Databricks Runtime 15.1 para Machine Learning (EoS)
Nota:
El soporte técnico con esta versión de Databricks Runtime ha finalizado. Para obtener la fecha de finalización del soporte técnico, consulte Historial de finalización del soporte técnico. Para ver todas las versiones de Databricks Runtime con soporte técnico, consulte las notas de la versión de Databricks Runtime versiones y compatibilidad.
Databricks Runtime 15.1 para Machine Learning proporciona un entorno listo para usar para el aprendizaje automático y la ciencia de datos basado en Databricks Runtime 15.1 (EoS). 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.
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 15.1 ML se basa en Databricks Runtime 15.1. Para obtener información sobre las novedades de Databricks Runtime 15.1, incluidas las notas de la versión de Databricks Runtime 15.1 (EoS), incluidos Apache Spark MLlib y SparkR, consulte las notas de la versión de Databricks Runtime 15.1 (EoS).
Cambios importantes
La CLI de Databricks heredada ya no está instalada de forma predeterminada
En Databricks Runtime 14.3 LTS ML y versiones anteriores, ya que la versión preinstalada de MLflow requería la CLI heredada de Databricks, se instaló automáticamente en $PATH. Databricks Runtime 15.1 ML incluye MLflow versión 2.10.2, que no requiere la CLI heredada.
A partir de Databricks Runtime 15.1 ML, la CLI heredada de Databricks ya no se instala automáticamente en $PATH. Se trata de un cambio importante para los usuarios que dependen de la CLI heredada que se instala en tiempo de ejecución. Los comandos como %sh databricks ... ya no funcionan en Databricks Runtime 15.1 ML y versiones posteriores.
Para seguir usando la CLI heredada de Databricks desde un cuaderno, instálela como un clúster o biblioteca de cuadernos. La nueva CLI de Databricks está disponible en el terminal web. Para más información, consulte Uso del terminal web y la CLIde Databricks.
MLeap ya no está disponible a partir de Databricks Runtime 15.1 ML
MLeap ya no está disponible en Databricks Runtime 15.1 ML y versiones posteriores. Para empaquetar modelos para la implementación en marcos basados en JVM, Databricks recomienda usar el formatoONNX.
Desuso de Horovod y HorovodRunner
Horovod y HorovodRunner ya están en desuso. Para el aprendizaje profundo distribuido, Databricks recomienda usar TorchDistributor para el entrenamiento distribuido con PyTorch o la API para el tf.distribute.Strategy entrenamiento distribuido con TensorFlow. Horovod y HorovodRunner están preinstalados en Databricks Runtime 15.1 ML, pero se quitarán en la siguiente versión principal de Databricks Runtime ML.
Nota:
horovod.spark no admite las versiones 11.0 y posteriores de pyarrow (consulte el problema de GitHub pertinente). Databricks Runtime 15.1 ML incluye pyarrow versión 14.0.1. Para usar horovod.spark con Databricks Runtime 15.1 ML o superior, debe instalar manualmente pyarrow, especificando una versión inferior a 11.0.
Entorno del sistema
El entorno del sistema de Databricks Runtime 15.1 ML se diferencia del de Databricks Runtime 15.1 en los siguientes aspectos:
- En los clústeres de GPU, Databricks Runtime ML incluye las siguientes bibliotecas de GPU de NVIDIA:
- CUDA 12.1
- cuDNN 8.9.0.131-1
- NCCL 2.17.1
- TensorRT 8.6.1.6-1
Bibliotecas
En las siguientes secciones, se enumeran las bibliotecas que se incluyen en Databricks Runtime 15.1 ML, que difieren de las que se incluyen en Databricks Runtime 15.1.
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 15.1 ML incluye las siguientes bibliotecas de nivel superior:
- GraphFrames
- MLflow
- PyTorch
- spark-tensorflow-connector
- TensorFlow
- TensorBoard
- Scikit-learn
- (en desuso) Horovod y HorovodRunner
Bibliotecas de Python
Databricks Runtime 15.1 ML usa virtualenv para la administración de los paquetes de Python, e incluye muchos paquetes populares de ML.
