1.すぐに利用したい方へ(as soon as)
「Machine Learning with Swift」By Alexander Sosnovshchenko
http://shop.oreilly.com/product/9781787121515.do
docker
dockerを導入し、Windows, Macではdockerを起動しておいてください。
Windowsでは、BiosでIntel Virtualizationをenableにしないとdockerが起動しない場合があります。
また、セキュリティの警告などが出ることがあります。
docker pull and run
$ docker pull kaizenjapan/scala-karim
$ docker run -it --rm -v `pwd`:/root -p 8888:8888 kaizenjapan/scala-karim /bin/bash
以下のshell sessionでは
root@9f04f98b0ee1:/# は入力促進記号(comman prompt)です。実際には数字の部分が違うかもしれません。この行の#の右側を入力してください。
それ以外の行は出力です。出力にエラー、違いがあれば、コメント欄などでご連絡くださると幸いです。
それぞれの章のフォルダに移動します。
dockerの中と、dockerを起動したOSのシェルとが表示が似ている場合には、どちらで捜査しているか間違えることがあります。dockerの入力促進記号(comman prompt)に気をつけてください。
ファイル共有または複写
dockerとdockerを起動したOSでは、ファイル共有をするか、ファイル複写するかして、生成したファイルをブラウザ等表示させてください。参考文献欄にやり方のURLを記載しています。
複写の場合は、dockerを起動したOS側コマンドを実行しました。お使いのdockerの番号で置き換えてください。複写したファイルをブラウザで表示し内容確認しました。
2_decision_trees/
root@2ee25e04a93d:/SwiftMLBook# ls
10_nlp 12_hardware 14_best_practices 2_decision_trees 4_kmeans 6_linear_regression 8_nn LICENSE pages
11_libs 13_compression 1_intro 3_knn 5_rule_learning 7_logistic 9_cnn README.md
root@2ee25e04a93d:/SwiftMLBook# cd 2_decision_trees/
root@2ee25e04a93d:/SwiftMLBook/2_decision_trees# ls
README.md src supplementary
root@2ee25e04a93d:/SwiftMLBook/2_decision_trees# cd src
root@2ee25e04a93d:/SwiftMLBook/2_decision_trees/src# ls
DecisionTreeDemo ML_Intro.ipynb extraterrestrials.csv supplementary
root@2ee25e04a93d:/SwiftMLBook/2_decision_trees/src# cd DecisionTreeDemo/
root@2ee25e04a93d:/SwiftMLBook/2_decision_trees/src/DecisionTreeDemo# ls
DecisionTreeDemo DecisionTreeDemo.xcodeproj
root@2ee25e04a93d:/SwiftMLBook/2_decision_trees/src/DecisionTreeDemo# ls -al
total 16
drwxr-xr-x 4 root root 4096 Oct 21 20:30 .
drwxr-xr-x 4 root root 4096 Oct 21 20:30 ..
drwxr-xr-x 4 root root 4096 Oct 21 20:30 DecisionTreeDemo
drwxr-xr-x 3 root root 4096 Oct 21 20:30 DecisionTreeDemo.xcodeproj
root@2ee25e04a93d:/SwiftMLBook/2_decision_trees/src/DecisionTreeDemo# cd DecisionTreeDemo
root@2ee25e04a93d:/SwiftMLBook/2_decision_trees/src/DecisionTreeDemo/DecisionTreeDemo# ls
AccuracyMetrics.swift Base.lproj DecisionTree.mlmodel GKDecisionTreeWrapper.swift RandomForest.mlmodel data_test.csv
AppDelegate.swift DataProvider.swift FeaturesLabels.swift Info.plist StreamReader.swift extraterrestrials.csv
Assets.xcassets DataSplitter.swift Flow.swift NumericExtensions.swift ViewController.swift
root@2ee25e04a93d:/SwiftMLBook/2_decision_trees/src/DecisionTreeDemo/DecisionTreeDemo# ls
AccuracyMetrics.swift Base.lproj DecisionTree.mlmodel GKDecisionTreeWrapper.swift RandomForest.mlmodel data_test.csv
AppDelegate.swift DataProvider.swift FeaturesLabels.swift Info.plist StreamReader.swift extraterrestrials.csv
Assets.xcassets DataSplitter.swift Flow.swift NumericExtensions.swift ViewController.swift
root@2ee25e04a93d:/SwiftMLBook/2_decision_trees/src/DecisionTreeDemo/DecisionTreeDemo# swift AccuracyMetrics.swift
root@2ee25e04a93d:/SwiftMLBook/2_decision_trees/src/DecisionTreeDemo/DecisionTreeDemo# swift AppDelegate.swift
AppDelegate.swift:2:8: error: no such module 'UIKit'
import UIKit
^
root@2ee25e04a93d:/SwiftMLBook/2_decision_trees/src/DecisionTreeDemo/DecisionTreeDemo# swift DataProvider.swift
DataProvider.swift:3:8: error: no such module 'GameplayKit'
