【秒速で無料GPUを使う】深層学習実践Tips on Colaboratory
【秒速で無料GPUを使う】TensorFow(Keras)/PyTorch/Chainer環境構築 on Colaboratory
・無料GPU
- K80, 連続12hr利用可能
n1-highmem-2 instance
Ubuntu 18.04
2vCPU @ 2.2GHz
13GB RAM
(GPUなし/ TPU)40GB, (GPUあり)360GB Storage
GPU NVIDIA Tesla K80 12GB
アイドル状態が90分続くと停止
連続使用は最大12時間
Notebookサイズは最大20MB
それなりのサイズのdatasetをdisk上に持ってこれる
RAMはそんなにないので、Pythonのarrayでメモリ上に持っておく量は加減が必要
epochで使うdatasetが大量ならbatch毎に読み込むとか
tutorialとかをこなすには十分
ファイル > Python3の新しいノートブック を選ぶ。
画面上部のメニュー ランタイム > ランタイムのタイプを変更 で、 ノートブックの設定 を開く
ハードウェアアクセラレータに GPU を選択し、 保存 する
[+]コード から、コード入力用のセルを追加する
セルに下記を入力
import tensorflow as tf
tf.test.gpu_device_name()
矢印マークで実行
下記が出力されると、正しくGPUがアサインされている
'/device:GPU:0'
Package Version
------------------------ ---------------------
absl-py 0.7.1
alabaster 0.7.12
albumentations 0.1.12
altair 2.4.1
astor 0.7.1
astropy 3.0.5
atari-py 0.1.7
atomicwrites 1.3.0
attrs 19.1.0
audioread 2.1.6
autograd 1.2
Babel 2.6.0
backcall 0.1.0
backports.tempfile 1.0
backports.weakref 1.0.post1
beautifulsoup4 4.6.3
bleach 3.1.0
bokeh 1.0.4
boto 2.49.0
boto3 1.9.128
botocore 1.12.128
Bottleneck 1.2.1
branca 0.3.1
bs4 0.0.1
bz2file 0.98
cachetools 3.1.0
certifi 2019.3.9
cffi 1.12.2
chainer 5.0.0
chardet 3.0.4
Click 7.0
cloudpickle 0.6.1
cmake 3.12.0
colorlover 0.3.0
community 1.0.0b1
contextlib2 0.5.5
convertdate 2.1.3
coverage 3.7.1
coveralls 0.5
crcmod 1.7
cufflinks 0.14.6
cupy-cuda100 5.2.0
cvxopt 1.2.3
cvxpy 1.0.15
cycler 0.10.0
cymem 2.0.2
Cython 0.29.6
cytoolz 0.9.0.1
daft 0.0.4
dask 0.20.2
dataclasses 0.6
datascience 0.10.6
decorator 4.4.0
defusedxml 0.5.0
dill 0.2.9
distributed 1.25.3
Django 2.2
dlib 19.16.0
dm-sonnet 1.23
docopt 0.6.2
docutils 0.14
dopamine-rl 1.0.5
easydict 1.9
ecos 2.0.7.post1
editdistance 0.5.3
en-core-web-sm 2.0.0
entrypoints 0.3
enum34 1.1.6
ephem 3.7.6.0
et-xmlfile 1.0.1
fa2 0.3.5
fancyimpute 0.4.2
fastai 1.0.51
fastcache 1.0.2
fastdtw 0.3.2
fastprogress 0.1.20
fastrlock 0.4
fbprophet 0.4.post2
featuretools 0.4.1
filelock 3.0.10
fix-yahoo-finance 0.0.22
Flask 1.0.2
folium 0.8.3
future 0.16.0
gast 0.2.2
GDAL 2.2.2
gdown 3.6.4
gensim 3.6.0
geographiclib 1.49
geopy 1.17.0
gevent 1.4.0
gin-config 0.1.4
glob2 0.6
google 2.0.2
google-api-core 1.8.2
google-api-python-client 1.6.7
google-auth 1.4.2
google-auth-httplib2 0.0.3
google-auth-oauthlib 0.3.0
google-cloud-bigquery 1.8.1
google-cloud-core 0.29.1
google-cloud-language 1.0.2
google-cloud-storage 1.13.2
google-cloud-translate 1.3.3
google-colab 1.0.0
google-resumable-media 0.3.2
googleapis-common-protos 1.5.9