Además de los paquetes especificados en las siguientes secciones, Databricks Runtime 15.1 ML también incluye estos paquetes:
- hyperopt 0.2.7.db4
- sparkdl 3.0.0_db1
- automl 1.25.0
Para reproducir el entorno de Python de Databricks Runtime ML en el entorno virtual local de Python, descargue el archivo requirements-15.1.txt y ejecute pip install -r requirements-15.1.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 | 0.25.0 | aiohttp | 3.8.5 |
| aiohttp-cors | 0.7.0 | aiosignal | 1.2.0 | anyio | 3.5.0 |
| argon2-cffi | 21.3.0 | argon2-cffi-bindings | 21.2.0 | astor | 0.8.1 |
| asttokens | 2.0.5 | astunparse | 1.6.3 | async-timeout | 4.0.2 |
| attrs | 22.1.0 | audioread | 3.0.1 | azure-core | 1.30.1 |
| azure-cosmos | 4.3.1 | azure-storage-blob | 12.19.0 | azure-storage-file-datalake | 12.14.0 |
| backcall | 0.2.0 | bcrypt | 3.2.0 | beautifulsoup4 | 4.12.2 |
| black | 23.3.0 | bleach | 4.1.0 | Bendecido | 1.20.0 |
| blinker | 1.4 | blis | 0.7.11 | boto3 | 1.34.39 |
| botocore | 1.34.39 | cachetools | 5.3.3 | catalogue | 2.0.10 |
| category-encoders | 2.6.3 | certifi | 2023.7.22 | cffi | 1.15.1 |
| chardet | 4.0.0 | charset-normalizer | 2.0.4 | click | 8.0.4 |
| cloudpathlib | 0.16.0 | cloudpickle | 2.2.1 | cmdstanpy | 1.2.1 |
| multicolor | 0.5.6 | comm | 0.1.2 | confection | 0.1.4 |
| configparser | 5.2.0 | contourpy | 1.0.5 | criptografía | 41.0.3 |
| cycler | 0.11.0 | cymem | 2.0.8 | Cython | 0.29.32 |
| dacite | 1.8.1 | databricks-automl-runtime | 0.2.21 | databricks-feature-engineering | 0.3.0 |
| databricks-sdk | 0.20.0 | dataclasses-json | 0.6.4 | conjuntos de datos | 2.16.1 |
| dbl-tempo | 0.1.26 | dbus-python | 1.2.18 | debugpy | 1.6.7 |
| decorator | 5.1.1 | deepspeed | 0.13.1 | defusedxml | 0.7.1 |
| dill | 0.3.6 | diskcache | 5.6.3 | distlib | 0.3.8 |
| dm-tree | 0.1.8 | entrypoints | 0,4 | evaluate | 0.4.1 |
| executing | 0.8.3 | facets-overview | 1.1.1 | Farama-Notifications | 0.0.4 |
| fastjsonschema | 2.19.1 | fasttext | 0.9.2 | filelock | 3.9.0 |
| Flask | 2.2.5 | flatbuffers | 23.5.26 | fonttools | 4.25.0 |
| frozenlist | 1.3.3 | fsspec | 2023.5.0 | future | 0.18.3 |
| gast | 0.4.0 | gitdb | 4.0.11 | GitPython | 3.1.27 |
| google-api-core | 2.17.1 | google-auth | 2.21.0 | google-auth-oauthlib | 1.0.0 |
| google-cloud-core | 2.4.1 | google-cloud-storage | 2.11.0 | google-crc32c | 1.5.0 |
| google-pasta | 0.2.0 | google-resumable-media | 2.7.0 | googleapis-common-protos | 1.62.0 |
| gpustat | 1.1.1 | greenlet | 2.0.1 | grpcio | 1.60.0 |
| grpcio-status | 1.60.0 | gunicorn | 20.1.0 | gviz-api | 1.10.0 |
