Databricks Runtime 8.2 pour ML (EoS)
Remarque
La prise en charge de cette version databricks Runtime a pris fin. Pour connaître la date de fin de support, consultez l’historique de fin de support. Pour toutes les versions prises en charge de Databricks Runtime, consultez Notes de publication sur les versions et la compatibilité de Databricks Runtime.
Databricks a publié cette version en avril 2021.
Databricks Runtime 8.2 for Machine Learning fournit un environnement prêt à l'emploi pour l'apprentissage automatique et la science des données basé sur Databricks Runtime 8.2 (EoS). Databricks Runtime ML contient de nombreuses bibliothèques populaires de Machine Learning, notamment TensorFlow, PyTorch et XGBoost. Il prend également en charge la formation de Deep Learning distribué avec Horovod.
Pour plus d’informations, y compris les instructions relatives à la création d’un cluster Databricks Runtime ML, consultez IA et machine learning sur Databricks.
Nouvelles fonctionnalités et modifications majeures
Databricks Runtime 8.2 ML s’appuie sur Databricks Runtime 8.2 . Pour plus d’informations sur les nouveautés dans Databricks Runtime 8.2, notamment Apache Spark MLlib et SparkR, consultez les notes de publication sur Databricks Runtime 8.2 (EoS).
Changements importants apportés à l’environnement Python de Databricks Runtime ML
Consultez Databricks Runtime 8.2 (EoS) pour connaître les modifications majeures apportées à l’environnement Databricks Runtime Python. Pour obtenir la liste complète des packages Python installés et leurs versions, consultez Bibliothèques Python.
Mise à niveau des packages Python
- databricks-cli 0.14.1 -> 0.14.3
- horovod 0.21.1 -> 0.21.3
- koalas 1.6.0 -> 1.7.0
- mlflow 1.14.1 -> 1.15.0
- shap 0.38.1 -> 0.39.0
- torch 1.7.1 -> 1.8.1
- torchvision 0.8.2 -> 0.9.1
Ajout de packages Python
- pandas-profiling: 2.11.0
Environnement du système
L’environnement système de Databricks Runtime 8.2 ML diffère de Databricks Runtime 8.2 comme suit :
- DBUtils : Databricks Runtime ML n’inclut pas L’Utilitaire de bibliothèque (dbutils.library) (hérité).
Utilisez plutôt les commandes
%pip
et%conda
. Consultez Bibliothèques Python délimitées à un notebook. - Pour les clusters GPU, Databricks Runtime ML inclut les bibliothèques GPU NVIDIA suivantes :
- CUDA==11.0
- cuDNN 8.0.4.30
- NCCL 2.7.8
- TensorRT 7.1.3
Bibliothèques
Les sections suivantes répertorient les bibliothèques incluses dans Databricks Runtime ML 8.2 qui diffèrent de celles incluses dans Databricks Runtime 8.2.
Dans cette section :
- Bibliothèques de niveau supérieur
- Bibliothèques Python
- Bibliothèques R
- Bibliothèques Java et Scala (cluster Scala 2.12)
Bibliothèques de niveau supérieur
Databricks Runtime 8.2 ML comprend les bibliothèquesde niveau supérieur suivantes :
- GraphFrames
- Horovod et HorovodRunner
- MLflow
- PyTorch
- spark-tensorflow-connector
- TensorFlow
- TensorBoard
Bibliothèques Python
Databricks Runtime 8.2 ML utilise conda pour la gestion des packages Python et comprend de nombreux packages ML populaires.