googledrivedownloader 0.3
graph-nets 1.0.3
graphviz 0.10.1
greenlet 0.4.15
grpcio 1.15.0
gspread 3.0.1
gspread-dataframe 3.0.2
gunicorn 19.9.0
gym 0.10.11
h5py 2.8.0
HeapDict 1.0.0
holidays 0.9.10
html5lib 1.0.1
httpimport 0.5.16
httplib2 0.11.3
humanize 0.5.1
hyperopt 0.1.2
ideep4py 2.0.0.post3
idna 2.6
image 1.5.27
imageio 2.4.1
imagesize 1.1.0
imbalanced-learn 0.4.3
imblearn 0.0
imgaug 0.2.8
imutils 0.5.2
inflect 2.1.0
intel-openmp 2019.0
intervaltree 2.1.0
ipykernel 4.6.1
ipython 5.5.0
ipython-genutils 0.2.0
ipython-sql 0.3.9
ipywidgets 7.4.2
itsdangerous 1.1.0
jdcal 1.4
jedi 0.13.3
jieba 0.39
Jinja2 2.10
jmespath 0.9.4
joblib 0.12.5
jpeg4py 0.1.4
jsonschema 2.6.0
jupyter 1.0.0
jupyter-client 5.2.4
jupyter-console 6.0.0
jupyter-core 4.4.0
kaggle 1.5.3
kapre 0.1.3.1
Keras 2.2.4
Keras-Applications 1.0.7
Keras-Preprocessing 1.0.9
keras-vis 0.4.1
kiwisolver 1.0.1
knnimpute 0.1.0
librosa 0.6.3
lightgbm 2.2.3
llvmlite 0.28.0
lmdb 0.94
lucid 0.3.8
lunardate 0.2.0
lxml 4.2.6
magenta 0.3.19
Markdown 3.1
MarkupSafe 1.1.1
matplotlib 3.0.3
matplotlib-venn 0.11.5
mesh-tensorflow 0.0.5
mido 1.2.6
mir-eval 0.5
missingno 0.4.1
mistune 0.8.4
mkl 2019.0
mlxtend 0.14.0
mock 2.0.0
more-itertools 7.0.0
moviepy 0.2.3.5
mpi4py 3.0.1
mpmath 1.1.0
msgpack 0.5.6
msgpack-numpy 0.4.3.2
multiprocess 0.70.7
multitasking 0.0.7
murmurhash 1.0.2
music21 5.5.0
natsort 5.5.0
nbconvert 5.4.1
nbformat 4.4.0
networkx 2.2
nibabel 2.3.3
nltk 3.2.5
nose 1.3.7
notebook 5.2.2
np-utils 0.5.10.0
numba 0.40.1
numexpr 2.6.9
numpy 1.14.6
nvidia-ml-py3 7.352.0
oauth2client 4.1.3
oauthlib 3.0.1
okgrade 0.4.3
olefile 0.46
opencv-contrib-python 3.4.3.18
opencv-python 3.4.5.20
openpyxl 2.5.9
osqp 0.5.0
packaging 19.0
pandas 0.22.0
pandas-datareader 0.7.0
pandas-gbq 0.4.1
pandas-profiling 1.4.1
pandocfilters 1.4.2
parso 0.3.4
pathlib 1.0.1
patsy 0.5.1
pbr 5.1.3
pexpect 4.6.0
pickleshare 0.7.5
Pillow 4.1.1
pip 19.0.3
pip-tools 3.4.0
plac 0.9.6
plotly 3.6.1
pluggy 0.7.1
portpicker 1.2.0
prefetch-generator 1.0.1
preshed 2.0.1
pretty-midi 0.2.8
prettytable 0.7.2
progressbar2 3.38.0
prometheus-client 0.6.0
promise 2.2.1
prompt-toolkit 1.0.15
protobuf 3.7.1
psutil 5.4.8
psycopg2 2.7.6.1
ptyprocess 0.6.0
py 1.8.0
pyasn1 0.4.5
pyasn1-modules 0.2.4
pycocotools 2.0.0
pycparser 2.19
pydot 1.3.0
pydot-ng 2.0.0
pydotplus 2.0.2
pyemd 0.5.1
pyglet 1.3.2
Pygments 2.1.3
pygobject 3.26.1
pymc3 3.6
pymongo 3.7.2
pymystem3 0.2.0
PyOpenGL 3.1.0
pyparsing 2.3.1
pyrsistent 0.14.11
pysndfile 1.3.2
PySocks 1.6.8
pystan 2.18.1.0
pytest 3.6.4
python-apt 1.6.3+ubuntu1
python-chess 0.23.11
python-dateutil 2.5.3
python-louvain 0.13
python-rtmidi 1.2.1
python-slugify 3.0.2
python-utils 2.3.0
pytz 2018.9
PyWavelets 1.0.2
PyYAML 3.13
pyzmq 17.0.0
qtconsole 4.4.3
regex 2018.1.10
requests 2.18.4
requests-oauthlib 1.2.0
resampy 0.2.1
retrying 1.3.3
rpy2 2.9.5
rsa 4.0
s3fs 0.2.0
s3transfer 0.2.0
scikit-image 0.13.1
scikit-learn 0.20.3
scipy 1.1.0
screen-resolution-extra 0.0.0
scs 2.1.0
seaborn 0.7.1
Send2Trash 1.5.0
setuptools 40.9.0
setuptools-git 1.2
Shapely 1.6.4.post2
simplegeneric 0.8.1
six 1.11.0
sklearn 0.0
smart-open 1.8.0
snowballstemmer 1.2.1
sortedcontainers 2.1.0
spacy 2.0.18
Sphinx 1.8.5
sphinxcontrib-websupport 1.1.0
SQLAlchemy 1.3.2
sqlparse 0.3.0
stable-baselines 2.2.1
statsmodels 0.8.0
sympy 1.1.1
tables 3.4.4
tabulate 0.8.3
tblib 1.3.2
tensor2tensor 1.11.0
tensorboard 1.13.1
tensorboardcolab 0.0.22
tensorflow 1.13.1
tensorflow-estimator 1.13.0
tensorflow-hub 0.4.0
tensorflow-metadata 0.13.0
tensorflow-probability 0.6.0
termcolor 1.1.0
terminado 0.8.2
testpath 0.4.2
text-unidecode 1.2
textblob 0.15.3
textgenrnn 1.4.1
tfds-nightly 1.0.1.dev201904030106
tflearn 0.3.2
Theano 1.0.4
thinc 6.12.1
toolz 0.9.0
torch 1.0.1.post2
torchsummary 1.5.1
torchtext 0.3.1
torchvision 0.2.2.post3
tornado 4.5.3
tqdm 4.28.1
traitlets 4.3.2
tweepy 3.6.0
typing 3.6.6
tzlocal 1.5.1
ujson 1.35
umap-learn 0.3.8
uritemplate 3.0.0
urllib3 1.22
vega-datasets 0.7.0
wcwidth 0.1.7
webencodings 0.5.1
Werkzeug 0.15.2
wheel 0.33.1
widgetsnbextension 3.4.2
wordcloud 1.5.0
wrapt 1.10.11
xarray 0.11.3
xgboost 0.7.post4
xkit 0.0.0
xlrd 1.1.0
xlwt 1.3.0
yellowbrick 0.9.1
zict 0.1.4
zmq 0.0.0
Google colabを開く
https://colab.research.google.com/新規ノートブックの作成
ファイル > Python3の新しいノートブック を選ぶ。
GPUをアサイン
画面上部のメニュー ランタイム > ランタイムのタイプを変更 で、 ノートブックの設定 を開く
ハードウェアアクセラレータに GPU を選択し、 保存 する
GPUが正しくアサインされたか確認
[+]コード から、コード入力用のセルを追加する
セルに下記を入力
import tensorflow as tf
tf.test.gpu_device_name()
矢印マークで実行
下記が出力されると、正しくGPUがアサインされている
'/device:GPU:0'
pythonのバージョン
!pip list
Package Version
------------------------ ---------------------
absl-py 0.7.1
alabaster 0.7.12
albumentations 0.1.12
altair 2.4.1
astor 0.7.1
astropy 3.0.5
atari-py 0.1.7
atomicwrites 1.3.0
attrs 19.1.0
audioread 2.1.6
autograd 1.2
Babel 2.6.0
backcall 0.1.0
backports.tempfile 1.0
backports.weakref 1.0.post1
beautifulsoup4 4.6.3
bleach 3.1.0
bokeh 1.0.4
boto 2.49.0
boto3 1.9.128
botocore 1.12.128
Bottleneck 1.2.1
branca 0.3.1
bs4 0.0.1
bz2file 0.98
