Curt-Park

ScottTodd

Goal: built mlir-opt through emscripten to run it interactively from documentation websites.

References:

• Install emsdk: https://emscripten.org/docs/getting_started/downloads.html
• Read https://emscripten.org/docs/compiling/Building-Projects.html
• LLVM cross compilation: https://llvm.org/docs/HowToCrossCompileLLVM.html
• LLVM CMake options: https://llvm.org/docs/CMake.html

Notes:

vreality64

# Show all node_modules folder information in current working directory
alias show-all-node-modules="find . -name 'node_modules' -type d -prune -print | xargs du -chs"

# Remove all node_modules folder in current working directory
alias remove-all-node-modules="show-all-node-modules && find . -name 'node_modules' -type d -prune -print -exec rm -rf '{}' \;"

tucan9389

# Usage: 
# command  
# `sh gifconverter.sh /Users/canapio/Desktop/turtle_DEMO_004_4.MP4` 
# on mac

# some configuration
width="240"
fps="12"

# path setup

mkocabas

mkdir coco
cd coco
mkdir images
cd images

wget http://images.cocodataset.org/zips/train2017.zip
wget http://images.cocodataset.org/zips/val2017.zip
wget http://images.cocodataset.org/zips/test2017.zip
wget http://images.cocodataset.org/zips/unlabeled2017.zip

lattner

Swift Concurrency Manifesto

Author: Chris Lattner

Chinese Translation by Jason Yu

Contents

• Introduction
• Overall Vision

omimo

# Create a simple TF Graph 
# By Omid Alemi - Jan 2017
# Works with TF <r1.0

import tensorflow as tf

I = tf.placeholder(tf.float32, shape=[None,3], name='I') # input
W = tf.Variable(tf.zeros_initializer(shape=[3,2]), dtype=tf.float32, name='W') # weights
b = tf.Variable(tf.zeros_initializer(shape=[2]), dtype=tf.float32, name='b') # biases
O = tf.nn.relu(tf.matmul(I, W) + b, name='O') # activation / output

rgl

bash -c 'while [[ "$(curl -s -o /dev/null -w ''%{http_code}'' localhost:9000)" != "200" ]]; do sleep 5; done'

# also check https://gist.github.com/rgl/c2ba64b7e2a5a04d1eb65983995dce76