Google 공동 작업 개요 및 사용 절차 (TensorFlow 및 GPU를 사용할 수 있음)
지금까지 Anaconda/Miniconda등을 사용해 로컬 환경을 만들고 있었습니다만, 그것조차 불필요하게 된다고는・・・ 문턱의 낮음에 놀라움입니다
기사 "TensorFlow를 Windows에 설치 Python 초보자라도 간단했던 건" 이나 "Windows에서 Miniconda를 사용하여 TensorFlow 환경 구축 (2018 년)" 로 쓴 내용보다 훨씬 간단합니다.
Windows 환경 비교는 기사「Windows PC로 기계 학습 환경을 만드는 방법 정리」에 썼습니다.
감상
좋은 점
GPU를 사용할 수 있습니다!
개선점
로컬 파일의 입출력이 번거롭다. Google 드라이브의 파일을 찾아보고 쓰는 것이 Jupyter Notebook에 비하면 시간이 많이 걸립니다. Google Drive에서 쉽게 파일에 액세스할 수 있습니다! 자세한 내용은 공식 참조 (2019/4/10 추가)
# こうするだけで、マウントできちゃう
from google.colab import drive
drive.mount('/content/gdrive')
# で、ファイル書き込み
with open('/content/gdrive/My Drive/foo.txt', 'w') as f:
f.write('Hello Google Drive!')
!cat /content/gdrive/My\ Drive/foo.txt
절차
1. Google Drive 설정
Google 드라이브에서 모든 폴더에 앱을 추가합니다.
공동체를 찾아 선택합니다.
2. Colaboratory 파일 작성
Colaboratory 파일(Jupyter Notebook 같은 사람)을 작성합니다.
그리고는 파일명을 적당히 바꾸어 코드를 써 실행하는 것입니다. 명령을 쓰고 Shift + Enter로 실행은 Jupyter Notebook과 동일합니다.
x = 1 + 2
print(x)
print x
이렇게 하면 패키지 목록을 확인할 수 있습니다.
!pip freeze
파이썬으로 내보내려면 이런 쓰기 방법입니다.
import pkg_resources
for package in pkg_resources.working_set:
print(package)
런타임에 관하여
기본값은 Python2.7입니다. 따라서 "print x"라고 써도 움직입니다.
메뉴의 「편집 -> 노트북 설정」에서 Python3계로 변경할 수 있습니다(2018/6/15시점에서 Python3.6과 같습니다).
기사 「【초속으로 무료 GPU를 사용한다】 심층 학습 실천 Tips on Colaboratory」 에 상세한 내용이 있으므로, 세세하게 보고 싶은 경우는, 매우 참고가 됩니다.
파일 입출력
Google Drive에서
아래의 코드를 실행하면 인증 페이지에 대한 링크가 출력되므로 인증을 허가하고 취득한 Authorization Code를 입력합니다.
from google.colab import drive
drive.mount('/content/gdrive')
# ファイル書き込み
with open('/content/gdrive/My Drive/foo.txt', 'w') as f:
f.write('Hello Google Drive!')
!cat /content/gdrive/My\ Drive/foo.txt
로컬 PC에서
# show upload dialog
from google.colab import files
uploaded = files.upload()
위 코드에서 로컬 파일을 업로드합니다.
업로드된 파일 이름을 다음 코드에 포함하고 로드합니다.
with open("アップロードされたファイル名") as f:
print(f.read())
덤: 편리한 기능
스크래치 코드 셀
x = 1 + 2
print(x)
print x
!pip freeze
import pkg_resources
for package in pkg_resources.working_set:
print(package)
기본값은 Python2.7입니다. 따라서 "print x"라고 써도 움직입니다.
메뉴의 「편집 -> 노트북 설정」에서 Python3계로 변경할 수 있습니다(2018/6/15시점에서 Python3.6과 같습니다).
기사 「【초속으로 무료 GPU를 사용한다】 심층 학습 실천 Tips on Colaboratory」 에 상세한 내용이 있으므로, 세세하게 보고 싶은 경우는, 매우 참고가 됩니다.
