-window -h -c "#{pane_current_path}"

saidsef

AWS Lambda

Whats the maximum number of virtual processor cores available in aws lambda

Memory Settings:

Memory: 3008 MB

iMilnb

Rationale

This snippet is a sample showing how to implement CloudWatch Logs streaming to ElasticSearch using terraform. I wrote this gist because I didn't found a clear, end-to-end example on how to achieve this task. In particular, I understood the resource "aws_lambda_permission" "cloudwatch_allow" part by reading a couple of bug reports plus this stackoverflow post.

The js file is actually the Lambda function automatically created by AWS when creating this pipeline through the web console. I only added a endpoint variable handling so it is configurable from terraform.

Mikulas

import bpy

# https://blender.stackexchange.com/questions/5281/blender-sets-compute-device-cuda-but-doesnt-use-it-for-actual-render-on-ec2
bpy.context.user_preferences.addons['cycles'].preferences.compute_device_type = 'CUDA'
bpy.context.user_preferences.addons['cycles'].preferences.devices[0].use = True

bpy.context.scene.cycles.device = 'GPU'

bpy.data.scenes["Scene"].render.filepath = "/tmp/output.png"
bpy.ops.render.render(write_still=True)

2075

// npm install --save scrollreveal or install like you're used to doing it.
// It doesn't work well if there are multiple instances of ScrollReveal,
// so we have to create a module returning an instance:
// file ScrollReveal.js:
import ScrollReveal from 'scrollreveal'
export default ScrollReveal()

// Then in a component:
import React from 'react'
import sr from './ScrollReveal'

jgautheron

import ReactUpdates from 'react-dom/lib/ReactUpdates'
import ReactDefaultBatchingStrategy from 'react-dom/lib/ReactDefaultBatchingStrategy'
import 'isomorphic-fetch'

const logError = (err, extra = {}) => {
  fetch('/logger', {
    method: 'POST',
    credentials: 'same-origin',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({

BretFisher

2021 Update: Easiest option is Justin's repo and image

Just run this from your Mac terminal and it'll drop you in a container with full permissions on the Docker VM. This also works for Docker for Windows for getting in Moby Linux VM (doesn't work for Windows Containers).

docker run -it --rm --privileged --pid=host justincormack/nsenter1

more info: https://github.com/justincormack/nsenter1

---

Brainiarc7

Useful Examples of ffmpeg and GNU parallel on the command-line:

Transcoding FLAC music to Opus:

ffmpeg is a highly useful application for converting music and videos. However, audio transcoding is limited to a a single core. If you have a large FLAC archive and you wanted to compress it into the efficient Opus codec, it would take forever with the fastest processor to complete, unless you were to take advantage of all cores in your CPU.

parallel 'ffmpeg -v 0 -i "{}" -c:a libopus -b:a 128k "{.}.opus"' ::: $(find -type f -name '*.flac')

Transcoding Videos to VP9: