Databricks Runtime 13.3 LTS para Machine Learning
Databricks Runtime 13.3 LTS para Machine Learning proporciona un entorno listo para usar, de aprendizaje automático y ciencia de datos, basado en Databricks Runtime 13.3 LTS. Databricks Runtime ML contiene muchas bibliotecas populares de aprendizaje automático, incluidas TensorFlow, PyTorch y XGBoost. Databricks Runtime ML incluye AutoML, una herramienta para entrenar automáticamente canalizaciones de aprendizaje automático. Databricks Runtime ML también admite el entrenamiento de aprendizaje profundo distribuido mediante Horovod.
Nota:
LTS significa que esta versión tiene soporte técnico a largo plazo. Consulte Ciclo de vida de la versión de Databricks Runtime LTS.
Para obtener más información, incluidas las instrucciones para crear un clúster de Databricks Runtime ML, consulte IA y aprendizaje automático en Databricks.
Sugerencia
Para ver las notas de la versión de las versiones de Databricks Runtime que han llegado a la finalización del soporte (EoS), vea las Notas de la versión de finalización del soporte de Databricks Runtime. Las versiones de Databricks Runtime EoS se han retirado y es posible que no se actualicen.
Nuevas características y mejoras
Databricks Runtime 13.3 LTS ML se basa en Databricks Runtime 13.3 LTS. Para más información sobre las novedades de Databricks Runtime 13.3 LTS, incluyendo Apache Spark MLlib y SparkR, consulte las notas de la versión de Databricks Runtime 13.3 LTS.
Cambios en el almacén de características de Databricks
- Databricks Runtime 13.3 LTS ML contiene el cliente del Almacén de características v0.14.0. Con la versión 0.14.0 del cliente y versiones posteriores, debe especificar columnas de clave de marca de tiempo en el argumento
primary_keys. Las claves de marca de tiempo forman parte de las "claves principales" que identifican de forma única cada fila de la tabla de características. - Ahora puede excluir valores de características con marcas de tiempo antes de una hora especificada del conjunto de entrenamiento. Para más información, consulte Establecimiento de un límite de tiempo para los valores de características históricos.
- Las características de aprendizaje automático ahora se pueden calcular a petición en el momento de la inferencia. La lógica de cálculo de las características, los modelos y los datos están regidos por Unity Catalog. Esto permite a los modelos procesar características mediante entradas que solo están disponibles en el momento de la inferencia, como la ubicación actual de un usuario. Para obtener más información, consulte Procesamiento de características a petición mediante funciones definidas por el usuario de Python.
Entorno del sistema
El entorno del sistema en Databricks Runtime 13.3 LTS ML se diferencia del de Databricks Runtime 13.3 LTS en lo siguiente:
- DBUtils: Databricks Runtime ML no incluye la utilidad de biblioteca de (dbutils.library) (heredada).
Use comandos
%pipen su lugar. Consulte Bibliotecas de Python cuyo ámbito es Notebook. - En los clústeres de GPU, Databricks Runtime ML incluye las siguientes bibliotecas de GPU de NVIDIA:
- CUDA 11.7
- cuDNN 8.5.0.96-1
- NCCL 2.15.1
- TensorRT 7.2.2
Databricks Runtime 13.3 LTS ML incluye XGBoost 1.7.3, que no admite clústeres de GPU con capacidad de proceso 5.2 e inferiores.
El paquete miniconda se ha quitado de Databricks Runtime 13.0 ML y versiones posteriores.
Bibliotecas
En las secciones siguientes se enumeran las bibliotecas incluidas en Databricks Runtime 13.3 LTS ML, que difieren de las incluidas en Databricks Runtime 13.3 LTS.
En esta sección:
- Bibliotecas de nivel superior
- Bibliotecas de Python
- Bibliotecas de R
- Bibliotecas de Java y Scala (clúster de Scala 2.12)
Bibliotecas de nivel superior
Databricks Runtime 13.3 LTS ML incluye las siguientes bibliotecas de nivel superior:
- GraphFrames
- Horovod y HorovodRunner
- MLflow
- PyTorch
- spark-tensorflow-connector
- TensorFlow
- TensorBoard
- Scikit-learn
Bibliotecas de Python
Databricks Runtime 13.3 LTS ML usa Virtualenv para la administración de paquetes de Python e incluye muchos paquetes de ML populares.
