Databricks Runtime 5.5 LTS för ML (EoS)
Kommentar
Stödet för den här Databricks Runtime-versionen har upphört. Information om slutdatumet för support finns i Historik över supportens slut. Alla Databricks Runtime-versioner som stöds finns i Databricks Runtime-versionsanteckningar och kompatibilitet.
Databricks släppte den här versionen i juli 2019. Supporten upphörde den 27 juli 2021. Databricks Runtime 5.5 ML Extended Support (EoS) utökar 5,5 ML-stöd till och med december 2021. Den använder Ubuntu 18.04.5 LTS i stället för den inaktuella Ubuntu 16.04.6 LTS-distributionen som användes i den ursprungliga Databricks Runtime 5.5 ML LTS. Stöd för Ubuntu 16.04.6 LTS upphörde den 1 april 2021.
Databricks Runtime 5.5 LTS for Machine Learning tillhandahåller en färdig miljö för maskininlärning och datavetenskap baserat på Databricks Runtime 5.5 LTS (EoS). Databricks Runtime ML innehåller många populära maskininlärningsbibliotek, inklusive TensorFlow, PyTorch, Keras och XGBoost. Den stöder även distribuerad djupinlärningsträning med Horovod.
Mer information, inklusive instruktioner för att skapa ett Databricks Runtime ML-kluster, finns i AI och maskininlärning på Databricks.
Nya funktioner
Databricks Runtime 5.5 LTS for Machine Learning bygger på Databricks Runtime 5.5 LTS. Information om nyheter i Databricks Runtime 5.5 LTS finns i viktig information om Databricks Runtime 5.5 LTS (EoS).
Förutom biblioteksuppdateringar introducerar Databricks Runtime 5.5 LTS for Machine Learning följande nya funktioner:
- MLflow 1.0 Python-paketet har lagts till
Förbättringar
Uppgraderade maskininlärningsbibliotek
- TensorFlow har uppgraderats från 1.12.0 till 1.13.1
- PyTorch har uppgraderats från 0.4.1 till 1.1.0
- scikit-learn har uppgraderats från 0.19.1 till 0.20.3
Ennodsåtgärd för HorovodRunner
HorovodRunner har aktiverats för att endast köras på drivrutinsnoden. Tidigare måste du köra en drivrutin och minst en arbetsnod för att kunna använda HorovodRunner. Med den här ändringen kan du nu distribuera träning inom en enskild nod (dvs. en nod med flera GPU:er) och därmed använda beräkningsresurser mer effektivt.
Inaktualitet
I hyperoptbiblioteket inaktuella vi följande egenskaper hyperopt.SparkTrials
för :
SparkTrials.successful_trials_count
SparkTrials.failed_trials_count
SparkTrials.cancelled_trials_count
SparkTrials.total_trials_count
och ersatte egenskaperna med följande funktioner:
SparkTrials.count_successful_trials()
SparkTrials.count_failed_trials()
SparkTrials.count_cancelled_trials()
SparkTrials.count_total_trials()
Systemmiljö
Systemmiljön i Databricks Runtime 5.5 LTS for Machine Learning skiljer sig från Databricks Runtime 5.5 på följande sätt:
- Python: 3.6.5 för Python 3-kluster och 2.7.15 för Python 2-kluster.
- DBUtils: Innehåller inte biblioteksverktyget (dbutils.library) (äldre).
- Följande NVIDIA GPU-bibliotek för GPU-kluster:
- CUDA 10.0
- CUDNN 7.6.0
Bibliotek
I följande avsnitt visas de bibliotek som ingår i Databricks Runtime 5.5 LTS for Machine Learning som skiljer sig från de som ingår i Databricks Runtime 5.5.
Bibliotek på den översta nivån
Databricks Runtime 5.5 LTS för Machine Learning innehåller följande bibliotek på den översta nivån:
Python-bibliotek
Databricks Runtime 5.5 LTS för Machine Learning använder Conda för Python-pakethantering. Därför finns det stora skillnader i installerade Python-bibliotek jämfört med Databricks Runtime. I följande avsnitt beskrivs Conda-miljöerna för Databricks Runtime 5.5 LTS för Machine Learning-kluster med Python 2 eller 3 samt PROCESSOR- eller GPU-aktiverade datorer.