En plus des packages spécifiés dans les environnements conda dans les sections suivantes, Databricks Runtime 8.2 ML comprend également les packages suivants :
- hyperopt 0.2.5.db1
- sparkdl 2.1.0.db4
Bibliothèques Python sur les clusters UC
name: databricks-ml
channels:
- pytorch
- defaults
dependencies:
- _libgcc_mutex=0.1=main
- absl-py=0.11.0=pyhd3eb1b0_1
- aiohttp=3.7.4=py38h27cfd23_1
- asn1crypto=1.4.0=py_0
- astor=0.8.1=py38h06a4308_0
- async-timeout=3.0.1=py38h06a4308_0
- attrs=20.3.0=pyhd3eb1b0_0
- backcall=0.2.0=pyhd3eb1b0_0
- bcrypt=3.2.0=py38h7b6447c_0
- blas=1.0=mkl
- blinker=1.4=py38h06a4308_0
- boto3=1.16.7=pyhd3eb1b0_0
- botocore=1.19.7=pyhd3eb1b0_0
- brotlipy=0.7.0=py38h27cfd23_1003
- bzip2=1.0.8=h7b6447c_0
- c-ares=1.17.1=h27cfd23_0
- ca-certificates=2021.4.13=h06a4308_1 # (updated from 2021.1.19 in May 26, 2021 maintenance update)
- cachetools=4.2.1=pyhd3eb1b0_0
- certifi=2020.12.5=py38h06a4308_0
- cffi=1.14.3=py38h261ae71_2
- chardet=3.0.4=py38h06a4308_1003
- click=7.1.2=pyhd3eb1b0_0
- cloudpickle=1.6.0=py_0
- configparser=5.0.1=py_0
- cpuonly=1.0=0
- cryptography=3.1.1=py38h1ba5d50_0
- cycler=0.10.0=py38_0
- cython=0.29.21=py38h2531618_0
- decorator=4.4.2=pyhd3eb1b0_0
- dill=0.3.2=py_0
- docutils=0.15.2=py38h06a4308_1
- entrypoints=0.3=py38_0
- ffmpeg=4.2.2=h20bf706_0
- flask=1.1.2=pyhd3eb1b0_0
- freetype=2.10.4=h5ab3b9f_0
- future=0.18.2=py38_1
- gitdb=4.0.5=py_0
- gitpython=3.1.12=pyhd3eb1b0_1
- gmp=6.1.2=h6c8ec71_1
- gnutls=3.6.5=h71b1129_1002
- google-auth=1.22.1=py_0
- google-auth-oauthlib=0.4.2=pyhd3eb1b0_2
- google-pasta=0.2.0=py_0
- gunicorn=20.0.4=py38h06a4308_0
- h5py=2.10.0=py38h7918eee_0
- hdf5=1.10.4=hb1b8bf9_0
- icu=58.2=he6710b0_3
- idna=2.10=pyhd3eb1b0_0
- importlib-metadata=2.0.0=py_1
- intel-openmp=2019.4=243
- ipykernel=5.3.4=py38h5ca1d4c_0
- ipython=7.19.0=py38hb070fc8_1
- ipython_genutils=0.2.0=pyhd3eb1b0_1
- isodate=0.6.0=py_1
- itsdangerous=1.1.0=pyhd3eb1b0_0
- jedi=0.17.2=py38h06a4308_1
- jinja2=2.11.2=pyhd3eb1b0_0
- jmespath=0.10.0=py_0
- joblib=0.17.0=py_0
- jpeg=9b=h024ee3a_2
- jupyter_client=6.1.7=py_0
- jupyter_core=4.6.3=py38_0
- kiwisolver=1.3.0=py38h2531618_0
- krb5=1.17.1=h173b8e3_0
- lame=3.100=h7b6447c_0
- lcms2=2.11=h396b838_0
- ld_impl_linux-64=2.33.1=h53a641e_7
- libedit=3.1.20191231=h14c3975_1
- libffi=3.3=he6710b0_2
- libgcc-ng=9.1.0=hdf63c60_0
- libgfortran-ng=7.3.0=hdf63c60_0