Además de los paquetes especificados en las secciones siguientes, Databricks Runtime 13.3 LTS ML también incluye los paquetes siguientes:
- hyperopt 0.2.7+db3
- sparkdl 3.0.0_db1
- automl 1.20.0
Para reproducir el entorno de Python de Databricks Runtime ML en el entorno virtual local de Python, descargue el archivo requirements-13.3.txt y ejecute pip install -r requirements-13.3.txt. Este comando instala todas las bibliotecas de código abierto que usa Databricks Runtime ML, pero no instala bibliotecas que desarrolla Databricks, como databricks-automl, databricks-feature-store o la bifurcación de Databricks de hyperopt.
Bibliotecas de Python en clústeres de CPU
| Biblioteca | Versión | Biblioteca | Versión | Biblioteca | Versión |
|---|---|---|---|---|---|
| absl-py | 1.0.0 | accelerate | 0.20.3 | aiohttp | 3.8.5 |
| aiosignal | 1.3.1 | anyio | 3.5.0 | appdirs | 1.4.4 |
| argon2-cffi | 21.3.0 | argon2-cffi-bindings | 21.2.0 | astor | 0.8.1 |
| asttokens | 2.2.1 | astunparse | 1.6.3 | async-timeout | 4.0.2 |
| attrs | 21.4.0 | audioread | 3.0.0 | azure-core | 1.28.0 |
| azure-cosmos | 4.3.1 | azure-storage-blob | 12.17.0 | azure-storage-file-datalake | 12.12.0 |
| backcall | 0.2.0 | bcrypt | 3.2.0 | beautifulsoup4 | 4.11.1 |
| black | 22.6.0 | bleach | 4.1.0 | blinker | 1.4 |
| blis | 0.7.10 | boto3 | 1.24.28 | botocore | 1.27.28 |
| cachetools | 4.2.4 | catalogue | 2.0.9 | category-encoders | 2.6.1 |
| certifi | 2022.9.14 | cffi | 1.15.1 | chardet | 4.0.0 |
| charset-normalizer | 2.0.4 | click | 8.0.4 | cloudpickle | 2.0.0 |
| cmdstanpy | 1.1.0 | confection | 0.1.0 | configparser | 5.2.0 |
| convertdate | 2.4.0 | criptografía | 37.0.1 | cycler | 0.11.0 |
| cymem | 2.0.7 | Cython | 0.29.32 | dacite | 1.8.1 |
| databricks-automl-runtime | 0.2.17 | databricks-cli | 0.17.7 | databricks-feature-store | 0.14.0 |
| databricks-sdk | 0.1.6 | dataclasses-json | 0.5.13 | conjuntos de datos | 2.13.1 |
| dbl-tempo | 0.1.23 | dbus-python | 1.2.18 | debugpy | 1.6.0 |
| decorator | 5.1.1 | defusedxml | 0.7.1 | dill | 0.3.4 |
| diskcache | 5.6.1 | distlib | 0.3.7 | docstring-to-markdown | 0,12 |
| entrypoints | 0,4 | ephem | 4.1.4 | evaluate | 0.4.0 |
| executing | 1.2.0 | facets-overview | 1.0.3 | fastapi | 0.98.0 |
| fastjsonschema | 2.18.0 | fasttext | 0.9.2 | filelock | 3.6.0 |
| Flask | 1.1.2+db1 | flatbuffers | 23.5.26 | fonttools | 4.25.0 |
| frozenlist | 1.4.0 | fsspec | 2022.7.1 | future | 0.18.2 |
| gast | 0.4.0 | gitdb | 4.0.10 | GitPython | 3.1.27 |
| google-api-core | 2.8.2 | google-auth | 1.33.0 | google-auth-oauthlib | 0.4.6 |
| google-cloud-core | 2.3.3 | google-cloud-storage | 2.10.0 | google-crc32c | 1.5.0 |