Python 3 på CPU-kluster
name: null
channels:
- pytorch
- defaults
dependencies:
- _libgcc_mutex=0.1=main
- _py-xgboost-mutex=2.0=cpu_0
- _tflow_select=2.3.0=mkl
- absl-py=0.7.1=py36_0
- asn1crypto=0.24.0=py36_0
- astor=0.7.1=py36_0
- backcall=0.1.0=py36_0
- backports=1.0=py_2
- bcrypt=3.1.6=py36h7b6447c_0
- blas=1.0=mkl
- bleach=2.1.3=py36_0
- boto=2.48.0=py36_1
- boto3=1.7.62=py36h28b3542_1
- botocore=1.10.62=py36h28b3542_0
- ca-certificates=2018.03.07=0
- certifi=2018.4.16=py36_0
- cffi=1.11.5=py36he75722e_1
- chardet=3.0.4=py36_1
- click=7.0=py36_0
- cloudpickle=0.8.0=py36_0
- colorama=0.3.9=py36h489cec4_0
- configparser=3.7.3=py36_1
- cryptography=2.2.2=py36h14c3975_0
- cycler=0.10.0=py36h93f1223_0
- cython=0.28.2=py36h14c3975_0
- decorator=4.3.0=py36_0
- docutils=0.14=py36hb0f60f5_0
- entrypoints=0.2.3=py36_2
- et_xmlfile=1.0.1=py36hd6bccc3_0
- flask=1.0.2=py36_1
- freetype=2.8=hab7d2ae_1
- gast=0.2.2=py36_0
- gitdb2=2.0.5=py36_0
- gitpython=2.1.11=py36_0
- gmp=6.1.2=h6c8ec71_1
- grpcio=1.12.1=py36hdbcaa40_0
- gunicorn=19.9.0=py36_0
- h5py=2.8.0=py36h989c5e5_3
- hdf5=1.10.2=hba1933b_1
- html5lib=1.0.1=py36_0
- icu=58.2=h9c2bf20_1
- idna=2.6=py36h82fb2a8_1
- intel-openmp=2018.0.0=8
- ipython=6.4.0=py36_1
- ipython_genutils=0.2.0=py36_0
- itsdangerous=0.24=py36_1
- jdcal=1.4=py36_0
- jedi=0.12.0=py36_1
- jinja2=2.10=py36_0
- jmespath=0.9.4=py_0
- jpeg=9b=h024ee3a_2
- jsonschema=2.6.0=py36_0
- jupyter_client=5.2.3=py36_0
- jupyter_core=4.4.0=py36_0
- keras=2.2.4=0
- keras-applications=1.0.8=py_0
- keras-base=2.2.4=py36_0
- keras-preprocessing=1.1.0=py_1
- krb5=1.16.1=hc83ff2d_6
- libedit=3.1.20170329=h6b74fdf_2
- libffi=3.2.1=hd88cf55_4
- libgcc-ng=7.3.0=hdf63c60_0
- libgfortran-ng=7.2.0=hdf63c60_3
- libpng=1.6.34=hb9fc6fc_0
- libpq=10.4=h1ad7b7a_0
- libprotobuf=3.8.0=hd408876_0
- libsodium=1.0.16=h1bed415_0
- libstdcxx-ng=7.3.0=hdf63c60_0
- libtiff=4.0.9=he85c1e1_2
- libxgboost=0.90=he6710b0_0
- libxml2=2.9.8=h26e45fe_1
- libxslt=1.1.32=h1312cb7_0
- llvmlite=0.23.1=py36hdbcaa40_0
- lxml=4.2.1=py36h23eabaa_0
- mako=1.0.10=py_0
- markdown=3.1.1=py36_0
- markupsafe=1.0=py36h14c3975_1
- mistune=0.8.3=py36h14c3975_1
- mkl=2019.4=243
- mkl_fft=1.0.12=py36ha843d7b_0
- mkl_random=1.0.2=py36hd81dba3_0
- mock=3.0.5=py36_0
- msgpack-python=0.5.6=py36h6bb024c_1
- nbconvert=5.3.1=py36_0
- nbformat=4.4.0=py36h31c9010_0
- ncurses=6.1=he6710b0_1
- ninja=1.9.0=py36hfd86e86_0
- numba=0.38.0=py36h637b7d7_0
- numpy=1.16.2=py36h7e9f1db_0
- numpy-base=1.16.2=py36hde5b4d6_0
- olefile=0.45.1=py36_0
- openpyxl=2.5.3=py36_0
- openssl=1.0.2o=h14c3975_1
- pandas=0.23.0=py36h637b7d7_0
- pandocfilters=1.4.2=py36_1
- paramiko=2.4.2=py36_0
- parso=0.2.0=py36_0
- pathlib2=2.3.2=py36_0
- patsy=0.5.0=py36_0
- pexpect=4.5.0=py36_0
- pickleshare=0.7.4=py36_0
- pillow=5.1.0=py36h3deb7b8_0
- pip=10.0.1=py36_0
- ply=3.11=py36_0
- prompt_toolkit=1.0.15=py36h17d85b1_0
- protobuf=3.8.0=py36he6710b0_0
- psycopg2=2.7.5=py36hb7f436b_0
- ptyprocess=0.5.2=py36h69acd42_0
- py-xgboost=0.90=py36he6710b0_0
- py-xgboost-cpu=0.90=py36_0
- pyasn1=0.4.5=py_0
- pycparser=2.18=py36_1
- pygments=2.2.0=py36_0