import GameplayKit
^
root@2ee25e04a93d:/SwiftMLBook/2_decision_trees/src/DecisionTreeDemo/DecisionTreeDemo# swift DataSplitter.swift
DataSplitter.swift:3:8: error: no such module 'GameplayKit'
import GameplayKit
^
root@2ee25e04a93d:/SwiftMLBook/2_decision_trees/src/DecisionTreeDemo/DecisionTreeDemo# swift FeaturesLabels.swift
FeaturesLabels.swift:16:57: error: cannot invoke initializer for type 'Int' with an argument list of type '(Bool)'
return (0..<type(of: self).allValuesCount).map{ Int($0 == rawValue) }
^
FeaturesLabels.swift:16:57: note: overloads for 'Int' exist with these partially matching parameter lists: (Float), (Double), (Float80), (Int64), (Word), (NSNumber), (CGFloat)
return (0..<type(of: self).allValuesCount).map{ Int($0 == rawValue) }
^
root@2ee25e04a93d:/SwiftMLBook/2_decision_trees/src/DecisionTreeDemo/DecisionTreeDemo# swift NumericExtensions.swift
root@2ee25e04a93d:/SwiftMLBook/2_decision_trees/src/DecisionTreeDemo/DecisionTreeDemo# swift StreamReader.swift
root@2ee25e04a93d:/SwiftMLBook/2_decision_trees/src/DecisionTreeDemo/DecisionTreeDemo# swift ViewController.swift
ViewController.swift:2:8: error: no such module 'UIKit'
import UIKit
^
現状の課題
エラー類
2. dockerを自力で構築する方へ
ここから下は、上記のpullしていただいたdockerをどういう方針で、どういう手順で作ったかを記録します。
上記のdockerを利用する上での参考資料です。本の続きを実行する上では必要ありません。
DockerでScala/sbt環境をお手軽に使う
https://qiita.com/yotsak83/items/43cee726d44536208358
ひとまず上記の手順を踏みます。
dockerfileを作る方法ではありません。ごめんなさい。
docker
ubuntu, debianなどのLinuxを、linux, windows, mac osから共通に利用できる仕組み。
利用するOSの設定を変更せずに利用できるのがよい。
同じ仕様で、大量の人が利用することができる。
ソフトウェアの開発元が公式に対応しているものと、利用者が便利に仕立てたものの両方が利用可能である。今回は、公式に配布しているものを、自分で仕立てて、他の人にも利用できるようにする。
ubuntu, debianなどのOSの公式配布,gcc, anacondaなどの言語の公式配布などがある。
これらを利用し、docker-hubに登録することにより、公式配布の質の確認と、変更権を含む幅広い情報の共有ができる。dockerが公式配布するものではなく、それぞれのソフト提供者の公式配布という意味。
2018年10月20日現在、scalaの公式dockerが見つからない。
docker pull and run
OgawaKiyoshi-no-MacBook-Pro:~ ogawakiyoshi$ docker pull swiftdocker/swift
Using default tag: latest
latest: Pulling from swiftdocker/swift
50aff78429b1: Pull complete
f6d82e297bce: Pull complete
275abb2c8a6f: Pull complete
9f15a39356d6: Pull complete
fc0342a94c89: Pull complete
2b53dcb0eee7: Pull complete
267fcb0a26f6: Pull complete
Digest: sha256:0b2ad4a26977a27bedd2cbbae1c8821b3816a7be8b1fb4ad783816be058f8e95
Status: Downloaded newer image for swiftdocker/swift:latest
OgawaKiyoshi-no-MacBook-Pro:~ ogawakiyoshi$ docker run --privileged -i -t --name swiftfun swiftdocker/swift:latest /bin/bash
root@2ee25e04a93d:/# ls
bin boot dev etc home lib lib64 media mnt opt proc root run sbin srv sys tmp usr var
apt-get
root@2ee25e04a93d:/# apt-get update
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Reading package lists... Done
root@2ee25e04a93d:/# apt-get install vim
Reading package lists... Done
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libgpm2 libmpdec2 libpython3.5 libpython3.5-minimal libpython3.5-stdlib vim-common vim-runtime
Suggested packages:
gpm ctags vim-doc vim-scripts vim-gnome-py2 | vim-gtk-py2 | vim-gtk3-py2 | vim-athena-py2 | vim-nox-py2
The following NEW packages will be installed:
libgpm2 libmpdec2 libpython3.5 libpython3.5-minimal libpython3.5-stdlib vim vim-common vim-runtime
0 upgraded, 8 newly installed, 0 to remove and 105 not upgraded.