| Gimnasio | 0.28.1 | h11 | 0.14.0 | h5py | 3.9.0 |
| hjson | 3.1.0 | holidays | 0,38 | horovod | 0.28.1+db1 |
| htmlmin | 0.1.12 | httpcore | 1.0.4 | httplib2 | 0.20.2 |
| httpx | 0.27.0 | huggingface-hub | 0.20.2 | idna | 3.4 |
| ImageHash | 4.3.1 | imageio | 2.31.1 | imbalanced-learn | 0.11.0 |
| importlib-metadata | 6.0.0 | importlib_resources | 6.1.2 | ipyflow-core | 0.0.198 |
| ipykernel | 6.25.1 | ipython | 8.15.0 | ipython-genutils | 0.2.0 |
| ipywidgets | 8.0.4 | isodate | 0.6.1 | itsdangerous | 2.0.1 |
| jax-jumpy | 1.0.0 | jedi | 0.18.1 | jeepney | 0.7.1 |
| Jinja2 | 3.1.2 | jmespath | 0.10.0 | joblib | 1.2.0 |
| joblibspark | 0.5.1 | jsonpatch | 1.33 | jsonpointer | 2.4 |
| jsonschema | 4.17.3 | jupyter-server | 1.23.4 | jupyter_client | 7.4.9 |
| jupyter_core | 5.3.0 | jupyterlab-pygments | 0.1.2 | jupyterlab-widgets | 3.0.5 |
| keras | 2.15.0 | keyring | 23.5.0 | kiwisolver | 1.4.4 |
| langchain | 0.1.3 | langchain-community | 0.0.20 | langchain-core | 0.1.23 |
| langcodes | 3.3.0 | langsmith | 0.0.87 | launchpadlib | 1.10.16 |
| lazr.restfulclient | 0.14.4 | lazr.uri | 1.0.6 | lazy_loader | 0,2 |
| libclang | 16.0.6 | librosa | 0.10.1 | lightgbm | 4.2.0 |
| llvmlite | 0.40.0 | lxml | 4.9.2 | lz4 | 4.3.2 |
| Mako | 1.2.0 | Markdown | 3.4.1 | markdown-it-py | 2.2.0 |
| MarkupSafe | 2.1.1 | marshmallow | 3.21.1 | matplotlib | 3.7.2 |
| matplotlib-inline | 0.1.6 | mdurl | 0.1.0 | mistune | 0.8.4 |
| ml-dtypes | 0.2.0 | mlflow-skinny | 2.10.2 | more-itertools | 8.10.0 |
| mpmath | 1.3.0 | msgpack | 1.0.8 | multidict | 6.0.2 |
| multimethod | 1.11.2 | multiprocess | 0.70.14 | murmurhash | 1.0.10 |
| mypy-extensions | 0.4.3 | nbclassic | 0.5.5 | nbclient | 0.5.13 |
| nbconvert | 6.5.4 | nbformat | 5.7.0 | nest-asyncio | 1.5.6 |
| networkx | 3.1 | ninja | 1.11.1.1 | nltk | 3.8.1 |
| notebook | 6.5.4 | notebook_shim | 0.2.2 | numba | 0.57.1 |
| numpy | 1.23.5 | nvidia-ml-py | 12.535.133 | oauthlib | 3.2.0 |
| openai | 1.9.0 | opencensus==0.7.13 | 0.11.4 | opencensus-context==0.1.2 | 0.1.3 |
| opt-einsum | 3.3.0 | empaquetado | 23,2 | pandas | 1.5.3 |
| pandocfilters | 1.5.0 | paramiko | 2.9.2 | parso | 0.8.3 |
| pathspec | 0.10.3 | patsy | 0.5.3 | petastorm | 0.12.1 |
| pexpect | 4.8.0 | phik | 0.12.4 | pickleshare | 0.7.5 |
| Pillow | 9.4.0 | pip | 23.2.1 | platformdirs | 3.10.0 |
| plotly | 5.9.0 | pmdarima | 2.0.4 | pooch | 1.8.1 |
| preshed | 3.0.9 | prometheus-client | 0.14.1 | prompt-toolkit | 3.0.36 |
| prophet | 1.1.5 | protobuf | 4.24.1 | psutil | 5.9.0 |
| psycopg2 | 2.9.3 | ptyprocess | 0.7.0 | pure-eval | 0.2.2 |
| py-cpuinfo | 8.0.0 | py-spy | 0.3.14 | pyarrow | 14.0.1 |