- pynacl=1.3.0=py36h7b6447c_0
- pyopenssl=18.0.0=py36_0
- pyparsing=2.2.0=py36_1
- pysocks=1.6.8=py36_0
- python=3.6.5=hc3d631a_2
- python-dateutil=2.7.3=py36_0
- python-editor=1.0.4=py_0
- pytz=2018.4=py36_0
- pyyaml=5.1=py36h7b6447c_0
- pyzmq=17.0.0=py36h14c3975_3
- readline=7.0=h7b6447c_5
- requests=2.18.4=py36he2e5f8d_1
- s3transfer=0.1.13=py36_0
- scikit-learn=0.20.3=py36hd81dba3_0
- scipy=1.1.0=py36h7c811a0_2
- setuptools=39.1.0=py36_0
- simplegeneric=0.8.1=py36_2
- simplejson=3.16.0=py36h14c3975_0
- singledispatch=3.4.0.3=py36_0
- six=1.11.0=py36_1
- smmap2=2.0.5=py36_0
- sqlite=3.23.1=he433501_0
- sqlparse=0.3.0=py_0
- statsmodels=0.9.0=py36h035aef0_0
- tabulate=0.8.3=py36_0
- tensorboard=1.13.1=py36hf484d3e_0
- tensorflow=1.13.1=mkl_py36h27d456a_0
- tensorflow-base=1.13.1=mkl_py36h7ce6ba3_0
- tensorflow-estimator=1.13.0=py_0
- tensorflow-mkl=1.13.1=h4fcabd2_0
- termcolor=1.1.0=py36_1
- testpath=0.3.1=py36h8cadb63_0
- tk=8.6.7=hc745277_3
- tornado=5.0.2=py36h14c3975_0
- traitlets=4.3.2=py36_0
- urllib3=1.22=py36hbe7ace6_0
- virtualenv=16.0.0=py36_0
- wcwidth=0.1.7=py36hdf4376a_0
- webencodings=0.5.1=py36_1
- werkzeug=0.14.1=py36_0
- wheel=0.31.1=py36_0
- wrapt=1.11.1=py36h7b6447c_0
- xz=5.2.4=h14c3975_4
- yaml=0.1.7=had09818_2
- zeromq=4.2.5=hf484d3e_1
- zlib=1.2.11=h7b6447c_3
- pytorch-cpu=1.1.0=py3.6_cpu_0
- torchvision-cpu=0.3.0=py36_cuNone_1
- pip:
- databricks-cli==0.8.7
- docker==4.0.2
- fusepy==2.0.4
- future==0.17.1
- horovod==0.16.4
- hyperopt==0.1.2.db6
- kiwisolver==1.1.0
- matplotlib==2.2.2
- mleap==0.8.1
- mlflow==1.0.0
- msgpack==0.5.6
- networkx==2.2
- nose==1.3.7
- nose-exclude==0.5.0
- psutil==5.6.3
- pyarrow==0.13.0
- pymongo==3.8.0
- querystring-parser==1.2.3
- seaborn==0.8.1
- tensorboardx==1.7
- torchvision==0.3.0
- tqdm==4.32.2
- websocket-client==0.56.0
prefix: /databricks/python3
Python 3 på GPU-kluster
name: null
channels:
- pytorch
- Databricks
- defaults
dependencies:
- tensorflow=1.13.1.db1=gpu_py36h2903d8e_0
- tensorflow-base=1.13.1.db1=gpu_py36he292aa2_0
- tensorflow-gpu=1.13.1.db1=h0d30ee6_0
- _libgcc_mutex=0.1=main
- _py-xgboost-mutex=1.0=gpu_0
- _tflow_select=2.1.0=gpu
- absl-py=0.7.1=py36_0
- asn1crypto=0.24.0=py36_0
- astor=0.7.1=py36_0
- backcall=0.1.0=py36_0
- backports=1.0=py_2
- bcrypt=3.1.6=py36h7b6447c_0
- blas=1.0=mkl
- bleach=2.1.3=py36_0
- boto=2.48.0=py36_1
- boto3=1.7.62=py36h28b3542_1
- botocore=1.10.62=py36h28b3542_0
- ca-certificates=2018.03.07=0
- certifi=2018.4.16=py36_0
- cffi=1.11.5=py36he75722e_1
- chardet=3.0.4=py36_1
- click=7.0=py36_0
- cloudpickle=0.8.0=py36_0
- colorama=0.3.9=py36h489cec4_0
- configparser=3.7.3=py36_1
- cryptography=2.2.2=py36h14c3975_0
- cudnn=7.6.0=cuda10.0_0
- cupti=10.0.130=0
- cycler=0.10.0=py36_0
- cython=0.28.2=py36h14c3975_0
- decorator=4.3.0=py36_0
- docutils=0.14=py36_0
- entrypoints=0.2.3=py36_2
- et_xmlfile=1.0.1=py36hd6bccc3_0
- flask=1.0.2=py36_1
- freetype=2.8=hab7d2ae_1
- gast=0.2.2=py36_0
- gitdb2=2.0.5=py36_0
- gitpython=2.1.11=py36_0
- gmp=6.1.2=h6c8ec71_1
- grpcio=1.12.1=py36hdbcaa40_0
- gunicorn=19.9.0=py36_0
- h5py=2.8.0=py36h989c5e5_3
- hdf5=1.10.2=hba1933b_1