- libopus=1.3.1=h7b6447c_0
- libpng=1.6.37=hbc83047_0
- libpq=12.2=h20c2e04_0
- libprotobuf=3.13.0.1=hd408876_0
- libsodium=1.0.18=h7b6447c_0
- libstdcxx-ng=9.1.0=hdf63c60_0
- libtiff=4.1.0=h2733197_1
- libuv=1.40.0=h7b6447c_0
- libvpx=1.7.0=h439df22_0
- lightgbm=3.1.1=py38h2531618_0
- lz4-c=1.9.2=heb0550a_3
- mako=1.1.3=py_0
- markdown=3.3.3=py38h06a4308_0
- markupsafe=1.1.1=py38h7b6447c_0
- matplotlib-base=3.2.2=py38hef1b27d_0
- mkl=2019.4=243
- mkl-service=2.3.0=py38he904b0f_0
- mkl_fft=1.2.0=py38h23d657b_0
- mkl_random=1.1.0=py38h962f231_0
- more-itertools=8.6.0=pyhd3eb1b0_0
- multidict=5.1.0=py38h27cfd23_2
- ncurses=6.2=he6710b0_1
- nettle=3.4.1=hbb512f6_0
- networkx=2.5=py_0
- ninja=1.10.2=py38hff7bd54_0
- nltk=3.5=py_0
- numpy=1.19.2=py38h54aff64_0
- numpy-base=1.19.2=py38hfa32c7d_0
- oauthlib=3.1.0=py_0
- olefile=0.46=py_0
- openh264=2.1.0=hd408876_0
- openssl=1.1.1k=h27cfd23_0 # (updated from 1.1.1i in May 26, 2021 maintenance update)
- packaging=20.4=py_0
- pandas=1.1.3=py38he6710b0_0
- paramiko=2.7.2=py_0
- parso=0.7.0=py_0
- patsy=0.5.1=py38_0
- pexpect=4.8.0=pyhd3eb1b0_3
- pickleshare=0.7.5=pyhd3eb1b0_1003
- pillow=8.0.1=py38he98fc37_0
- pip=20.2.4=py38h06a4308_0
- plotly=4.14.3=pyhd3eb1b0_0
- prompt-toolkit=3.0.8=py_0
- prompt_toolkit=3.0.8=0
- protobuf=3.13.0.1=py38he6710b0_1
- psutil=5.7.2=py38h7b6447c_0
- psycopg2=2.8.5=py38h3c74f83_1
- ptyprocess=0.6.0=pyhd3eb1b0_2
- pyasn1=0.4.8=py_0
- pyasn1-modules=0.2.8=py_0
- pycparser=2.20=py_2
- pygments=2.7.2=pyhd3eb1b0_0
- pyjwt=1.7.1=py38_0
- pynacl=1.4.0=py38h7b6447c_1
- pyodbc=4.0.30=py38he6710b0_0
- pyopenssl=19.1.0=pyhd3eb1b0_1
- pyparsing=2.4.7=pyhd3eb1b0_0
- pysocks=1.7.1=py38h06a4308_0
- python=3.8.8=hdb3f193_4 # (updated from 3.8.5 in May 26, 2021 maintenance update)
- python-dateutil=2.8.1=pyhd3eb1b0_0
- python-editor=1.0.4=py_0
- pytorch=1.8.1=py3.8_cpu_0
- pytz=2020.5=pyhd3eb1b0_0
- pyzmq=19.0.2=py38he6710b0_1
- readline=8.0=h7b6447c_0
- regex=2020.10.15=py38h7b6447c_0
- requests=2.24.0=py_0
- requests-oauthlib=1.3.0=py_0
- retrying=1.3.3=py_2
- rsa=4.7.2=pyhd3eb1b0_1
- s3transfer=0.3.6=pyhd3eb1b0_0
- scikit-learn=0.23.2=py38h0573a6f_0
- scipy=1.5.2=py38h0b6359f_0
- setuptools=50.3.1=py38h06a4308_1
- simplejson=3.17.2=py38h27cfd23_2
- six=1.15.0=py38h06a4308_0
- smmap=3.0.5=pyhd3eb1b0_0
- sqlite=3.33.0=h62c20be_0
- sqlparse=0.4.1=py_0
- statsmodels=0.12.0=py38h7b6447c_0