Need to get 10.4 MB of archives.
After this operation, 49.2 MB of additional disk space will be used.
Do you want to continue? [Y/n] y
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update-alternatives: using /usr/bin/vim.basic to provide /usr/bin/vim (vim) in auto mode
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update-alternatives: using /usr/bin/vim.basic to provide /usr/bin/view (view) in auto mode
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update-alternatives: using /usr/bin/vim.basic to provide /usr/bin/editor (editor) in auto mode
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root@2ee25e04a93d:/# apt-get install -y apt-utils
Reading package lists... Done
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The following additional packages will be installed:
apt libapt-inst2.0 libapt-pkg5.0
Suggested packages:
aptitude | synaptic | wajig apt-doc python-apt
The following NEW packages will be installed:
apt-utils libapt-inst2.0
The following packages will be upgraded:
apt libapt-pkg5.0
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root@2ee25e04a93d:/# apt-get install -y procps
Reading package lists... Done
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Recommended packages:
psmisc
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procps
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debconf: unable to initialize frontend: Dialog
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update-rc.d: warning: start and stop actions are no longer supported; falling back to defaults
root@2ee25e04a93d:/# apt-get install -y sudo
Reading package lists... Done
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The following NEW packages will be installed:
sudo
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debconf: unable to initialize frontend: Dialog
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debconf: falling back to frontend: Readline
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ソース git
root@2ee25e04a93d:/# git clone https://github.com/alexsosn/SwiftMLBook
Cloning into 'SwiftMLBook'...
remote: Enumerating objects: 512, done.
remote: Total 512 (delta 0), reused 0 (delta 0), pack-reused 512
Receiving objects: 100% (512/512), 99.37 MiB | 582.00 KiB/s, done.
Resolving deltas: 100% (130/130), done.
Checking connectivity... done.