- html5lib=1.0.1=py36_0
- icu=58.2=h9c2bf20_1
- idna=2.6=py36h82fb2a8_1
- intel-openmp=2018.0.0=8
- ipython=6.4.0=py36_1
- ipython_genutils=0.2.0=py36hb52b0d5_0
- itsdangerous=0.24=py36_1
- jdcal=1.4=py36_0
- jedi=0.12.0=py36_1
- jinja2=2.10=py36_0
- jmespath=0.9.4=py_0
- jpeg=9b=h024ee3a_2
- jsonschema=2.6.0=py36_0
- jupyter_client=5.2.3=py36_0
- jupyter_core=4.4.0=py36_0
- keras=2.2.4=0
- keras-applications=1.0.8=py_0
- keras-base=2.2.4=py36_0
- keras-preprocessing=1.1.0=py_1
- krb5=1.16.1=hc83ff2d_6
- libedit=3.1.20170329=h6b74fdf_2
- libffi=3.2.1=hd88cf55_4
- libgcc-ng=7.3.0=hdf63c60_0
- libgfortran-ng=7.2.0=hdf63c60_3
- libpng=1.6.34=hb9fc6fc_0
- libpq=10.4=h1ad7b7a_0
- libprotobuf=3.8.0=hd408876_0
- libsodium=1.0.16=h1bed415_0
- libstdcxx-ng=7.3.0=hdf63c60_0
- libtiff=4.0.9=he85c1e1_2
- libxgboost=0.90=h688424c_0
- libxml2=2.9.8=h26e45fe_1
- libxslt=1.1.32=h1312cb7_0
- llvmlite=0.23.1=py36hdbcaa40_0
- lxml=4.2.1=py36h23eabaa_0
- mako=1.0.10=py_0
- markdown=3.1.1=py36_0
- markupsafe=1.0=py36h14c3975_1
- mistune=0.8.3=py36h14c3975_1
- mkl=2019.4=243
- mkl_fft=1.0.12=py36ha843d7b_0
- mkl_random=1.0.2=py36hd81dba3_0
- mock=3.0.5=py36_0
- msgpack-python=0.5.6=py36h6bb024c_1
- nbconvert=5.3.1=py36_0
- nbformat=4.4.0=py36h31c9010_0
- ncurses=6.1=he6710b0_1
- ninja=1.9.0=py36hfd86e86_0
- numba=0.38.0=py36h637b7d7_0
- numpy=1.16.2=py36h7e9f1db_0
- numpy-base=1.16.2=py36hde5b4d6_0
- olefile=0.45.1=py36_0
- openpyxl=2.5.3=py36_0
- openssl=1.0.2o=h14c3975_1
- pandas=0.23.0=py36h637b7d7_0
- pandocfilters=1.4.2=py36_1
- paramiko=2.4.2=py36_0
- parso=0.2.0=py36_0
- pathlib2=2.3.2=py36_0
- patsy=0.5.0=py36_0
- pexpect=4.5.0=py36_0
- pickleshare=0.7.4=py36h63277f8_0
- pillow=5.1.0=py36h3deb7b8_0
- pip=10.0.1=py36_0
- ply=3.11=py36_0
- prompt_toolkit=1.0.15=py36_0
- protobuf=3.8.0=py36he6710b0_0
- psycopg2=2.7.5=py36hb7f436b_0
- ptyprocess=0.5.2=py36h69acd42_0
- py-xgboost=0.90=py36h688424c_0
- py-xgboost-gpu=0.90=py36h28bbb66_0
- pyasn1=0.4.5=py_0
- pycparser=2.18=py36_1
- pygments=2.2.0=py36_0
- pynacl=1.3.0=py36h7b6447c_0
- pyopenssl=18.0.0=py36_0
- pyparsing=2.2.0=py36_1
- pysocks=1.6.8=py36_0
- python=3.6.5=hc3d631a_2
- python-dateutil=2.7.3=py36_0
- python-editor=1.0.4=py_0
- pytz=2018.4=py36_0
- pyyaml=5.1=py36h7b6447c_0
- pyzmq=17.0.0=py36h14c3975_3
- readline=7.0=h7b6447c_5
- requests=2.18.4=py36he2e5f8d_1
- s3transfer=0.1.13=py36_0
- scikit-learn=0.20.3=py36hd81dba3_0
- scipy=1.1.0=py36h7c811a0_2
- setuptools=39.1.0=py36_0
- simplegeneric=0.8.1=py36_2
- simplejson=3.16.0=py36h14c3975_0
- singledispatch=3.4.0.3=py36h7a266c3_0
- six=1.11.0=py36_1
- smmap2=2.0.5=py36_0
- sqlite=3.23.1=he433501_0
- sqlparse=0.3.0=py_0
- statsmodels=0.9.0=py36h035aef0_0
- tabulate=0.8.3=py36_0
- tensorboard=1.13.1=py36hf484d3e_0
- tensorflow-estimator=1.13.0=py_0
- termcolor=1.1.0=py36_1
- testpath=0.3.1=py36_0
- tk=8.6.7=hc745277_3
- tornado=5.0.2=py36h14c3975_0
- traitlets=4.3.2=py36h674d592_0
- urllib3=1.22=py36hbe7ace6_0
- virtualenv=16.0.0=py36_0
- wcwidth=0.1.7=py36hdf4376a_0
- webencodings=0.5.1=py36_1
- werkzeug=0.14.1=py36_0
- wheel=0.31.1=py36_0