cachetools 3.1.0
certifi 2019.3.9
cffi 1.12.2
chainer 5.0.0
chardet 3.0.4
Click 7.0
cloudpickle 0.6.1
cmake 3.12.0
colorlover 0.3.0
community 1.0.0b1
contextlib2 0.5.5
convertdate 2.1.3
coverage 3.7.1
coveralls 0.5
crcmod 1.7
cufflinks 0.14.6
cupy-cuda100 5.2.0
cvxopt 1.2.3
cvxpy 1.0.15
cycler 0.10.0
cymem 2.0.2
Cython 0.29.6
cytoolz 0.9.0.1
daft 0.0.4
dask 0.20.2
dataclasses 0.6
datascience 0.10.6
decorator 4.4.0
defusedxml 0.5.0
dill 0.2.9
distributed 1.25.3
Django 2.2
dlib 19.16.0
dm-sonnet 1.23
docopt 0.6.2
docutils 0.14
dopamine-rl 1.0.5
easydict 1.9
ecos 2.0.7.post1
editdistance 0.5.3
en-core-web-sm 2.0.0
entrypoints 0.3
enum34 1.1.6
ephem 3.7.6.0
et-xmlfile 1.0.1
fa2 0.3.5
fancyimpute 0.4.2
fastai 1.0.51
fastcache 1.0.2
fastdtw 0.3.2
fastprogress 0.1.20
fastrlock 0.4
fbprophet 0.4.post2
featuretools 0.4.1
filelock 3.0.10
fix-yahoo-finance 0.0.22
Flask 1.0.2
folium 0.8.3
future 0.16.0
gast 0.2.2
GDAL 2.2.2
gdown 3.6.4
gensim 3.6.0
geographiclib 1.49
geopy 1.17.0
gevent 1.4.0
gin-config 0.1.4
glob2 0.6
google 2.0.2
google-api-core 1.8.2
google-api-python-client 1.6.7
google-auth 1.4.2
google-auth-httplib2 0.0.3
google-auth-oauthlib 0.3.0
google-cloud-bigquery 1.8.1
google-cloud-core 0.29.1
google-cloud-language 1.0.2
google-cloud-storage 1.13.2
google-cloud-translate 1.3.3
google-colab 1.0.0
google-resumable-media 0.3.2
googleapis-common-protos 1.5.9
googledrivedownloader 0.3
graph-nets 1.0.3
graphviz 0.10.1
greenlet 0.4.15
grpcio 1.15.0
gspread 3.0.1
gspread-dataframe 3.0.2
gunicorn 19.9.0
gym 0.10.11
h5py 2.8.0
HeapDict 1.0.0
holidays 0.9.10
html5lib 1.0.1
httpimport 0.5.16
httplib2 0.11.3
humanize 0.5.1
hyperopt 0.1.2
ideep4py 2.0.0.post3
idna 2.6
image 1.5.27
imageio 2.4.1
imagesize 1.1.0
imbalanced-learn 0.4.3
imblearn 0.0
imgaug 0.2.8
imutils 0.5.2
inflect 2.1.0
intel-openmp 2019.0
intervaltree 2.1.0
ipykernel 4.6.1
ipython 5.5.0
ipython-genutils 0.2.0
ipython-sql 0.3.9
ipywidgets 7.4.2
itsdangerous 1.1.0
jdcal 1.4
jedi 0.13.3
jieba 0.39
Jinja2 2.10
jmespath 0.9.4
joblib 0.12.5
jpeg4py 0.1.4
jsonschema 2.6.0
jupyter 1.0.0
jupyter-client 5.2.4
jupyter-console 6.0.0
jupyter-core 4.4.0
kaggle 1.5.3
kapre 0.1.3.1
Keras 2.2.4
Keras-Applications 1.0.7
Keras-Preprocessing 1.0.9
keras-vis 0.4.1
kiwisolver 1.0.1
knnimpute 0.1.0
librosa 0.6.3
lightgbm 2.2.3
llvmlite 0.28.0
lmdb 0.94
lucid 0.3.8
lunardate 0.2.0
lxml 4.2.6
magenta 0.3.19
Markdown 3.1
MarkupSafe 1.1.1
matplotlib 3.0.3
matplotlib-venn 0.11.5
mesh-tensorflow 0.0.5
mido 1.2.6
mir-eval 0.5