| google-pasta | 0.2.0 | google-resumable-media | 2.5.0 | googleapis-common-protos | 1.56.4 |
| greenlet | 1.1.1 | grpcio | 1.48.1 | grpcio-status | 1.48.1 |
| gunicorn | 20.1.0 | gviz-api | 1.10.0 | h11 | 0.14.0 |
| h5py | 3.7.0 | holidays | 0.27.1 | horovod | 0.28.1 |
| htmlmin | 0.1.12 | httplib2 | 0.20.2 | httptools | 0.6.0 |
| huggingface-hub | 0.16.4 | idna | 3.3 | ImageHash | 4.3.1 |
| imbalanced-learn | 0.10.1 | importlib-metadata | 4.11.3 | importlib-resources | 6.0.0 |
| ipykernel | 6.17.1 | ipython | 8.10.0 | ipython-genutils | 0.2.0 |
| ipywidgets | 7.7.2 | isodate | 0.6.1 | itsdangerous | 2.0.1 |
| jedi | 0.18.1 | jeepney | 0.7.1 | Jinja2 | 2.11.3 |
| jmespath | 0.10.0 | joblib | 1.2.0 | joblibspark | 0.5.1 |
| jsonschema | 4.16.0 | jupyter-client | 7.3.4 | jupyter_core | 4.11.2 |
| jupyterlab-pygments | 0.1.2 | jupyterlab-widgets | 1.0.0 | keras | 2.11.0 |
| keyring | 23.5.0 | kiwisolver | 1.4.2 | langchain | 0.0.217 |
| langchainplus-sdk | 0.0.20 | langcodes | 3.3.0 | launchpadlib | 1.10.16 |
| lazr.restfulclient | 0.14.4 | lazr.uri | 1.0.6 | lazy_loader | 0,3 |
| libclang | 15.0.6.1 | librosa | 0.10.0 | lightgbm | 3.3.5 |
| llvmlite | 0.38.0 | LunarCalendar | 0.0.9 | Mako | 1.2.0 |
| Markdown | 3.3.4 | MarkupSafe | 2.0.1 | marshmallow | 3.20.1 |
| matplotlib | 3.5.2 | matplotlib-inline | 0.1.6 | mccabe | 0.7.0 |
| mistune | 0.8.4 | mleap | 0.20.0 | mlflow-skinny | 2.5.0 |
| more-itertools | 8.10.0 | msgpack | 1.0.5 | multidict | 6.0.4 |
| multimethod | 1.9.1 | multiprocess | 0.70.12.2 | murmurhash | 1.0.9 |
| mypy-extensions | 0.4.3 | nbclient | 0.5.13 | nbconvert | 6.4.4 |
| nbformat | 5.5.0 | nest-asyncio | 1.5.5 | networkx | 2.8.4 |
| ninja | 1.11.1 | nltk | 3.7 | nodeenv | 1.8.0 |
| notebook | 6.4.12 | numba | 0.55.1 | numexpr | 2.8.4 |
| numpy | 1.21.5 | oauthlib | 3.2.0 | openai | 0.27.8 |
| openapi-schema-pydantic | 1.2.4 | opt-einsum | 3.3.0 | empaquetado | 21,3 |
| pandas | 1.4.4 | pandocfilters | 1.5.0 | paramiko | 2.9.2 |
| parso | 0.8.3 | pathspec | 0.9.0 | pathy | 0.10.2 |
| patsy | 0.5.2 | petastorm | 0.12.1 | pexpect | 4.8.0 |
| phik | 0.12.3 | pickleshare | 0.7.5 | Pillow | 9.2.0 |
| pip | 22.2.2 | platformdirs | 2.5.2 | plotly | 5.9.0 |
| pluggy | 1.0.0 | pmdarima | 2.0.3 | pooch | 1.7.0 |
| preshed | 3.0.8 | prometheus-client | 0.14.1 | prompt-toolkit | 3.0.36 |
| prophet | 1.1.4 | protobuf | 3.19.4 | psutil | 5.9.0 |
| psycopg2 | 2.9.3 | ptyprocess | 0.7.0 | pure-eval | 0.2.2 |
| pyarrow | 8.0.0 | pyasn1 | 0.4.8 | pyasn1-modules | 0.2.8 |
| pybind11 | 2.11.1 | pycparser | 2.21 | pydantic | 1.10.6 |
| pyflakes | 3.0.1 | Pygments | 2.11.2 | PyGObject | 3.42.1 |
| PyJWT | 2.3.0 | PyMeeus | 0.5.12 | PyNaCl | 1.5.0 |