- wrapt=1.11.1=py36h7b6447c_0
- xz=5.2.4=h14c3975_4
- yaml=0.1.7=had09818_2
- zeromq=4.2.5=hf484d3e_1
- zlib=1.2.11=h7b6447c_3
- pytorch=1.1.0=py3.6_cuda10.0.130_cudnn7.5.1_0
- torchvision=0.3.0=py36_cu10.0.130_1
- pip:
- databricks-cli==0.8.7
- docker==4.0.2
- fusepy==2.0.4
- future==0.17.1
- horovod==0.16.4
- hyperopt==0.1.2.db6
- kiwisolver==1.1.0
- matplotlib==2.2.2
- mleap==0.8.1
- mlflow==1.0.0
- msgpack==0.5.6
- networkx==2.2
- nose==1.3.7
- nose-exclude==0.5.0
- psutil==5.6.3
- pyarrow==0.13.0
- pymongo==3.8.0
- querystring-parser==1.2.3
- seaborn==0.8.1
- tensorboardx==1.7
- tqdm==4.32.2
- websocket-client==0.56.0
prefix: /databricks/python3
Python 2 på CPU-kluster
name: null
channels:
- pytorch
- defaults
dependencies:
- _libgcc_mutex=0.1=main
- _py-xgboost-mutex=2.0=cpu_0
- _tflow_select=2.3.0=mkl
- absl-py=0.7.1=py27_0
- asn1crypto=0.24.0=py27_0
- astor=0.7.1=py27_0
- backports=1.0=py_2
- backports.shutil_get_terminal_size=1.0.0=py27_2
- backports.weakref=1.0.post1=py_1
- backports_abc=0.5=py_0
- bcrypt=3.1.6=py27h7b6447c_0
- blas=1.0=mkl
- bleach=2.1.3=py27_0
- boto=2.48.0=py27_1
- boto3=1.7.62=py27h28b3542_1
- botocore=1.10.62=py27h28b3542_0
- ca-certificates=2018.03.07=0
- certifi=2018.4.16=py27_0
- cffi=1.11.5=py27he75722e_1
- chardet=3.0.4=py27_1
- click=7.0=py27_0
- cloudpickle=0.8.0=py27_0
- colorama=0.3.9=py27h5cde069_0
- configparser=3.7.3=py27_1
- cryptography=2.2.2=py27h14c3975_0
- cycler=0.10.0=py27hc7354d3_0
- cython=0.28.2=py27h14c3975_0
- decorator=4.3.0=py27_0
- docutils=0.14=py27_0
- entrypoints=0.2.3=py27_2
- enum34=1.1.6=py27_1
- et_xmlfile=1.0.1=py27_0
- flask=1.0.2=py27_1
- freetype=2.8=hab7d2ae_1
- funcsigs=1.0.2=py27_0
- functools32=3.2.3.2=py27_1
- future=0.17.1=py27_0
- futures=3.2.0=py27_0
- gast=0.2.2=py27_0
- gitdb2=2.0.5=py27_0
- gitpython=2.1.11=py27_0
- gmp=6.1.2=h6c8ec71_1
- grpcio=1.12.1=py27hdbcaa40_0
- gunicorn=19.9.0=py27_0
- h5py=2.8.0=py27h989c5e5_3
- hdf5=1.10.2=hba1933b_1
- html5lib=1.0.1=py27_0
- icu=58.2=h9c2bf20_1
- idna=2.6=py27h5722d68_1
- intel-openmp=2018.0.0=8
- ipaddress=1.0.22=py27_0
- ipython=5.7.0=py27_0
- ipython_genutils=0.2.0=py27_0
- itsdangerous=0.24=py27_1
- jdcal=1.4=py27_0
- jinja2=2.10=py27_0
- jmespath=0.9.4=py_0
- jpeg=9b=h024ee3a_2
- jsonschema=2.6.0=py27h7ed5aa4_0
- jupyter_client=5.2.3=py27_0
- jupyter_core=4.4.0=py27_0
- keras=2.2.4=0
- keras-applications=1.0.8=py_0
- keras-base=2.2.4=py27_0
- keras-preprocessing=1.1.0=py_1
- krb5=1.16.1=hc83ff2d_6
- libedit=3.1.20170329=h6b74fdf_2
- libffi=3.2.1=hd88cf55_4
- libgcc-ng=7.3.0=hdf63c60_0
- libgfortran-ng=7.2.0=hdf63c60_3
- libpng=1.6.34=hb9fc6fc_0
- libpq=10.4=h1ad7b7a_0
- libprotobuf=3.8.0=hd408876_0
- libsodium=1.0.16=h1bed415_0
- libstdcxx-ng=7.3.0=hdf63c60_0
- libtiff=4.0.9=he85c1e1_2
- libxgboost=0.90=he6710b0_0
- libxml2=2.9.8=h26e45fe_1
- libxslt=1.1.32=h1312cb7_0
- linecache2=1.0.0=py27_0
- llvmlite=0.23.1=py27hdbcaa40_0
- lxml=4.2.1=py27h23eabaa_0
- mako=1.0.10=py_0
- markdown=3.1.1=py27_0
- markupsafe=1.0=py27h14c3975_1
- mistune=0.8.3=py27h14c3975_1
- mkl=2019.4=243
- mkl_fft=1.0.12=py27ha843d7b_0
- mkl_random=1.0.2=py27hd81dba3_0
