macOS Mojave で Chainer 環境構築
macOS Mojave で Chainer 環境構築
使用環境
$ sw_vers ProductName: Mac OS X ProductVersion: 10.14.5 BuildVersion: 18F132
Install Python
3.7.3 is the latest.
$ python3 --version Python 3.7.3
Create virtual environment.
$ python3 -m venv . $ source bin/activate
Install Chainer
Installation — Chainer 6.0.0 documentation
$ pip install -U setuptools pip $ pip install chainer
$ pip freeze cached-property==1.5.1 chainer==6.0.0 chainerrl==0.6.0 cycler==0.10.0 filelock==3.0.12 future==0.17.1 graphviz==0.11 gym==0.12.5 kiwisolver==1.1.0 matplotlib==3.1.0 numpy==1.16.4 Pillow==6.0.0 protobuf==3.7.1 pyglet==1.3.2 pyparsing==2.4.0 python-dateutil==2.8.0 scipy==1.3.0 six==1.12.0 typing==3.6.6 typing-extensions==3.7.2
Run the MNIST example
chainer/examples/mnist at v6.0.0 · chainer/chainer · GitHub
$ python train_mnist.py ./lib/python3.7/site-packages/chainer/_environment_check.py:41: UserWarning: Accelerate has been detected as a NumPy backend library. vecLib, which is a part of Accelerate, is known not to work correctly with Chainer. We recommend using other BLAS libraries such as OpenBLAS. For details of the issue, please see https://docs.chainer.org/en/stable/tips.html#mnist-example-does-not-converge-in-cpu-mode-on-mac-os-x. Please be aware that Mac OS X is not an officially supported OS. ''') # NOQA Device: @numpy # unit: 1000 # Minibatch-size: 100 # epoch: 20 Downloading from http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz... Downloading from http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz... Downloading from http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz... Downloading from http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz... epoch main/loss validation/main/loss main/accuracy validation/main/accuracy elapsed_time 1 0.190276 0.0994537 0.942633 0.9698 23.8376 2 0.0747232 0.0705411 0.976717 0.9778 47.7668 3 0.0487931 0.0757109 0.984167 0.9769 72.6437 4 0.0366443 0.0786135 0.988367 0.9765 98.4305 5 0.0273172 0.0694717 0.991467 0.981 125.23 6 0.0218385 0.108687 0.99275 0.9726 153.306 7 0.0198589 0.0779753 0.993367 0.9791 188.598 8 0.0186954 0.0732773 0.993783 0.9823 218.851 9 0.0176328 0.0889091 0.994433 0.9785 249.011 10 0.0142019 0.0829101 0.995233 0.9814 279.932 11 0.0121828 0.113355 0.996433 0.9776 311.948 12 0.0144403 0.0905099 0.995367 0.9808 344.985 13 0.0137652 0.0838266 0.996067 0.9833 379.64 14 0.00821494 0.117748 0.997517 0.9802 413.659 15 0.0132004 0.109114 0.996067 0.9817 449.17 16 0.0143113 0.112049 0.995533 0.9804 485.779 17 0.00892646 0.0957723 0.997017 0.9831 523.138 18 0.00662617 0.104108 0.998117 0.9817 564.709 19 0.00824879 0.12197 0.99755 0.9808 604.888 20 0.0157249 0.111977 0.995883 0.9829 645.684
There is a warning message.
./lib/python3.7/site-packages/chainer/_environment_check.py:41: UserWarning: Accelerate has been detected as a NumPy backend library. vecLib, which is a part of Accelerate, is known not to work correctly with Chainer. We recommend using other BLAS libraries such as OpenBLAS. For details of the issue, please see https://docs.chainer.org/en/stable/tips.html#mnist-example-does-not-converge-in-cpu-mode-on-mac-os-x.
Need to install NumPy separately. Let's try with Anaconda.