missingno 0.4.1
mistune 0.8.4
mkl 2019.0
mlxtend 0.14.0
mock 2.0.0
more-itertools 7.0.0
moviepy 0.2.3.5
mpi4py 3.0.1
mpmath 1.1.0
msgpack 0.5.6
msgpack-numpy 0.4.3.2
multiprocess 0.70.7
multitasking 0.0.7
murmurhash 1.0.2
music21 5.5.0
natsort 5.5.0
nbconvert 5.4.1
nbformat 4.4.0
networkx 2.2
nibabel 2.3.3
nltk 3.2.5
nose 1.3.7
notebook 5.2.2
np-utils 0.5.10.0
numba 0.40.1
numexpr 2.6.9
numpy 1.14.6
nvidia-ml-py3 7.352.0
oauth2client 4.1.3
oauthlib 3.0.1
okgrade 0.4.3
olefile 0.46
opencv-contrib-python 3.4.3.18
opencv-python 3.4.5.20
openpyxl 2.5.9
osqp 0.5.0
packaging 19.0
pandas 0.22.0
pandas-datareader 0.7.0
pandas-gbq 0.4.1
pandas-profiling 1.4.1
pandocfilters 1.4.2
parso 0.3.4
pathlib 1.0.1
patsy 0.5.1
pbr 5.1.3
pexpect 4.6.0
pickleshare 0.7.5
Pillow 4.1.1
pip 19.0.3
pip-tools 3.4.0
plac 0.9.6
plotly 3.6.1
pluggy 0.7.1
portpicker 1.2.0
prefetch-generator 1.0.1
preshed 2.0.1
pretty-midi 0.2.8
prettytable 0.7.2
progressbar2 3.38.0
prometheus-client 0.6.0
promise 2.2.1
prompt-toolkit 1.0.15
protobuf 3.7.1
psutil 5.4.8
psycopg2 2.7.6.1
ptyprocess 0.6.0
py 1.8.0
pyasn1 0.4.5
pyasn1-modules 0.2.4
pycocotools 2.0.0
pycparser 2.19
pydot 1.3.0
pydot-ng 2.0.0
pydotplus 2.0.2
pyemd 0.5.1
pyglet 1.3.2
Pygments 2.1.3
pygobject 3.26.1
pymc3 3.6
pymongo 3.7.2
pymystem3 0.2.0
PyOpenGL 3.1.0
pyparsing 2.3.1
pyrsistent 0.14.11
pysndfile 1.3.2
PySocks 1.6.8
pystan 2.18.1.0
pytest 3.6.4
python-apt 1.6.3+ubuntu1
python-chess 0.23.11
python-dateutil 2.5.3
python-louvain 0.13
python-rtmidi 1.2.1
python-slugify 3.0.2
python-utils 2.3.0
pytz 2018.9
PyWavelets 1.0.2
PyYAML 3.13
pyzmq 17.0.0
qtconsole 4.4.3
regex 2018.1.10
requests 2.18.4
requests-oauthlib 1.2.0
resampy 0.2.1
retrying 1.3.3
rpy2 2.9.5
rsa 4.0
s3fs 0.2.0
s3transfer 0.2.0
scikit-image 0.13.1
scikit-learn 0.20.3
scipy 1.1.0
screen-resolution-extra 0.0.0
scs 2.1.0
seaborn 0.7.1
Send2Trash 1.5.0
setuptools 40.9.0
setuptools-git 1.2
Shapely 1.6.4.post2
simplegeneric 0.8.1
six 1.11.0
sklearn 0.0
smart-open 1.8.0
snowballstemmer 1.2.1
sortedcontainers 2.1.0
spacy 2.0.18
Sphinx 1.8.5
sphinxcontrib-websupport 1.1.0
SQLAlchemy 1.3.2
sqlparse 0.3.0
stable-baselines 2.2.1
statsmodels 0.8.0
sympy 1.1.1
tables 3.4.4
tabulate 0.8.3
tblib 1.3.2
tensor2tensor 1.11.0
tensorboard 1.13.1
tensorboardcolab 0.0.22
tensorflow 1.13.1
tensorflow-estimator 1.13.0
tensorflow-hub 0.4.0
tensorflow-metadata 0.13.0
tensorflow-probability 0.6.0
termcolor 1.1.0
terminado 0.8.2
testpath 0.4.2
text-unidecode 1.2
textblob 0.15.3