- mock=3.0.5=py27_0
- msgpack-python=0.5.6=py27h6bb024c_1
- nbconvert=5.3.1=py27_0
- nbformat=4.4.0=py27hed7f2b2_0
- ncurses=6.1=he6710b0_1
- ninja=1.9.0=py27hfd86e86_0
- numba=0.38.0=py27h637b7d7_0
- numpy=1.16.2=py27h7e9f1db_0
- numpy-base=1.16.2=py27hde5b4d6_0
- olefile=0.45.1=py27_0
- openpyxl=2.5.3=py27_0
- openssl=1.0.2o=h14c3975_1
- pandas=0.23.0=py27h637b7d7_0
- pandocfilters=1.4.2=py27_1
- paramiko=2.4.2=py27_0
- pathlib2=2.3.2=py27_0
- patsy=0.5.0=py27_0
- pexpect=4.5.0=py27_0
- pickleshare=0.7.4=py27_0
- pillow=5.1.0=py27h3deb7b8_0
- pip=10.0.1=py27_0
- ply=3.11=py27_0
- prompt_toolkit=1.0.15=py27_0
- protobuf=3.8.0=py27he6710b0_0
- psycopg2=2.7.5=py27hb7f436b_0
- ptyprocess=0.5.2=py27h4ccb14c_0
- py-xgboost=0.90=py27he6710b0_0
- py-xgboost-cpu=0.90=py27_0
- pyasn1=0.4.5=py_0
- pycparser=2.18=py27_1
- pygments=2.2.0=py27_0
- pynacl=1.3.0=py27h7b6447c_0
- pyopenssl=18.0.0=py27_0
- pyparsing=2.2.0=py27_1
- pysocks=1.6.8=py27_0
- python=2.7.15=h1571d57_0
- python-dateutil=2.7.3=py27_0
- python-editor=1.0.4=py_0
- pytz=2018.4=py27_0
- pyyaml=5.1=py27h7b6447c_0
- pyzmq=17.0.0=py27h14c3975_3
- readline=7.0=h7b6447c_5
- requests=2.18.4=py27hc5b0589_1
- s3transfer=0.1.13=py27_0
- scandir=1.7=py27h14c3975_0
- scikit-learn=0.20.3=py27hd81dba3_0
- scipy=1.1.0=py27h7c811a0_2
- setuptools=39.1.0=py27_0
- simplegeneric=0.8.1=py27_2
- simplejson=3.16.0=py27h14c3975_0
- singledispatch=3.4.0.3=py27_0
- six=1.11.0=py27_1
- smmap2=2.0.5=py27_0
- sqlite=3.23.1=he433501_0
- sqlparse=0.3.0=py_0
- statsmodels=0.9.0=py27h035aef0_0
- tabulate=0.8.3=py27_0
- tensorboard=1.13.1=py27hf484d3e_0
- tensorflow=1.13.1=mkl_py27h74ee40f_0
- tensorflow-base=1.13.1=mkl_py27h7ce6ba3_0
- tensorflow-estimator=1.13.0=py_0
- tensorflow-mkl=1.13.1=h4fcabd2_0
- termcolor=1.1.0=py27_1
- testpath=0.3.1=py27hc38d2c4_0
- tk=8.6.7=hc745277_3
- tornado=5.0.2=py27h14c3975_0
- traceback2=1.4.0=py27_0
- traitlets=4.3.2=py27_0
- unittest2=1.1.0=py27_0
- urllib3=1.22=py27ha55213b_0
- virtualenv=16.0.0=py27_0
- wcwidth=0.1.7=py27h9e3e1ab_0
- webencodings=0.5.1=py27_1
- werkzeug=0.14.1=py27_0
- wheel=0.31.1=py27_0
- wrapt=1.11.1=py27h7b6447c_0
- xz=5.2.4=h14c3975_4
- yaml=0.1.7=had09818_2
- zeromq=4.2.5=hf484d3e_1
- zlib=1.2.11=h7b6447c_3
- pytorch-cpu=1.1.0=py2.7_cpu_0
- torchvision-cpu=0.3.0=py27_cuNone_1
- pip:
- backports.functools-lru-cache==1.5
- backports.ssl-match-hostname==3.7.0.1
- databricks-cli==0.8.7
- docker==4.0.2
- fusepy==2.0.4
- horovod==0.16.4
- hyperopt==0.1.2.db6
- kiwisolver==1.1.0
- matplotlib==2.2.2
- mleap==0.8.1
- mlflow==1.0.0
- msgpack==0.5.6
- networkx==2.2
- nose==1.3.7
- nose-exclude==0.5.0
- psutil==5.6.3
- pyarrow==0.13.0
- pymongo==3.8.0
- querystring-parser==1.2.3
- seaborn==0.8.1
- subprocess32==3.5.4
- tensorboardx==1.7
- torchvision==0.3.0
- tqdm==4.32.2
- websocket-client==0.56.0
prefix: /databricks/python2
Python 2 på GPU-kluster
name: null
channels:
- Databricks
- pytorch
- defaults
dependencies:
- tensorflow=1.13.1.db1=gpu_py27h8e347d7_0
- tensorflow-base=1.13.1.db1=gpu_py27he292aa2_0
- tensorflow-gpu=1.13.1.db1=h0d30ee6_0
- _libgcc_mutex=0.1=main