$ conda create --name condachainer pip $ conda activate condachainer $ pip install -U setuptools pip $ pip install chainer
$ conda env export
name: condachainer
channels:
- defaults
dependencies:
- blas=1.0=mkl
- ca-certificates=2019.5.15=0
- certifi=2019.6.16=py37_0
- cycler=0.10.0=py37_0
- freetype=2.9.1=hb4e5f40_0
- intel-openmp=2019.4=233
- kiwisolver=1.1.0=py37h0a44026_0
- libcxx=4.0.1=hcfea43d_1
- libcxxabi=4.0.1=hcfea43d_1
- libedit=3.1.20181209=hb402a30_0
- libffi=3.2.1=h475c297_4
- libgfortran=3.0.1=h93005f0_2
- libpng=1.6.37=ha441bb4_0
- matplotlib=3.1.0=py37h54f8f79_0
- mkl=2019.4=233
- mkl_fft=1.0.12=py37h5e564d8_0
- mkl_random=1.0.2=py37h27c97d8_0
- ncurses=6.1=h0a44026_1
- numpy-base=1.16.4=py37h6575580_0
- openssl=1.1.1c=h1de35cc_1
- pip=19.1.1=py37_0
- pyparsing=2.4.0=py_0
- python=3.7.3=h359304d_0
- python-dateutil=2.8.0=py37_0
- pytz=2019.1=py_0
- readline=7.0=h1de35cc_5
- setuptools=41.0.1=py37_0
- sqlite=3.28.0=ha441bb4_0
- tk=8.6.8=ha441bb4_0
- tornado=6.0.2=py37h1de35cc_0
- wheel=0.33.4=py37_0
- xz=5.2.4=h1de35cc_4
- zlib=1.2.11=h1de35cc_3
- pip:
- chainer==6.1.0
- filelock==3.0.12
- numpy==1.16.4
- protobuf==3.7.1
- six==1.12.0
- typing==3.6.6
- typing-extensions==3.6.6
prefix: ~/anaconda3/envs/condachainer
Releases · chainer/chainer · GitHub
v6.1.0 @beam2d beam2d released this 20 hours ago
Oh...never mind.
$ python train_mnist.py Device: @numpy # unit: 1000 # Minibatch-size: 100 # epoch: 20 epoch main/loss validation/main/loss main/accuracy validation/main/accuracy elapsed_time 1 0.189819 0.0923269 0.942533 0.9721 18.4105 2 0.0730058 0.0963992 0.97735 0.9696 38.9289 3 0.0507709 0.0681645 0.983517 0.9796 60.7336 4 0.0357853 0.0733023 0.988467 0.9784 83.1306 5 0.0286872 0.082298 0.990917 0.979 106.233 6 0.0228451 0.0738484 0.99235 0.9806 131.034 7 0.0206049 0.0837659 0.993467 0.9796 155.578 8 0.0200223 0.0870863 0.993383 0.98 180.522 9 0.0133957 0.0855648 0.995667 0.9831 206.545 10 0.0175329 0.0806837 0.994467 0.982 233.34 11 0.0119728 0.0871093 0.99595 0.9829 260.76 12 0.0110821 0.0840505 0.996633 0.9829 288.536 13 0.0158595 0.0899242 0.995533 0.9823 317.186 14 0.00708507 0.104456 0.99755 0.982 347.658 15 0.0122286 0.0986352 0.996533 0.9806 376.948 16 0.0142947 0.107316 0.995783 0.9815 406.64 17 0.00880313 0.114419 0.9972 0.9815 438.935 18 0.00582421 0.0949353 0.998267 0.9826 471.025 19 0.00788875 0.123834 0.997783 0.9814 504.499 20 0.0126048 0.10169 0.996483 0.9816 539.86
1.2x - 1.3x faster than before.
その他
Install -> お試し実行で warning -> Anaconda 使って再度 install -> してる間に Chainer のバージョンが上がる、というオチまでついて環境構築完了。
Chainer は日本発のフレームワークということで色々期待が持てるが Mac はあまり積極的にはサポートされていないので最初っから Ubuntu 用意した方が良かったかもしれない。