| pyodbc | 4.0.32 | pyparsing | 3.0.9 | pyright | 1.1.294 |
| pyrsistent | 0.18.0 | pytesseract | 0.3.10 | Python-dateutil | 2.8.2 |
| python-dotenv | 1.0.0 | python-editor | 1.0.4 | python-lsp-jsonrpc | 1.0.0 |
| python-lsp-server | 1.7.1 | pytoolconfig | 1.2.2 | pytz | 2022.1 |
| PyWavelets | 1.3.0 | PyYAML | 6.0 | pyzmq | 23.2.0 |
| regex | 2022.7.9 | requests | 2.28.1 | requests-oauthlib | 1.3.1 |
| responses | 0.18.0 | rope | 1.7.0 | rsa | 4,9 |
| s3transfer | 0.6.0 | safetensors | 0.3.1 | scikit-learn | 1.1.1 |
| scipy | 1.9.1 | seaborn | 0.11.2 | SecretStorage | 3.3.1 |
| Send2Trash | 1.8.0 | sentence-transformers | 2.2.2 | sentencepiece | 0.1.99 |
| setuptools | 63.4.1 | shap | 0.41.0 | simplejson | 3.17.6 |
| six (seis) | 1.16.0 | segmentación | 0.0.7 | smart-open | 5.2.1 |
| smmap | 5.0.0 | sniffio | 1.2.0 | soundfile | 0.12.1 |
| soupsieve | 2.3.1 | soxr | 0.3.5 | spacy | 3.5.3 |
| spacy-legacy | 3.0.12 | spacy-loggers | 1.0.4 | spark-tensorflow-distributor | 1.0.0 |
| SQLAlchemy | 1.4.39 | sqlparse | 0.4.2 | srsly | 2.4.7 |
| ssh-import-id | 5.11 | stack-data | 0.6.2 | starlette | 0.27.0 |
| statsmodels | 0.13.2 | tabulate | 0.8.10 | tangled-up-in-unicode | 0.2.0 |
| tenacity | 8.1.0 | tensorboard | 2.11.0 | tensorboard-data-server | 0.6.1 |
| tensorboard-plugin-profile | 2.11.2 | tensorboard-plugin-wit | 1.8.1 | tensorflow-cpu | 2.11.1 |
| tensorflow-estimator | 2.11.0 | tensorflow-io-gcs-filesystem | 0.32.0 | termcolor | 2.3.0 |
| terminado | 0.13.1 | testpath | 0.6.0 | thinc | 8.1.10 |
| threadpoolctl | 2.2.0 | tiktoken | 0.4.0 | tokenize-rt | 4.2.1 |
| tokenizers | 0.13.3 | tomli | 2.0.1 | torch | 1.13.1+cpu |
| torchvision | 0.14.1+cpu | tornado | 6.1 | tqdm | 4.64.1 |
| traitlets | 5.1.1 | transformers | 4.30.2 | typeguard | 2.13.3 |
| typer | 0.7.0 | typing-inspect | 0.9.0 | typing_extensions | 4.3.0 |
| ujson | 5.4.0 | unattended-upgrades | 0,1 | urllib3 | 1.26.11 |
| uvicorn | 0.23.1 | uvloop | 0.17.0 | virtualenv | 20.16.3 |
| visions | 0.7.5 | wadllib | 1.3.6 | wasabi | 1.1.2 |
| watchfiles | 0.19.0 | wcwidth | 0.2.5 | webencodings | 0.5.1 |
| websocket-client | 0.58.0 | websockets | 11.0.3 | Werkzeug | 2.0.3 |
| whatthepatch | 1.0.2 | wheel | 0.37.1 | widgetsnbextension | 3.6.1 |
| wordcloud | 1.9.2 | wrapt | 1.14.1 | xgboost | 1.7.6 |
| xxhash | 3.2.0 | yapf | 0.31.0 | yarl | 1.9.2 |
| ydata-profiling | 4.2.0 | zipp | 3.8.0 |
Bibliotecas de Python en clústeres de GPU
| Biblioteca | Versión | Biblioteca | Versión | Biblioteca | Versión |
|---|---|---|---|---|---|
| absl-py | 1.0.0 | accelerate | 0.20.3 | aiohttp | 3.8.5 |
| aiosignal | 1.3.1 | anyio | 3.5.0 | appdirs | 1.4.4 |