- tabulate=0.8.7=py38h06a4308_0
- threadpoolctl=2.1.0=pyh5ca1d4c_0
- tk=8.6.10=hbc83047_0
- torchvision=0.9.1=py38_cpu
- tornado=6.0.4=py38h7b6447c_1
- tqdm=4.50.2=py_0
- traitlets=5.0.5=pyhd3eb1b0_0
- typing-extensions=3.7.4.3=hd3eb1b0_0
- typing_extensions=3.7.4.3=pyh06a4308_0
- unixodbc=2.3.9=h7b6447c_0
- urllib3=1.25.11=py_0
- wcwidth=0.2.5=py_0
- websocket-client=0.57.0=py38_2
- werkzeug=1.0.1=pyhd3eb1b0_0
- wheel=0.35.1=pyhd3eb1b0_0
- wrapt=1.12.1=py38h7b6447c_1
- x264=1!157.20191217=h7b6447c_0
- xz=5.2.5=h7b6447c_0
- yarl=1.6.3=py38h27cfd23_0
- zeromq=4.3.3=he6710b0_3
- zipp=3.4.0=pyhd3eb1b0_0
- zlib=1.2.11=h7b6447c_3
- zstd=1.4.5=h9ceee32_0
- pip:
- argon2-cffi==20.1.0
- astunparse==1.6.3
- async-generator==1.10
- azure-core==1.11.0
- azure-storage-blob==12.7.1
- bleach==3.3.0
- confuse==1.4.0
- databricks-cli==0.14.3
- defusedxml==0.7.1
- diskcache==5.2.1
- docker==4.4.4
- flatbuffers==1.12
- gast==0.3.3
- grpcio==1.32.0
- horovod==0.21.3
- htmlmin==0.1.12
- imagehash==4.2.0
- ipywidgets==7.6.3
- joblibspark==0.3.0
- jsonschema==3.2.0
- jupyterlab-pygments==0.1.2
- jupyterlab-widgets==1.0.0
- keras-preprocessing==1.1.2
- koalas==1.7.0
- llvmlite==0.36.0
- missingno==0.4.2
- mistune==0.8.4
- mleap==0.16.1
- mlflow-skinny==1.15.0
- msrest==0.6.21
- nbclient==0.5.3
- nbconvert==6.0.7
- nbformat==5.1.2
- nest-asyncio==1.5.1
- notebook==6.3.0
- numba==0.53.1
- opt-einsum==3.3.0
- pandas-profiling==2.11.0
- pandocfilters==1.4.3
- petastorm==0.9.8
- phik==0.11.2
- prometheus-client==0.9.0
- pyarrow==1.0.1
- pyrsistent==0.17.3
- pywavelets==1.1.1
- pyyaml==5.4.1
- querystring-parser==1.2.4
- seaborn==0.10.0
- send2trash==1.5.0
- shap==0.39.0
- slicer==0.0.7
- spark-tensorflow-distributor==0.1.0
- tangled-up-in-unicode==0.0.7
- tensorboard==2.4.1
- tensorboard-plugin-wit==1.8.0
- tensorflow-cpu==2.4.1
- tensorflow-estimator==2.4.0
- termcolor==1.1.0
- terminado==0.9.4
- testpath==0.4.4
- visions==0.6.0
- webencodings==0.5.1
- widgetsnbextension==3.5.1
- xgboost==1.3.3
prefix: /databricks/conda/envs/databricks-ml
Bibliothèques Python sur les clusters GPU
name: databricks-ml-gpu
channels:
- defaults
dependencies:
- _libgcc_mutex=0.1=main
- absl-py=0.11.0=pyhd3eb1b0_1
- aiohttp=3.7.4=py38h27cfd23_1
- asn1crypto=1.4.0=py_0
- astor=0.8.1=py38h06a4308_0
- async-timeout=3.0.1=py38h06a4308_0
- attrs=20.3.0=pyhd3eb1b0_0
- backcall=0.2.0=pyhd3eb1b0_0