textgenrnn 1.4.1
tfds-nightly 1.0.1.dev201904030106
tflearn 0.3.2
Theano 1.0.4
thinc 6.12.1
toolz 0.9.0
torch 1.0.1.post2
torchsummary 1.5.1
torchtext 0.3.1
torchvision 0.2.2.post3
tornado 4.5.3
tqdm 4.28.1
traitlets 4.3.2
tweepy 3.6.0
typing 3.6.6
tzlocal 1.5.1
ujson 1.35
umap-learn 0.3.8
uritemplate 3.0.0
urllib3 1.22
vega-datasets 0.7.0
wcwidth 0.1.7
webencodings 0.5.1
Werkzeug 0.15.2
wheel 0.33.1
widgetsnbextension 3.4.2
wordcloud 1.5.0
wrapt 1.10.11
xarray 0.11.3
xgboost 0.7.post4
xkit 0.0.0
xlrd 1.1.0
xlwt 1.3.0
yellowbrick 0.9.1
zict 0.1.4
zmq 0.0.0
ubuntuのバージョン確認
!cat /etc/issueUbuntu 18.04.2 LTS \n \l
ディスク容量
!df -h
Filesystem Size Used Avail Use% Mounted on
overlay 359G 23G 318G 7% /
tmpfs 6.4G 0 6.4G 0% /dev
tmpfs 6.4G 0 6.4G 0% /sys/fs/cgroup
tmpfs 6.4G 12K 6.4G 1% /var/colab
/dev/sda1 365G 27G 339G 8% /opt/bin
shm 6.0G 0 6.0G 0% /dev/shm
tmpfs 6.4G 0 6.4G 0% /sys/firmware
RAM容量
!free -h
total used free shared buff/cache available
Mem: 12G 836M 9.9G 2.9M 2.0G 11G
Swap: 0B 0B 0B
CPU情報
!cat /proc/cpuinfo
processor : 0
vendor_id : GenuineIntel
cpu family : 6
model : 63
model name : Intel(R) Xeon(R) CPU @ 2.30GHz
stepping : 0
microcode : 0x1
cpu MHz : 2300.000
cache size : 46080 KB
physical id : 0
siblings : 2
core id : 0
cpu cores : 1
apicid : 0
initial apicid : 0
fpu : yes
fpu_exception : yes
cpuid level : 13
wp : yes
flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology nonstop_tsc cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm abm invpcid_single pti ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid xsaveopt arat arch_capabilities
bugs : cpu_meltdown spectre_v1 spectre_v2 spec_store_bypass l1tf
bogomips : 4600.00
clflush size : 64
cache_alignment : 64
address sizes : 46 bits physical, 48 bits virtual
power management:
processor : 1
vendor_id : GenuineIntel
cpu family : 6
model : 63
model name : Intel(R) Xeon(R) CPU @ 2.30GHz
stepping : 0
microcode : 0x1
cpu MHz : 2300.000
cache size : 46080 KB
physical id : 0
siblings : 2
core id : 0
cpu cores : 1
apicid : 1
initial apicid : 1
fpu : yes
fpu_exception : yes
cpuid level : 13
wp : yes
flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology nonstop_tsc cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm abm invpcid_single pti ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid xsaveopt arat arch_capabilities
bugs : cpu_meltdown spectre_v1 spectre_v2 spec_store_bypass l1tf
bogomips : 4600.00
clflush size : 64
cache_alignment : 64
address sizes : 46 bits physical, 48 bits virtual