| argon2-cffi | 21.3.0 | argon2-cffi-bindings | 21.2.0 | astor | 0.8.1 |
| asttokens | 2.2.1 | astunparse | 1.6.3 | async-timeout | 4.0.2 |
| attrs | 21.4.0 | audioread | 3.0.0 | azure-core | 1.28.0 |
| azure-cosmos | 4.3.1 | azure-storage-blob | 12.17.0 | azure-storage-file-datalake | 12.12.0 |
| backcall | 0.2.0 | bcrypt | 3.2.0 | beautifulsoup4 | 4.11.1 |
| black | 22.6.0 | bleach | 4.1.0 | blinker | 1.4 |
| blis | 0.7.10 | boto3 | 1.24.28 | botocore | 1.27.28 |
| cachetools | 4.2.4 | catalogue | 2.0.9 | category-encoders | 2.6.1 |
| certifi | 2022.9.14 | cffi | 1.15.1 | chardet | 4.0.0 |
| charset-normalizer | 2.0.4 | click | 8.0.4 | cloudpickle | 2.0.0 |
| cmdstanpy | 1.1.0 | confection | 0.1.0 | configparser | 5.2.0 |
| convertdate | 2.4.0 | criptografía | 37.0.1 | cycler | 0.11.0 |
| cymem | 2.0.7 | Cython | 0.29.32 | dacite | 1.8.1 |
| databricks-automl-runtime | 0.2.17 | databricks-cli | 0.17.7 | databricks-feature-store | 0.14.0 |
| databricks-sdk | 0.1.6 | dataclasses-json | 0.5.13 | conjuntos de datos | 2.13.1 |
| dbl-tempo | 0.1.23 | dbus-python | 1.2.18 | debugpy | 1.6.0 |
| decorator | 5.1.1 | defusedxml | 0.7.1 | dill | 0.3.4 |
| diskcache | 5.6.1 | distlib | 0.3.7 | docstring-to-markdown | 0,12 |
| einops | 0.6.1 | entrypoints | 0,4 | ephem | 4.1.4 |
| evaluate | 0.4.0 | executing | 1.2.0 | facets-overview | 1.0.3 |
| fastapi | 0.98.0 | fastjsonschema | 2.18.0 | fasttext | 0.9.2 |
| filelock | 3.6.0 | flash-attn | 1.0.7 | Flask | 1.1.2+db1 |
| flatbuffers | 23.5.26 | fonttools | 4.25.0 | frozenlist | 1.4.0 |
| fsspec | 2022.7.1 | future | 0.18.2 | gast | 0.4.0 |
| gitdb | 4.0.10 | GitPython | 3.1.27 | google-api-core | 2.8.2 |
| google-auth | 1.33.0 | google-auth-oauthlib | 0.4.6 | google-cloud-core | 2.3.3 |
| google-cloud-storage | 2.10.0 | google-crc32c | 1.5.0 | google-pasta | 0.2.0 |
| google-resumable-media | 2.5.0 | googleapis-common-protos | 1.56.4 | greenlet | 1.1.1 |
| grpcio | 1.48.1 | grpcio-status | 1.48.1 | gunicorn | 20.1.0 |
| gviz-api | 1.10.0 | h11 | 0.14.0 | h5py | 3.7.0 |
| holidays | 0.27.1 | horovod | 0.28.1 | htmlmin | 0.1.12 |
| httplib2 | 0.20.2 | httptools | 0.6.0 | huggingface-hub | 0.16.4 |
| idna | 3.3 | ImageHash | 4.3.1 | imbalanced-learn | 0.10.1 |
| importlib-metadata | 4.11.3 | importlib-resources | 6.0.0 | ipykernel | 6.17.1 |
| ipython | 8.10.0 | ipython-genutils | 0.2.0 | ipywidgets | 7.7.2 |
| isodate | 0.6.1 | itsdangerous | 2.0.1 | jedi | 0.18.1 |
| jeepney | 0.7.1 | Jinja2 | 2.11.3 | jmespath | 0.10.0 |
| joblib | 1.2.0 | joblibspark | 0.5.1 | jsonschema | 4.16.0 |
| jupyter-client | 7.3.4 | jupyter_core | 4.11.2 | jupyterlab-pygments | 0.1.2 |
| jupyterlab-widgets | 1.0.0 | keras | 2.11.0 | keyring | 23.5.0 |