| pyarrow-hotfix | 0.6 | pyasn1 | 0.4.8 | pyasn1-modules | 0.2.8 |
| pybind11 | 2.11.1 | pyccolo | 0.0.52 | pycparser | 2.21 |
| pydantic | 1.10.6 | Pygments | 2.15.1 | PyGObject | 3.42.1 |
| PyJWT | 2.3.0 | PyNaCl | 1.5.0 | pynvml | 11.5.0 |
| pyodbc | 4.0.38 | pyparsing | 3.0.9 | pyrsistent | 0.18.0 |
| pytesseract | 0.3.10 | Python-dateutil | 2.8.2 | python-editor | 1.0.4 |
| python-lsp-jsonrpc | 1.1.1 | pytz | 2022.7 | PyWavelets | 1.4.1 |
| PyYAML | 6.0 | pyzmq | 23.2.0 | Ray | 2.9.3 |
| regex | 2022.7.9 | requests | 2.31.0 | requests-oauthlib | 1.3.1 |
| responses | 0.13.3 | rich | 13.7.1 | rsa | 4,9 |
| s3transfer | 0.10.0 | safetensors | 0.3.2 | scikit-image | 0.20.0 |
| scikit-learn | 1.3.0 | scipy | 1.11.1 | seaborn | 0.12.2 |
| SecretStorage | 3.3.1 | Send2Trash | 1.8.0 | sentence-transformers | 2.2.2 |
| sentencepiece | 0.1.99 | setuptools | 68.0.0 | shap | 0.44.0 |
| 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 | 2.4 | soxr | 0.3.7 |
| spacy | 3.7.2 | spacy-legacy | 3.0.12 | spacy-loggers | 1.0.5 |
| spark-tensorflow-distributor | 1.0.0 | SQLAlchemy | 1.4.39 | sqlparse | 0.4.2 |
| srsly | 2.4.8 | ssh-import-id | 5.11 | stack-data | 0.2.0 |
| stanio | 0.3.0 | statsmodels | 0.14.0 | sympy | 1.11.1 |
| tangled-up-in-unicode | 0.2.0 | tenacity | 8.2.2 | tensorboard | 2.15.1 |
| tensorboard-data-server | 0.7.2 | tensorboard-plugin-profile | 2.15.0 | tensorboardX | 2.6.2.2 |
| tensorflow-cpu | 2.15.0 | tensorflow-estimator | 2.15.0 | tensorflow-io-gcs-filesystem | 0.36.0 |
| termcolor | 2.4.0 | terminado | 0.17.1 | thinc | 8.2.3 |
| threadpoolctl | 2.2.0 | tifffile | 2021.7.2 | tiktoken | 0.5.2 |
| tinycss2 | 1.2.1 | tokenize-rt | 4.2.1 | tokenizers | 0.15.0 |
| torch | 2.1.2+cpu | torcheval | 0.0.7 | torchvision | 0.16.2+cpu |
| tornado | 6.3.2 | tqdm | 4.65.0 | traitlets | 5.7.1 |
| transformers | 4.36.2 | typeguard | 2.13.3 | typer | 0.9.0 |
| typing-inspect | 0.9.0 | typing_extensions | 4.7.1 | tzdata | 2022.1 |
| ujson | 5.4.0 | unattended-upgrades | 0,1 | urllib3 | 1.26.16 |
| virtualenv | 20.21.0 | visions | 0.7.5 | wadllib | 1.3.6 |
| wasabi | 1.1.2 | wcwidth | 0.2.5 | weasel | 0.3.4 |
| webencodings | 0.5.1 | websocket-client | 0.58.0 | Werkzeug | 2.2.3 |
| wheel | 0.38.4 | widgetsnbextension | 4.0.5 | wordcloud | 1.9.3 |
| wrapt | 1.14.1 | xgboost | 2.0.3 | xxhash | 3.4.1 |
| yarl | 1.8.1 | ydata-profiling | 4.5.1 | zipp | 3.11.0 |
Bibliotecas de Python en clústeres de GPU
| Biblioteca | Versión | Biblioteca | Versión | Biblioteca | Versión |
|---|---|---|---|---|---|