power management:
GPU情報
!cat /proc/driver/nvidia/gpus/0000:00:04.0/information
Model: Tesla K80
IRQ: 33
GPU UUID: GPU-b326ec49-f657-ad75-b36d-bf455795f341
Video BIOS: 80.21.25.00.01
Bus Type: PCI
DMA Size: 40 bits
DMA Mask: 0xffffffffff
Bus Location: 0000:00:04.0
Device Minor: 0
Blacklisted: No
from tensorflow.python.client import device_lib
device_lib.list_local_devices()
from tensorflow.python.client import device_lib
device_lib.list_local_devices()
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation: 17679820642583323928, name: "/device:XLA_CPU:0"
device_type: "XLA_CPU"
memory_limit: 17179869184
locality {
}
incarnation: 4994606220071157720
physical_device_desc: "device: XLA_CPU device", name: "/device:XLA_GPU:0"
device_type: "XLA_GPU"
memory_limit: 17179869184
locality {
}
incarnation: 10277020030904524337
physical_device_desc: "device: XLA_GPU device", name: "/device:GPU:0"
device_type: "GPU"
memory_limit: 11276822119
locality {
bus_id: 1
links {
}
}
incarnation: 15587524712171966759
physical_device_desc: "device: 0, name: Tesla K80, pci bus id: 0000:00:04.0, compute capability: 3.7"]
device_lib.list_local_devices()
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation: 17679820642583323928, name: "/device:XLA_CPU:0"
device_type: "XLA_CPU"
memory_limit: 17179869184
locality {
}
incarnation: 4994606220071157720
physical_device_desc: "device: XLA_CPU device", name: "/device:XLA_GPU:0"
device_type: "XLA_GPU"
memory_limit: 17179869184
locality {
}
incarnation: 10277020030904524337
physical_device_desc: "device: XLA_GPU device", name: "/device:GPU:0"
device_type: "GPU"
memory_limit: 11276822119
locality {
bus_id: 1
links {
}
}
incarnation: 15587524712171966759
physical_device_desc: "device: 0, name: Tesla K80, pci bus id: 0000:00:04.0, compute capability: 3.7"]
CUDAバージョン
!nvcc --versionnvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2018 NVIDIA Corporation
Built on Sat_Aug_25_21:08:01_CDT_2018
Cuda compilation tools, release 10.0, V10.0.130
アサインGPU、Driverの確認
!nvidia-smi
Sun Apr 7 22:29:01 2019
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 418.56 Driver Version: 410.79 CUDA Version: 10.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 Tesla K80 Off | 00000000:00:04.0 Off | 0 |
| N/A 47C P0 54W / 149W | 121MiB / 11441MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
+-----------------------------------------------------------------------------+
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