| kiwisolver | 1.4.2 | langchain | 0.0.217 | langchainplus-sdk | 0.0.20 |
| langcodes | 3.3.0 | launchpadlib | 1.10.16 | lazr.restfulclient | 0.14.4 |
| lazr.uri | 1.0.6 | lazy_loader | 0,3 | libclang | 15.0.6.1 |
| librosa | 0.10.0 | lightgbm | 3.3.5 | llvmlite | 0.38.0 |
| LunarCalendar | 0.0.9 | Mako | 1.2.0 | Markdown | 3.3.4 |
| MarkupSafe | 2.0.1 | marshmallow | 3.20.1 | matplotlib | 3.5.2 |
| matplotlib-inline | 0.1.6 | mccabe | 0.7.0 | mistune | 0.8.4 |
| mleap | 0.20.0 | mlflow-skinny | 2.5.0 | more-itertools | 8.10.0 |
| msgpack | 1.0.5 | multidict | 6.0.4 | multimethod | 1.9.1 |
| multiprocess | 0.70.12.2 | murmurhash | 1.0.9 | mypy-extensions | 0.4.3 |
| nbclient | 0.5.13 | nbconvert | 6.4.4 | nbformat | 5.5.0 |
| nest-asyncio | 1.5.5 | networkx | 2.8.4 | ninja | 1.11.1 |
| nltk | 3.7 | nodeenv | 1.8.0 | notebook | 6.4.12 |
| numba | 0.55.1 | numexpr | 2.8.4 | numpy | 1.21.5 |
| oauthlib | 3.2.0 | openai | 0.27.8 | openapi-schema-pydantic | 1.2.4 |
| opt-einsum | 3.3.0 | empaquetado | 21,3 | pandas | 1.4.4 |
| pandocfilters | 1.5.0 | paramiko | 2.9.2 | parso | 0.8.3 |
| pathspec | 0.9.0 | pathy | 0.10.2 | patsy | 0.5.2 |
| petastorm | 0.12.1 | pexpect | 4.8.0 | phik | 0.12.3 |
| pickleshare | 0.7.5 | Pillow | 9.2.0 | pip | 22.2.2 |
| platformdirs | 2.5.2 | plotly | 5.9.0 | pluggy | 1.0.0 |
| pmdarima | 2.0.3 | pooch | 1.7.0 | preshed | 3.0.8 |
| prompt-toolkit | 3.0.36 | prophet | 1.1.4 | protobuf | 3.19.4 |
| psutil | 5.9.0 | psycopg2 | 2.9.3 | ptyprocess | 0.7.0 |
| pure-eval | 0.2.2 | pyarrow | 8.0.0 | pyasn1 | 0.4.8 |
| pyasn1-modules | 0.2.8 | pybind11 | 2.11.1 | pycparser | 2.21 |
| pydantic | 1.10.6 | pyflakes | 3.0.1 | Pygments | 2.11.2 |
| PyGObject | 3.42.1 | PyJWT | 2.3.0 | PyMeeus | 0.5.12 |
| PyNaCl | 1.5.0 | pyodbc | 4.0.32 | pyparsing | 3.0.9 |
| pyright | 1.1.294 | pyrsistent | 0.18.0 | pytesseract | 0.3.10 |
| Python-dateutil | 2.8.2 | python-dotenv | 1.0.0 | python-editor | 1.0.4 |
| python-lsp-jsonrpc | 1.0.0 | python-lsp-server | 1.7.1 | pytoolconfig | 1.2.2 |
| pytz | 2022.1 | PyWavelets | 1.3.0 | PyYAML | 6.0 |
| pyzmq | 23.2.0 | regex | 2022.7.9 | requests | 2.28.1 |
| requests-oauthlib | 1.3.1 | responses | 0.18.0 | rope | 1.7.0 |
| rsa | 4,9 | s3transfer | 0.6.0 | safetensors | 0.3.1 |
| scikit-learn | 1.1.1 | scipy | 1.9.1 | seaborn | 0.11.2 |
| SecretStorage | 3.3.1 | Send2Trash | 1.8.0 | sentence-transformers | 2.2.2 |
| sentencepiece | 0.1.99 | setuptools | 63.4.1 | shap | 0.41.0 |
| simplejson | 3.17.6 | six (seis) | 1.16.0 | segmentación | 0.0.7 |
| smart-open | 5.2.1 | smmap | 5.0.0 | sniffio | 1.2.0 |
| soundfile | 0.12.1 | soupsieve | 2.3.1 | soxr | 0.3.5 |