| absl-py | 1.0.0 | accelerate | 0.25.0 | aiohttp | 3.8.5 |
| aiohttp-cors | 0.7.0 | aiosignal | 1.2.0 | anyio | 3.5.0 |
| argon2-cffi | 21.3.0 | argon2-cffi-bindings | 21.2.0 | astor | 0.8.1 |
| asttokens | 2.0.5 | astunparse | 1.6.3 | async-timeout | 4.0.2 |
| attrs | 22.1.0 | audioread | 3.0.1 | azure-core | 1.30.1 |
| azure-cosmos | 4.3.1 | azure-storage-blob | 12.19.0 | azure-storage-file-datalake | 12.14.0 |
| backcall | 0.2.0 | bcrypt | 3.2.0 | beautifulsoup4 | 4.12.2 |
| black | 23.3.0 | bleach | 4.1.0 | Bendecido | 1.20.0 |
| blinker | 1.4 | blis | 0.7.11 | boto3 | 1.34.39 |
| botocore | 1.34.39 | cachetools | 5.3.3 | catalogue | 2.0.10 |
| category-encoders | 2.6.3 | certifi | 2023.7.22 | cffi | 1.15.1 |
| chardet | 4.0.0 | charset-normalizer | 2.0.4 | click | 8.0.4 |
| cloudpathlib | 0.16.0 | cloudpickle | 2.2.1 | cmdstanpy | 1.2.1 |
| multicolor | 0.5.6 | comm | 0.1.2 | confection | 0.1.4 |
| configparser | 5.2.0 | contourpy | 1.0.5 | criptografía | 41.0.3 |
| cycler | 0.11.0 | cymem | 2.0.8 | Cython | 0.29.32 |
| dacite | 1.8.1 | databricks-automl-runtime | 0.2.21 | databricks-feature-engineering | 0.3.0 |
| databricks-sdk | 0.20.0 | dataclasses-json | 0.6.4 | conjuntos de datos | 2.16.1 |
| dbl-tempo | 0.1.26 | dbus-python | 1.2.18 | debugpy | 1.6.7 |
| decorator | 5.1.1 | deepspeed | 0.13.1 | defusedxml | 0.7.1 |
| dill | 0.3.6 | diskcache | 5.6.3 | distlib | 0.3.8 |
| dm-tree | 0.1.8 | einops | 0.7.0 | entrypoints | 0,4 |
| evaluate | 0.4.1 | executing | 0.8.3 | facets-overview | 1.1.1 |
| Farama-Notifications | 0.0.4 | fastjsonschema | 2.19.1 | fasttext | 0.9.2 |
| filelock | 3.9.0 | flash-attn | 2.5.0 | Flask | 2.2.5 |
| flatbuffers | 23.5.26 | fonttools | 4.25.0 | frozenlist | 1.3.3 |
| fsspec | 2023.5.0 | future | 0.18.3 | gast | 0.4.0 |
| gitdb | 4.0.11 | GitPython | 3.1.27 | google-api-core | 2.17.1 |
| google-auth | 2.21.0 | google-auth-oauthlib | 1.0.0 | google-cloud-core | 2.4.1 |
| google-cloud-storage | 2.11.0 | google-crc32c | 1.5.0 | google-pasta | 0.2.0 |
| google-resumable-media | 2.7.0 | googleapis-common-protos | 1.62.0 | gpustat | 1.1.1 |
| greenlet | 2.0.1 | grpcio | 1.60.0 | grpcio-status | 1.60.0 |
| gunicorn | 20.1.0 | gviz-api | 1.10.0 | Gimnasio | 0.28.1 |
| h11 | 0.14.0 | h5py | 3.9.0 | hjson | 3.1.0 |
| holidays | 0,38 | horovod | 0.28.1+db1 | htmlmin | 0.1.12 |
| httpcore | 1.0.4 | httplib2 | 0.20.2 | httpx | 0.27.0 |
| huggingface-hub | 0.20.2 | idna | 3.4 | ImageHash | 4.3.1 |
| imageio | 2.31.1 | imbalanced-learn | 0.11.0 | importlib-metadata | 6.0.0 |
| importlib_resources | 6.1.2 | ipyflow-core | 0.0.198 | ipykernel | 6.25.1 |