- bcrypt=3.2.0=py38h7b6447c_0
- blas=1.0=mkl
- blinker=1.4=py38h06a4308_0
- boto3=1.16.7=pyhd3eb1b0_0
- botocore=1.19.7=pyhd3eb1b0_0
- brotlipy=0.7.0=py38h27cfd23_1003
- c-ares=1.17.1=h27cfd23_0
- ca-certificates=2021.4.13=h06a4308_1 # (updated from 2021.1.19 in May 26, 2021 maintenance update)
- cachetools=4.2.1=pyhd3eb1b0_0
- certifi=2020.12.5=py38h06a4308_0
- cffi=1.14.3=py38h261ae71_2
- chardet=3.0.4=py38h06a4308_1003
- click=7.1.2=pyhd3eb1b0_0
- cloudpickle=1.6.0=py_0
- configparser=5.0.1=py_0
- cryptography=3.1.1=py38h1ba5d50_0
- cycler=0.10.0=py38_0
- cython=0.29.21=py38h2531618_0
- decorator=4.4.2=pyhd3eb1b0_0
- dill=0.3.2=py_0
- docutils=0.15.2=py38h06a4308_1
- entrypoints=0.3=py38_0
- flask=1.1.2=pyhd3eb1b0_0
- freetype=2.10.4=h5ab3b9f_0
- future=0.18.2=py38_1
- gitdb=4.0.5=py_0
- gitpython=3.1.12=pyhd3eb1b0_1
- google-auth=1.22.1=py_0
- google-auth-oauthlib=0.4.2=pyhd3eb1b0_2
- google-pasta=0.2.0=py_0
- grpcio=1.31.0=py38hf8bcb03_0
- gunicorn=20.0.4=py38h06a4308_0
- h5py=2.10.0=py38h7918eee_0
- hdf5=1.10.4=hb1b8bf9_0
- icu=58.2=he6710b0_3
- idna=2.10=pyhd3eb1b0_0
- importlib-metadata=2.0.0=py_1
- intel-openmp=2019.4=243
- ipykernel=5.3.4=py38h5ca1d4c_0
- ipython=7.19.0=py38hb070fc8_1
- ipython_genutils=0.2.0=pyhd3eb1b0_1
- isodate=0.6.0=py_1
- itsdangerous=1.1.0=pyhd3eb1b0_0
- jedi=0.17.2=py38h06a4308_1
- jinja2=2.11.2=pyhd3eb1b0_0
- jmespath=0.10.0=py_0
- joblib=0.17.0=py_0
- jpeg=9b=h024ee3a_2
- jupyter_client=6.1.7=py_0
- jupyter_core=4.6.3=py38_0
- kiwisolver=1.3.0=py38h2531618_0
- krb5=1.17.1=h173b8e3_0
- lcms2=2.11=h396b838_0
- ld_impl_linux-64=2.33.1=h53a641e_7
- libedit=3.1.20191231=h14c3975_1
- libffi=3.3=he6710b0_2
- libgcc-ng=9.1.0=hdf63c60_0
- libgfortran-ng=7.3.0=hdf63c60_0
- libpng=1.6.37=hbc83047_0
- libpq=12.2=h20c2e04_0
- libprotobuf=3.13.0.1=hd408876_0
- libsodium=1.0.18=h7b6447c_0
- libstdcxx-ng=9.1.0=hdf63c60_0
- libtiff=4.1.0=h2733197_1
- lightgbm=3.1.1=py38h2531618_0
- lz4-c=1.9.2=heb0550a_3
- mako=1.1.3=py_0
- markdown=3.3.3=py38h06a4308_0
- markupsafe=1.1.1=py38h7b6447c_0
- matplotlib-base=3.2.2=py38hef1b27d_0
- mkl=2019.4=243
- mkl-service=2.3.0=py38he904b0f_0
- mkl_fft=1.2.0=py38h23d657b_0
- mkl_random=1.1.0=py38h962f231_0
- more-itertools=8.6.0=pyhd3eb1b0_0
- multidict=5.1.0=py38h27cfd23_2
- ncurses=6.2=he6710b0_1
- networkx=2.5=py_0
- nltk=3.5=py_0
- numpy=1.19.2=py38h54aff64_0
- numpy-base=1.19.2=py38hfa32c7d_0