| spacy | 3.5.3 | spacy-legacy | 3.0.12 | spacy-loggers | 1.0.4 |
| spark-tensorflow-distributor | 1.0.0 | SQLAlchemy | 1.4.39 | sqlparse | 0.4.2 |
| srsly | 2.4.7 | ssh-import-id | 5.11 | stack-data | 0.6.2 |
| starlette | 0.27.0 | statsmodels | 0.13.2 | tabulate | 0.8.10 |
| tangled-up-in-unicode | 0.2.0 | tenacity | 8.1.0 | tensorboard | 2.11.0 |
| tensorboard-data-server | 0.6.1 | tensorboard-plugin-profile | 2.11.2 | tensorboard-plugin-wit | 1.8.1 |
| tensorflow | 2.11.1 | tensorflow-estimator | 2.11.0 | tensorflow-io-gcs-filesystem | 0.32.0 |
| termcolor | 2.3.0 | terminado | 0.13.1 | testpath | 0.6.0 |
| thinc | 8.1.10 | threadpoolctl | 2.2.0 | tiktoken | 0.4.0 |
| tokenize-rt | 4.2.1 | tokenizers | 0.13.3 | tomli | 2.0.1 |
| torch | 1.13.1+cu117 | torchvision | 0.14.1+cu117 | tornado | 6.1 |
| tqdm | 4.64.1 | traitlets | 5.1.1 | transformers | 4.30.2 |
| typeguard | 2.13.3 | typer | 0.7.0 | typing-inspect | 0.9.0 |
| typing_extensions | 4.3.0 | ujson | 5.4.0 | unattended-upgrades | 0,1 |
| urllib3 | 1.26.11 | uvicorn | 0.23.1 | uvloop | 0.17.0 |
| virtualenv | 20.16.3 | visions | 0.7.5 | wadllib | 1.3.6 |
| wasabi | 1.1.2 | watchfiles | 0.19.0 | wcwidth | 0.2.5 |
| webencodings | 0.5.1 | websocket-client | 0.58.0 | websockets | 11.0.3 |
| Werkzeug | 2.0.3 | whatthepatch | 1.0.2 | wheel | 0.37.1 |
| widgetsnbextension | 3.6.1 | wordcloud | 1.9.2 | wrapt | 1.14.1 |
| xgboost | 1.7.6 | xxhash | 3.2.0 | yapf | 0.31.0 |
| yarl | 1.9.2 | ydata-profiling | 4.2.0 | zipp | 3.8.0 |
Bibliotecas de R
Las bibliotecas de R son idénticas a las bibliotecas de R de Databricks Runtime 13.3 LTS.
Bibliotecas de Java y Scala (clúster de Scala 2.12)
Además de las bibliotecas de Java y Scala de Databricks Runtime 13.3 LTS, Databricks Runtime 13.3 LTS ML contiene los siguientes JAR:
Clústeres de CPU
| Identificador de grupo | Identificador de artefacto | Versión |
|---|---|---|
| com.typesafe.akka | akka-actor_2.12 | 2.5.23 |
| ml.dmlc | xgboost4j-spark_2.12 | 1.7.3 |
| ml.dmlc | xgboost4j_2.12 | 1.7.3 |
| org.graphframes | graphframes_2.12 | 0.8.2-db2-spark3.4 |
| org.mlflow | mlflow-client | 2.5.0 |
| org.scala-lang.modules | scala-java8-compat_2.12 | 0.8.0 |
| org.tensorflow | spark-tensorflow-connector_2.12 | 1.15.0 |
Clústeres de GPU
| Identificador de grupo | Identificador de artefacto | Versión |
|---|---|---|
| com.typesafe.akka | akka-actor_2.12 | 2.5.23 |
| ml.dmlc | xgboost4j-gpu_2.12 | 1.7.3 |
| ml.dmlc | xgboost4j-spark-gpu_2.12 | 1.7.3 |
| org.graphframes | graphframes_2.12 | 0.8.2-db2-spark3.4 |
| org.mlflow | mlflow-client | 2.5.0 |
| org.scala-lang.modules | scala-java8-compat_2.12 | 0.8.0 |
| org.tensorflow | spark-tensorflow-connector_2.12 | 1.15.0 |