root@2ee25e04a93d:/# ls
SwiftMLBook bin boot dev etc home lib lib64 media mnt opt proc root run sbin srv sys tmp usr var
root@2ee25e04a93d:/# cd SwiftMLBook/
docker hubへの登録
$ docker ps
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
2ee25e04a93d swiftdocker/swift:latest "/bin/bash" 15 minutes ago Up 15 minutes swiftfun
$ docker commit 2ee25e04a93d kaizenjapan/swift
sha256:50694f07975d8b8f4f20622ed7e9b240080f6c9ebc8556f79ca6be995ccad9d1
$ docker push kaizenjapan/swift
The push refers to repository [docker.io/kaizenjapan/swift]
4c36ed0a0aae: Pushed
c070c46b781c: Mounted from swiftdocker/swift
dd02019985be: Mounted from swiftdocker/swift
f17fc24fb8d0: Mounted from swiftdocker/swift
6458f770d435: Mounted from swiftdocker/swift
5a876f8f1a3d: Mounted from swiftdocker/swift
d2f8c05d353b: Mounted from swiftdocker/swift
48e0baf45d4d: Pushed
latest: digest: sha256:585e97c6205e3a77b959fc3a4c2ee32c57e6ebd2e53605aaf4970054e48a09a9 size: 1996
参考資料(reference)
swift on docker
swiftdocker/docker-swift
https://github.com/swiftdocker/docker-swift
DockerでSwiftが動くUbuntu環境を立ち上げる
https://qiita.com/clouder/items/867ecb5db2077bc91f9e
Server Side SwiftをDockerコンテナ上で動かしてみる
https://qiita.com/Nonchalant/items/a23949f3e525109a58bc
Swift学習 on Docker for Windows
https://qiita.com/kfjt/items/6a49d603aa497c2807a5
Docker+Ubuntu+Swiftをやってみる
https://qiita.com/AcaiBowl/items/bfd2418b9531a2661fa3
Linux 版 Swift を Mac 上で Docker を使って手っ取り早く試す
https://qiita.com/taketin/items/77af9bc29f44166b8270
Dockerでswift repl起動時にerrorになった場合の対処法
https://qiita.com/atsuya046/items/b84d57ac79b688c018dd
機械学習
なぜdockerで機械学習するか 書籍・ソース一覧作成中 (目標100)
https://qiita.com/kaizen_nagoya/items/ddd12477544bf5ba85e2#_reference-4c0cfe43b25323d43bd3
dockerで機械学習 with anaconda(1)「ゼロから作るDeep Learning - Pythonで学ぶディープラーニングの理論と実装」斎藤 康毅 著
https://qiita.com/kaizen_nagoya/items/a7e94ef6dca128d035ab
dockerで機械学習with anaconda(2)「ゼロから作るDeep Learning2自然言語処理編」斎藤 康毅 著
https://qiita.com/kaizen_nagoya/items/3b80dfc76933cea522c6
dockerで機械学習 with anaconda(3)「直感Deep Learning」Antonio Gulli、Sujit Pal 第1章,第2章
https://qiita.com/kaizen_nagoya/items/483ae708c71c88419c32
dockerで機械学習(71) 環境構築(1) docker どっかーら、どーやってもエラーばっかり。
https://qiita.com/kaizen_nagoya/items/690d806a4760d9b9e040
dockerで機械学習(72) 環境構築(2) Docker for Windows
https://qiita.com/kaizen_nagoya/items/c4daa5cf52e9f0c2c002
dockerで機械学習(73) 環境構築(3) docker/linux/macos bash スクリプト, ms-dos batchファイル
https://qiita.com/kaizen_nagoya/items/3f7b39110b7f303a5558
dockerで機械学習(74) 環境構築(4) R 難関いくつ？
https://qiita.com/kaizen_nagoya/items/5fb44773bc38574bcf1c
dockerで機械学習(75)環境構築(5)docker関連ファイルの管理
https://qiita.com/kaizen_nagoya/items/4f03df9a42c923087b5d
ゼロから作るDeepLearning２自然言語処理編 読書会の進め方（例）
https://qiita.com/kaizen_nagoya/items/025eb3f701b36209302e
環境構築
OpenCVをPythonで動かそうとしてlibGL.soが無いって言われたけど解決した。
https://qiita.com/toshitanian/items/5da24c0c0bd473d514c8
サーバサイドにおけるmatplotlibによる作図Tips
https://qiita.com/TomokIshii/items/3a26ee4453f535a69e9e
Dockerでホストとコンテナ間でのファイルコピー
https://qiita.com/gologo13/items/7e4e404af80377b48fd5
Docker for Mac でファイル共有を利用する
https://qiita.com/seijimomoto/items/1992d68de8baa7e29bb5
「名古屋のIoTは名古屋のOSで」Dockerをどっかーらどうやって使えばいいんでしょう。TOPPERS/FMP on RaspberryPi with Macintosh編 ５つの関門
https://qiita.com/kaizen_nagoya/items/9c46c6da8ceb64d2d7af
64bitCPUへの道 and/or 64歳の決意
https://qiita.com/kaizen_nagoya/items/cfb5ffa24ded23ab3f60
Ubuntu 16.04 LTS で NVIDIA Docker を使ってみる
https://blog.amedama.jp/entry/2017/04/03/235901
文書履歴(document history)
ver. 0.10 初稿 20181022