- oauthlib=3.1.0=py_0
- olefile=0.46=py_0
- openssl=1.1.1k=h27cfd23_0 # (updated from 1.1.1i in May 26, 2021 maintenance update)
- packaging=20.4=py_0
- pandas=1.1.3=py38he6710b0_0
- paramiko=2.7.2=py_0
- parso=0.7.0=py_0
- patsy=0.5.1=py38_0
- pexpect=4.8.0=pyhd3eb1b0_3
- pickleshare=0.7.5=pyhd3eb1b0_1003
- pillow=8.0.1=py38he98fc37_0
- pip=20.2.4=py38h06a4308_0
- plotly=4.14.3=pyhd3eb1b0_0
- prompt-toolkit=3.0.8=py_0
- prompt_toolkit=3.0.8=0
- protobuf=3.13.0.1=py38he6710b0_1
- psutil=5.7.2=py38h7b6447c_0
- psycopg2=2.8.5=py38h3c74f83_1
- ptyprocess=0.6.0=pyhd3eb1b0_2
- pyasn1=0.4.8=py_0
- pyasn1-modules=0.2.8=py_0
- pycparser=2.20=py_2
- pygments=2.7.2=pyhd3eb1b0_0
- pyjwt=1.7.1=py38_0
- pynacl=1.4.0=py38h7b6447c_1
- pyodbc=4.0.30=py38he6710b0_0
- pyopenssl=19.1.0=pyhd3eb1b0_1
- pyparsing=2.4.7=pyhd3eb1b0_0
- pysocks=1.7.1=py38h06a4308_0
- python=3.8.8=hdb3f193_4 # (updated from 3.8.5 in May 26, 2021 maintenance update)
- python-dateutil=2.8.1=pyhd3eb1b0_0
- python-editor=1.0.4=py_0
- pytz=2020.5=pyhd3eb1b0_0
- pyzmq=19.0.2=py38he6710b0_1
- readline=8.0=h7b6447c_0
- regex=2020.10.15=py38h7b6447c_0
- requests=2.24.0=py_0
- requests-oauthlib=1.3.0=py_0
- retrying=1.3.3=py_2
- rsa=4.7.2=pyhd3eb1b0_1
- s3transfer=0.3.6=pyhd3eb1b0_0
- scikit-learn=0.23.2=py38h0573a6f_0
- scipy=1.5.2=py38h0b6359f_0
- setuptools=50.3.1=py38h06a4308_1
- simplejson=3.17.2=py38h27cfd23_2
- six=1.15.0=py38h06a4308_0
- smmap=3.0.5=pyhd3eb1b0_0
- sqlite=3.33.0=h62c20be_0
- sqlparse=0.4.1=py_0
- statsmodels=0.12.0=py38h7b6447c_0
- tabulate=0.8.7=py38h06a4308_0
- threadpoolctl=2.1.0=pyh5ca1d4c_0
- tk=8.6.10=hbc83047_0
- tornado=6.0.4=py38h7b6447c_1
- tqdm=4.50.2=py_0
- traitlets=5.0.5=pyhd3eb1b0_0
- typing-extensions=3.7.4.3=hd3eb1b0_0
- typing_extensions=3.7.4.3=pyh06a4308_0
- unixodbc=2.3.9=h7b6447c_0
- urllib3=1.25.11=py_0
- wcwidth=0.2.5=py_0
- websocket-client=0.57.0=py38_2
- werkzeug=1.0.1=pyhd3eb1b0_0
- wheel=0.35.1=pyhd3eb1b0_0
- wrapt=1.12.1=py38h7b6447c_1
- xz=5.2.5=h7b6447c_0
- yarl=1.6.3=py38h27cfd23_0
- zeromq=4.3.3=he6710b0_3
- zipp=3.4.0=pyhd3eb1b0_0
- zlib=1.2.11=h7b6447c_3
- zstd=1.4.5=h9ceee32_0
- pip:
- argon2-cffi==20.1.0
- astunparse==1.6.3
- async-generator==1.10
- azure-core==1.11.0
- azure-storage-blob==12.7.1
- bleach==3.3.0
- confuse==1.4.0
- databricks-cli==0.14.3
- defusedxml==0.7.1
- diskcache==5.2.1
- docker==4.4.4
- flatbuffers==1.12
- gast==0.3.3