| ipython | 8.15.0 | ipython-genutils | 0.2.0 | ipywidgets | 8.0.4 |
| isodate | 0.6.1 | itsdangerous | 2.0.1 | jax-jumpy | 1.0.0 |
| jedi | 0.18.1 | jeepney | 0.7.1 | Jinja2 | 3.1.2 |
| jmespath | 0.10.0 | joblib | 1.2.0 | joblibspark | 0.5.1 |
| jsonpatch | 1.33 | jsonpointer | 2.4 | jsonschema | 4.17.3 |
| jupyter-server | 1.23.4 | jupyter_client | 7.4.9 | jupyter_core | 5.3.0 |
| jupyterlab-pygments | 0.1.2 | jupyterlab-widgets | 3.0.5 | keras | 2.15.0 |
| keyring | 23.5.0 | kiwisolver | 1.4.4 | langchain | 0.1.3 |
| langchain-community | 0.0.20 | langchain-core | 0.1.23 | langcodes | 3.3.0 |
| langsmith | 0.0.87 | launchpadlib | 1.10.16 | lazr.restfulclient | 0.14.4 |
| lazr.uri | 1.0.6 | lazy_loader | 0,2 | libclang | 16.0.6 |
| librosa | 0.10.1 | lightgbm | 4.2.0 | llvmlite | 0.40.0 |
| lxml | 4.9.2 | lz4 | 4.3.2 | Mako | 1.2.0 |
| Markdown | 3.4.1 | markdown-it-py | 2.2.0 | MarkupSafe | 2.1.1 |
| marshmallow | 3.21.1 | matplotlib | 3.7.2 | matplotlib-inline | 0.1.6 |
| mdurl | 0.1.0 | mistune | 0.8.4 | ml-dtypes | 0.2.0 |
| mlflow-skinny | 2.10.2 | more-itertools | 8.10.0 | mpmath | 1.3.0 |
| msgpack | 1.0.8 | multidict | 6.0.2 | multimethod | 1.11.2 |
| multiprocess | 0.70.14 | murmurhash | 1.0.10 | mypy-extensions | 0.4.3 |
| nbclassic | 0.5.5 | nbclient | 0.5.13 | nbconvert | 6.5.4 |
| nbformat | 5.7.0 | nest-asyncio | 1.5.6 | networkx | 3.1 |
| ninja | 1.11.1.1 | nltk | 3.8.1 | notebook | 6.5.4 |
| notebook_shim | 0.2.2 | numba | 0.57.1 | numpy | 1.23.5 |
| nvidia-ml-py | 12.535.133 | oauthlib | 3.2.0 | openai | 1.9.0 |
| opencensus==0.7.13 | 0.11.4 | opencensus-context==0.1.2 | 0.1.3 | opt-einsum | 3.3.0 |
| empaquetado | 23,2 | pandas | 1.5.3 | pandocfilters | 1.5.0 |
| paramiko | 2.9.2 | parso | 0.8.3 | pathspec | 0.10.3 |
| patsy | 0.5.3 | petastorm | 0.12.1 | pexpect | 4.8.0 |
| phik | 0.12.4 | pickleshare | 0.7.5 | Pillow | 9.4.0 |
| pip | 23.2.1 | platformdirs | 3.10.0 | plotly | 5.9.0 |
| pmdarima | 2.0.4 | pooch | 1.8.1 | preshed | 3.0.9 |
| prompt-toolkit | 3.0.36 | prophet | 1.1.5 | protobuf | 4.24.1 |
| psutil | 5.9.0 | psycopg2 | 2.9.3 | ptyprocess | 0.7.0 |
| pure-eval | 0.2.2 | py-cpuinfo | 8.0.0 | py-spy | 0.3.14 |
| pyarrow | 14.0.1 | pyarrow-hotfix | 0.6 | pyasn1 | 0.4.8 |
| pyasn1-modules | 0.2.8 | pybind11 | 2.11.1 | pyccolo | 0.0.52 |
| pycparser | 2.21 | pydantic | 1.10.6 | Pygments | 2.15.1 |
| PyGObject | 3.42.1 | PyJWT | 2.3.0 | PyNaCl | 1.5.0 |
| pynvml | 11.5.0 | pyodbc | 4.0.38 | pyparsing | 3.0.9 |
| pyrsistent | 0.18.0 | pytesseract | 0.3.10 | Python-dateutil | 2.8.2 |
