Andrew Kane ankane

## idea1.rb
require "bundler/inline"

gemfile do
  source "https://rubygems.org"

  gem "activerecord", require: "active_record"
  gem "neighbor", github: "ankane/neighbor"
  gem "pg"
end

## output.txt
# CREATE INDEX output omitted
psql:repro.sql:8: INFO:  vector_l2_squared_distance
psql:repro.sql:8: INFO:  vector_l2_squared_distance
psql:repro.sql:8: INFO:  vector_l2_squared_distance
psql:repro.sql:8: INFO:  vector_l2_squared_distance
psql:repro.sql:8: INFO:  vector_l2_squared_distance
psql:repro.sql:8: INFO:  l2_distance
psql:repro.sql:8: INFO:  l2_distance
 id
----

## pr-180-aarch64.txt
Machine: r7g.large
Dataset: gist-960
Lists: 1000

IP today

INFO:  k-means: 46822.401 ms
INFO:  assign tuples: 253000.270 ms

IP PR

## elasticsearch.rb
require "active_record"
require "disco"
require "elasticsearch"
require "searchkick"

ActiveRecord::Base.establish_connection adapter: "sqlite3", database: ":memory:"
ActiveRecord::Schema.verbose = false
ActiveRecord::Schema.define do
  create_table :movies do |t|
    t.string :name

## detect_objects.php
<?php

require_once __DIR__ . '/../vendor/autoload.php';

function getPixels($img)
{
    $pixels = [];
    $width = imagesx($img);
    $height = imagesy($img);
    for ($y = 0; $y < $height; $y++) {

## pgsync_repro.sh
createdb pgsync_repro1
createdb pgsync_repro2

psql pgsync_repro1 << SQL
CREATE TABLE posts (
  id BIGINT PRIMARY KEY,
  linked_post_id BIGINT,
  FOREIGN KEY (linked_post_id) REFERENCES posts (id)
);
INSERT INTO posts VALUES (1, NULL), (2, 1);

## lockbox_repro.rb
require "bundler/inline"

gemfile do
  source "https://rubygems.org"

  gem "activerecord", require: "active_record"
  gem "sqlite3"
  gem "lockbox", git: "https://github.com/ankane/lockbox.git"
end

## data.csv

          
            1
            3.7
            1.2
            7.2
            9

            
              1
              7.5
              0.5
              7.9
              0

            
              1
              1.6
              0.1
              7.6
              7

            
              0
              0.6
              2.5
              5.0
              4

            
              1
              1.8
              8.4
              1.1
              2

            
              2
              6.8
              8.7
              8.7
              9

            
              2
              9.4
              9.6
              8.6
              9

            
              1
              0.9
              0.7
              6.3
              6

            
              0
              5.7
              0.1
              0.0
              1

            
              1
              0.8
              8.8
              1.3
              3

## bootstrap_ami.sh
# Bootstrap AWS Deep Learning Base AMI (Ubuntu 18.04)

# install Ruby
sudo snap install ruby --classic

# install LibTorch
wget -O libtorch.zip https://download.pytorch.org/libtorch/cu102/libtorch-cxx11-abi-shared-with-deps-1.7.0.zip
unzip libtorch.zip

# download

## emotion_recognition.rb
# https://github.com/onnx/models/tree/master/vision/body_analysis/emotion_ferplus
require "onnxruntime"
require "mini_magick"

img = MiniMagick::Image.open("ranger.jpg")
img.crop "100x100+60+20", "-gravity", "center"
img.resize "64x64^", "-gravity", "center", "-extent", "64x64"
img.colorspace "Gray"
img.write("resized.jpg")
	require "bundler/inline"

	gemfile do
	source "https://rubygems.org"

	gem "activerecord", require: "active_record"
	gem "neighbor", github: "ankane/neighbor"
	gem "pg"
	end
	# CREATE INDEX output omitted
	psql:repro.sql:8: INFO: vector_l2_squared_distance
	psql:repro.sql:8: INFO: vector_l2_squared_distance
	psql:repro.sql:8: INFO: vector_l2_squared_distance
	psql:repro.sql:8: INFO: vector_l2_squared_distance
	psql:repro.sql:8: INFO: vector_l2_squared_distance
	psql:repro.sql:8: INFO: l2_distance
	psql:repro.sql:8: INFO: l2_distance
	id
	----
	Machine: r7g.large
	Dataset: gist-960
	Lists: 1000

	IP today

	INFO: k-means: 46822.401 ms
	INFO: assign tuples: 253000.270 ms

	IP PR
	require "active_record"
	require "disco"
	require "elasticsearch"
	require "searchkick"

	ActiveRecord::Base.establish_connection adapter: "sqlite3", database: ":memory:"
	ActiveRecord::Schema.verbose = false
	ActiveRecord::Schema.define do
	create_table :movies do \|t\|
	t.string :name
	<?php

	require_once __DIR__ . '/../vendor/autoload.php';

	function getPixels($img)
	{
	$pixels = [];
	$width = imagesx($img);
	$height = imagesy($img);
	for ($y = 0; $y < $height; $y++) {
	createdb pgsync_repro1
	createdb pgsync_repro2

	psql pgsync_repro1 << SQL
	CREATE TABLE posts (
	id BIGINT PRIMARY KEY,
	linked_post_id BIGINT,
	FOREIGN KEY (linked_post_id) REFERENCES posts (id)
	);
	INSERT INTO posts VALUES (1, NULL), (2, 1);
1	3.7	1.2	7.2	9
1	7.5	0.5	7.9	0
1	1.6	0.1	7.6	7
0	0.6	2.5	5.0	4
1	1.8	8.4	1.1	2
2	6.8	8.7	8.7	9
2	9.4	9.6	8.6	9
1	0.9	0.7	6.3	6
0	5.7	0.1	0.0	1
1	0.8	8.8	1.3	3
	# Bootstrap AWS Deep Learning Base AMI (Ubuntu 18.04)

	# install Ruby
	sudo snap install ruby --classic

	# install LibTorch
	wget -O libtorch.zip https://download.pytorch.org/libtorch/cu102/libtorch-cxx11-abi-shared-with-deps-1.7.0.zip
	unzip libtorch.zip

	# download
	# https://github.com/onnx/models/tree/master/vision/body_analysis/emotion_ferplus
	require "onnxruntime"
	require "mini_magick"

	img = MiniMagick::Image.open("ranger.jpg")
	img.crop "100x100+60+20", "-gravity", "center"
	img.resize "64x64^", "-gravity", "center", "-extent", "64x64"
	img.colorspace "Gray"
	img.write("resized.jpg")