- _py-xgboost-mutex=1.0=gpu_0
- _tflow_select=2.1.0=gpu
- absl-py=0.7.1=py27_0
- asn1crypto=0.24.0=py27_0
- astor=0.7.1=py27_0
- backports=1.0=py_2
- backports.shutil_get_terminal_size=1.0.0=py27_2
- backports.weakref=1.0.post1=py_1
- backports_abc=0.5=py_0
- bcrypt=3.1.6=py27h7b6447c_0
- blas=1.0=mkl
- bleach=2.1.3=py27_0
- boto=2.48.0=py27_1
- boto3=1.7.62=py27h28b3542_1
- botocore=1.10.62=py27h28b3542_0
- ca-certificates=2018.03.07=0
- certifi=2018.4.16=py27_0
- cffi=1.11.5=py27he75722e_1
- chardet=3.0.4=py27_1
- click=7.0=py27_0
- cloudpickle=0.8.0=py27_0
- colorama=0.3.9=py27_0
- configparser=3.7.3=py27_1
- cryptography=2.2.2=py27h14c3975_0
- cudnn=7.6.0=cuda10.0_0
- cupti=10.0.130=0
- cycler=0.10.0=py27_0
- cython=0.28.2=py27h14c3975_0
- decorator=4.3.0=py27_0
- docutils=0.14=py27hae222c1_0
- entrypoints=0.2.3=py27_2
- enum34=1.1.6=py27_1
- et_xmlfile=1.0.1=py27h75840f5_0
- flask=1.0.2=py27_1
- freetype=2.8=hab7d2ae_1
- funcsigs=1.0.2=py27_0
- functools32=3.2.3.2=py27_1
- future=0.17.1=py27_0
- futures=3.2.0=py27_0
- gast=0.2.2=py27_0
- gitdb2=2.0.5=py27_0
- gitpython=2.1.11=py27_0
- gmp=6.1.2=h6c8ec71_1
- grpcio=1.12.1=py27hdbcaa40_0
- gunicorn=19.9.0=py27_0
- h5py=2.8.0=py27h989c5e5_3
- hdf5=1.10.2=hba1933b_1
- html5lib=1.0.1=py27_0
- icu=58.2=h9c2bf20_1
- idna=2.6=py27h5722d68_1
- intel-openmp=2018.0.0=8
- ipaddress=1.0.22=py27_0
- ipython=5.7.0=py27_0
- ipython_genutils=0.2.0=py27h89fb69b_0
- itsdangerous=0.24=py27_1
- jdcal=1.4=py27_0
- jinja2=2.10=py27_0
- jmespath=0.9.4=py_0
- jpeg=9b=h024ee3a_2
- jsonschema=2.6.0=py27h7ed5aa4_0
- jupyter_client=5.2.3=py27_0
- jupyter_core=4.4.0=py27_0
- keras=2.2.4=0
- keras-applications=1.0.8=py_0
- keras-base=2.2.4=py27_0
- keras-preprocessing=1.1.0=py_1
- krb5=1.16.1=hc83ff2d_6
- libedit=3.1.20170329=h6b74fdf_2
- libffi=3.2.1=hd88cf55_4
- libgcc-ng=7.3.0=hdf63c60_0
- libgfortran-ng=7.2.0=hdf63c60_3
- libpng=1.6.34=hb9fc6fc_0
- libpq=10.4=h1ad7b7a_0
- libprotobuf=3.8.0=hd408876_0
- libsodium=1.0.16=h1bed415_0
- libstdcxx-ng=7.3.0=hdf63c60_0
- libtiff=4.0.9=he85c1e1_2
- libxgboost=0.90=h688424c_0
- libxml2=2.9.8=h26e45fe_1
- libxslt=1.1.32=h1312cb7_0
- linecache2=1.0.0=py27_0
- llvmlite=0.23.1=py27hdbcaa40_0
- lxml=4.2.1=py27h23eabaa_0
- mako=1.0.10=py_0
- markdown=3.1.1=py27_0
- markupsafe=1.0=py27h14c3975_1
- mistune=0.8.3=py27h14c3975_1
- mkl=2019.4=243
- mkl_fft=1.0.12=py27ha843d7b_0
- mkl_random=1.0.2=py27hd81dba3_0
- mock=3.0.5=py27_0
- msgpack-python=0.5.6=py27h6bb024c_1
- nbconvert=5.3.1=py27_0
- nbformat=4.4.0=py27hed7f2b2_0
- ncurses=6.1=he6710b0_1
- ninja=1.9.0=py27hfd86e86_0
- numba=0.38.0=py27h637b7d7_0
- numpy=1.16.2=py27h7e9f1db_0
- numpy-base=1.16.2=py27hde5b4d6_0
- olefile=0.45.1=py27_0
- openpyxl=2.5.3=py27_0
- openssl=1.0.2o=h14c3975_1
- pandas=0.23.0=py27h637b7d7_0
- pandocfilters=1.4.2=py27_1
- paramiko=2.4.2=py27_0
- pathlib2=2.3.2=py27_0
- patsy=0.5.0=py27_0
- pexpect=4.5.0=py27_0
- pickleshare=0.7.4=py27h09770e1_0
- pillow=5.1.0=py27h3deb7b8_0
- pip=10.0.1=py27_0
- ply=3.11=py27_0
- prompt_toolkit=1.0.15=py27_0
- protobuf=3.8.0=py27he6710b0_0
- psycopg2=2.7.5=py27hb7f436b_0
- ptyprocess=0.5.2=py27h4ccb14c_0