- horovod==0.21.3
- htmlmin==0.1.12
- imagehash==4.2.0
- ipywidgets==7.6.3
- joblibspark==0.3.0
- jsonschema==3.2.0
- jupyterlab-pygments==0.1.2
- jupyterlab-widgets==1.0.0
- keras-preprocessing==1.1.2
- koalas==1.7.0
- llvmlite==0.36.0
- missingno==0.4.2
- mistune==0.8.4
- mleap==0.16.1
- mlflow-skinny==1.15.0
- msrest==0.6.21
- nbclient==0.5.3
- nbconvert==6.0.7
- nbformat==5.1.2
- nest-asyncio==1.5.1
- notebook==6.3.0
- numba==0.53.1
- opt-einsum==3.3.0
- pandas-profiling==2.11.0
- pandocfilters==1.4.3
- petastorm==0.9.8
- phik==0.11.2
- pyarrow==1.0.1
- pyrsistent==0.17.3
- pywavelets==1.1.1
- pyyaml==5.4.1
- querystring-parser==1.2.4
- seaborn==0.10.0
- send2trash==1.5.0
- shap==0.39.0
- slicer==0.0.7
- spark-tensorflow-distributor==0.1.0
- tangled-up-in-unicode==0.0.7
- tensorboard==2.4.1
- tensorboard-plugin-wit==1.8.0
- tensorflow==2.4.1
- tensorflow-estimator==2.4.0
- termcolor==1.1.0
- terminado==0.9.4
- testpath==0.4.4
- torch==1.8.1
- torchvision==0.9.1
- visions==0.6.0
- webencodings==0.5.1
- widgetsnbextension==3.5.1
- xgboost==1.3.3
prefix: /databricks/conda/envs/databricks-ml-gpu
Packages Spark contenant des modules Python
Package Spark | Module Python | Version |
---|---|---|
graphframes | graphframes | 0.8.1-db2-spark3.1 |
Bibliothèques R
Les bibliothèques R sont identiques aux bibliothèques R dans Databricks Runtime 8.2.
Bibliothèques Java et Scala (cluster Scala 2.12)
En plus des bibliothèques Java et Scala dans Databricks Runtime 8.2, Databricks Runtime 8.2 ML contient les fichiers jar suivants :
Clusters UC
ID de groupe | ID d’artefact | Version |
---|---|---|
com.typesafe.akka | akka-actor_2.12 | 2.5.23 |
ml.combust.mleap | mleap-databricks-runtime_2.12 | 0.17.3-4882dc3 |
ml.dmlc | xgboost4j-spark_2.12 | 1.3.1 |
ml.dmlc | xgboost4j_2.12 | 1.3.1 |
org.mlflow | mlflow-client | 1.15.0 |
org.scala-lang.modules | scala-java8-compat_2.12 | 0.8.0 |
org.tensorflow | spark-tensorflow-connector_2.12 | 1.15.0 |
Clusters GPU
ID de groupe | ID d’artefact | Version |
---|---|---|
com.typesafe.akka | akka-actor_2.12 | 2.5.23 |
ml.combust.mleap | mleap-databricks-runtime_2.12 | 0.17.3-4882dc3 |
ml.dmlc | xgboost4j-spark-gpu_2.12 | 1.3.1 |
ml.dmlc | xgboost4j-gpu_2.12 | 1.3.1 |
org.mlflow | mlflow-client | 1.15.0 |
org.scala-lang.modules | scala-java8-compat_2.12 | 0.8.0 |
org.tensorflow | spark-tensorflow-connector_2.12 | 1.15.0 |