| python-editor | 1.0.4 | python-lsp-jsonrpc | 1.1.1 | pytz | 2022.7 |
| PyWavelets | 1.4.1 | PyYAML | 6.0 | pyzmq | 23.2.0 |
| Ray | 2.9.3 | regex | 2022.7.9 | requests | 2.31.0 |
| requests-oauthlib | 1.3.1 | responses | 0.13.3 | rich | 13.7.1 |
| rsa | 4,9 | s3transfer | 0.10.0 | safetensors | 0.3.2 |
| scikit-image | 0.20.0 | scikit-learn | 1.3.0 | scipy | 1.11.1 |
| seaborn | 0.12.2 | SecretStorage | 3.3.1 | Send2Trash | 1.8.0 |
| sentence-transformers | 2.2.2 | sentencepiece | 0.1.99 | setuptools | 68.0.0 |
| shap | 0.44.0 | 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 | 2.4 |
| soxr | 0.3.7 | spacy | 3.7.2 | spacy-legacy | 3.0.12 |
| spacy-loggers | 1.0.5 | spark-tensorflow-distributor | 1.0.0 | SQLAlchemy | 1.4.39 |
| sqlparse | 0.4.2 | srsly | 2.4.8 | ssh-import-id | 5.11 |
| stack-data | 0.2.0 | stanio | 0.3.0 | statsmodels | 0.14.0 |
| sympy | 1.11.1 | tangled-up-in-unicode | 0.2.0 | tenacity | 8.2.2 |
| tensorboard | 2.15.1 | tensorboard-data-server | 0.7.2 | tensorboard-plugin-profile | 2.15.0 |
| tensorboardX | 2.6.2.2 | tensorflow | 2.15.0 | tensorflow-estimator | 2.15.0 |
| tensorflow-io-gcs-filesystem | 0.36.0 | termcolor | 2.4.0 | terminado | 0.17.1 |
| thinc | 8.2.3 | threadpoolctl | 2.2.0 | tifffile | 2021.7.2 |
| tiktoken | 0.5.2 | tinycss2 | 1.2.1 | tokenize-rt | 4.2.1 |
| tokenizers | 0.15.0 | torch | 2.1.2+cu121 | torcheval | 0.0.7 |
| torchvision | 0.16.2+cu121 | tornado | 6.3.2 | tqdm | 4.65.0 |
| traitlets | 5.7.1 | transformers | 4.36.2 | triton | 2.1.0 |
| typeguard | 2.13.3 | typer | 0.9.0 | typing-inspect | 0.9.0 |
| typing_extensions | 4.7.1 | tzdata | 2022.1 | ujson | 5.4.0 |
| unattended-upgrades | 0,1 | urllib3 | 1.26.16 | virtualenv | 20.21.0 |
| visions | 0.7.5 | wadllib | 1.3.6 | wasabi | 1.1.2 |
| wcwidth | 0.2.5 | weasel | 0.3.4 | webencodings | 0.5.1 |
| websocket-client | 0.58.0 | Werkzeug | 2.2.3 | wheel | 0.38.4 |
| widgetsnbextension | 4.0.5 | wordcloud | 1.9.3 | wrapt | 1.14.1 |
| xgboost | 2.0.3 | xxhash | 3.4.1 | yarl | 1.8.1 |
| ydata-profiling | 4.5.1 | zipp | 3.11.0 |
Bibliotecas de R
Las bibliotecas de R son idénticas a las bibliotecas de R de Databricks Runtime 15.1.
Bibliotecas de Java y Scala (clúster de Scala 2.12)
Además de las bibliotecas de Java y Scala de Databricks Runtime 15.1, los siguientes archivos JAR también se incluyen en Databricks Runtime 15.1 ML:
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 | 2.10.2 |
| 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 | 2.10.2 |
| org.scala-lang.modules | scala-java8-compat_2.12 | 0.8.0 |
| org.tensorflow | spark-tensorflow-connector_2.12 | 1.15.0 |