파일 입출력
Google Drive에서
아래의 코드를 실행하면 인증 페이지에 대한 링크가 출력되므로 인증을 허가하고 취득한 Authorization Code를 입력합니다.
from google.colab import drive
drive.mount('/content/gdrive')
# ファイル書き込み
with open('/content/gdrive/My Drive/foo.txt', 'w') as f:
f.write('Hello Google Drive!')
!cat /content/gdrive/My\ Drive/foo.txt
로컬 PC에서
# show upload dialog
from google.colab import files
uploaded = files.upload()
위 코드에서 로컬 파일을 업로드합니다.
업로드된 파일 이름을 다음 코드에 포함하고 로드합니다.
with open("アップロードされたファイル名") as f:
print(f.read())
덤: 편리한 기능
스크래치 코드 셀
from google.colab import drive
drive.mount('/content/gdrive')
# ファイル書き込み
with open('/content/gdrive/My Drive/foo.txt', 'w') as f:
f.write('Hello Google Drive!')
!cat /content/gdrive/My\ Drive/foo.txt
# show upload dialog
from google.colab import files
uploaded = files.upload()
with open("アップロードされたファイル名") as f:
print(f.read())
스크래치 코드 셀
코드 스니펫
양식 항목 추가
덤:2019/4/12 시점에서의 라이브러리 일람
!pip freeze
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==1.9.130
botocore==1.12.130
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==0.1.21
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==1.9.0
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==2.10.1
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==0.4.0
pathlib==1.0.1
patsy==0.5.1
pbr==5.1.3
pexpect==4.7.0
pickleshare==0.7.5
Pillow==4.1.1
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==2.4.0
pyrsistent==0.14.11
pysndfile==1.3.2
PySocks==1.6.8
pystan==2.19.0.0
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==1.0.3
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-git==1.2
Shapely==1.6.4.post2
simplegeneric==0.8.1
six==1.11.0
sklearn==0.0
smart-open==1.8.1
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==1.0.2.dev201904090105
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
widgetsnbextension==3.4.2
wordcloud==1.5.0
wrapt==1.10.11
xarray==0.11.3
xgboost==0.82
xkit==0.0.0
xlrd==1.1.0
xlwt==1.3.0
yellowbrick==0.9.1
zict==0.1.4
zmq==0.0.0
Reference
이 문제에 관하여(Google 공동 작업 개요 및 사용 절차 (TensorFlow 및 GPU를 사용할 수 있음)), 우리는 이곳에서 더 많은 자료를 발견하고 링크를 클릭하여 보았다
https://qiita.com/FukuharaYohei/items/18bc4465923bdda81826
텍스트를 자유롭게 공유하거나 복사할 수 있습니다.하지만 이 문서의 URL은 참조 URL로 남겨 두십시오.
우수한 개발자 콘텐츠 발견에 전념
(Collection and Share based on the CC Protocol.)
!pip freeze
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==1.9.130
botocore==1.12.130
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==0.1.21
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==1.9.0
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==2.10.1
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==0.4.0
pathlib==1.0.1
patsy==0.5.1
pbr==5.1.3
pexpect==4.7.0
pickleshare==0.7.5
Pillow==4.1.1
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==2.4.0
pyrsistent==0.14.11
pysndfile==1.3.2
PySocks==1.6.8
pystan==2.19.0.0
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==1.0.3
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-git==1.2
Shapely==1.6.4.post2
simplegeneric==0.8.1
six==1.11.0
sklearn==0.0
smart-open==1.8.1
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==1.0.2.dev201904090105
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
widgetsnbextension==3.4.2
wordcloud==1.5.0
wrapt==1.10.11
xarray==0.11.3
xgboost==0.82
xkit==0.0.0
xlrd==1.1.0
xlwt==1.3.0
yellowbrick==0.9.1
zict==0.1.4
zmq==0.0.0
Reference
이 문제에 관하여(Google 공동 작업 개요 및 사용 절차 (TensorFlow 및 GPU를 사용할 수 있음)), 우리는 이곳에서 더 많은 자료를 발견하고 링크를 클릭하여 보았다 https://qiita.com/FukuharaYohei/items/18bc4465923bdda81826텍스트를 자유롭게 공유하거나 복사할 수 있습니다.하지만 이 문서의 URL은 참조 URL로 남겨 두십시오.
우수한 개발자 콘텐츠 발견에 전념 (Collection and Share based on the CC Protocol.)