- py-xgboost=0.90=py27h688424c_0
- py-xgboost-gpu=0.90=py27h28bbb66_0
- pyasn1=0.4.5=py_0
- pycparser=2.18=py27_1
- pygments=2.2.0=py27_0
- pynacl=1.3.0=py27h7b6447c_0
- pyopenssl=18.0.0=py27_0
- pyparsing=2.2.0=py27_1
- pysocks=1.6.8=py27_0
- python=2.7.15=h1571d57_0
- python-dateutil=2.7.3=py27_0
- python-editor=1.0.4=py_0
- pytz=2018.4=py27_0
- pyyaml=5.1=py27h7b6447c_0
- pyzmq=17.0.0=py27h14c3975_3
- readline=7.0=h7b6447c_5
- requests=2.18.4=py27hc5b0589_1
- s3transfer=0.1.13=py27_0
- scandir=1.7=py27h14c3975_0
- scikit-learn=0.20.3=py27hd81dba3_0
- scipy=1.1.0=py27h7c811a0_2
- setuptools=39.1.0=py27_0
- simplegeneric=0.8.1=py27_2
- simplejson=3.16.0=py27h14c3975_0
- singledispatch=3.4.0.3=py27h9bcb476_0
- six=1.11.0=py27_1
- smmap2=2.0.5=py27_0
- sqlite=3.23.1=he433501_0
- sqlparse=0.3.0=py_0
- statsmodels=0.9.0=py27h035aef0_0
- tabulate=0.8.3=py27_0
- tensorboard=1.13.1=py27hf484d3e_0
- tensorflow-estimator=1.13.0=py_0
- termcolor=1.1.0=py27_1
- testpath=0.3.1=py27_0
- tk=8.6.7=hc745277_3
- tornado=5.0.2=py27h14c3975_0
- traceback2=1.4.0=py27_0
- traitlets=4.3.2=py27hd6ce930_0
- unittest2=1.1.0=py27_0
- urllib3=1.22=py27ha55213b_0
- virtualenv=16.0.0=py27_0
- wcwidth=0.1.7=py27_0
- webencodings=0.5.1=py27_1
- werkzeug=0.14.1=py27_0
- wheel=0.31.1=py27_0
- wrapt=1.11.1=py27h7b6447c_0
- xz=5.2.4=h14c3975_4
- yaml=0.1.7=had09818_2
- zeromq=4.2.5=hf484d3e_1
- zlib=1.2.11=h7b6447c_3
- pytorch=1.1.0=py2.7_cuda10.0.130_cudnn7.5.1_0
- torchvision=0.3.0=py27_cu10.0.130_1
- pip:
- backports.functools-lru-cache==1.5
- backports.ssl-match-hostname==3.7.0.1
- databricks-cli==0.8.7
- docker==4.0.2
- fusepy==2.0.4
- horovod==0.16.4
- hyperopt==0.1.2.db6
- kiwisolver==1.1.0
- matplotlib==2.2.2
- mleap==0.8.1
- mlflow==1.0.0
- msgpack==0.5.6
- networkx==2.2
- nose==1.3.7
- nose-exclude==0.5.0
- psutil==5.6.3
- pyarrow==0.13.0
- pymongo==3.8.0
- querystring-parser==1.2.3
- seaborn==0.8.1
- subprocess32==3.5.4
- tensorboardx==1.7
- tqdm==4.32.2
- websocket-client==0.56.0
prefix: /databricks/python2
Spark-paket som innehåller Python-moduler
Spark-paket | Python-modul | Version |
---|---|---|
graphframes | graphframes | 0.7.0-db1-spark2.4 |
spark-deep-learning | sparkdl | 1.5.0-db4-spark2.4 |
tensorframes | tensorframes | 0.7.0-s_2.11 |
R-bibliotek
R-biblioteken är identiska med R-biblioteken i Databricks Runtime 5.5.
Java- och Scala-bibliotek (Scala 2.11-kluster)
Förutom Java- och Scala-bibliotek i Databricks Runtime 5.5 innehåller Databricks Runtime 5.5 LTS för Machine Learning följande JAR:er:
Grupp-ID | Artefakt-ID | Version |
---|---|---|
com.databricks | spark-deep-learning | 1.5.0-db4-spark2.4 |
com.typesafe.akka | akka-actor_2.11 | 2.3.11 |
ml.combust.mleap | mleap-databricks-runtime_2.11 | 0.13.0 |
ml.dmlc | xgboost4j | 0.90 |
ml.dmlc | xgboost4j-spark | 0.90 |
org.graphframes | graphframes_2.11 | 0.7.0-db1-spark2.4 |
org.tensorflow | libtensorflow | 1.13.1 |
org.tensorflow | libtensorflow_jni | 1.13.1 |
org.tensorflow | spark-tensorflow-connector_2.11 | 1.13.1 |
org.tensorflow | tensorflow | 1.13.1 |
org.tensorframes | tensorframes | 0.7.0-s_2.11 |