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Databricks Runtime 18.0 para Machine Learning (Beta) proporciona un entorno listo para usar para el aprendizaje automático y la ciencia de datos basado en Databricks Runtime 18.0 (Beta). Databricks Runtime ML contiene muchas bibliotecas de aprendizaje automático populares, como TensorFlow, PyTorch y XGBoost. Databricks Runtime ML también admite el entrenamiento de aprendizaje profundo distribuido mediante TorchDistributor, DeepSpeed y Ray.
Importante
Databricks Runtime 18.0 para Machine Learning está en beta. El contenido de los entornos admitidos puede cambiar durante la versión Beta. Los cambios pueden incluir la lista de paquetes o versiones de paquetes instalados.
Nuevas características y mejoras
Databricks Runtime 18.0 ML se basa en Databricks Runtime 18.0. Para obtener información sobre las novedades de Databricks Runtime 18.0, incluidas apache Spark MLlib y SparkR, consulte las notas de la versión de Databricks Runtime 18.0 (beta).
Algunas de las actualizaciones de la biblioteca incluyen:
- Actualización de CUDA a la versión 12.9
- flash_attn 2.8.3
- keras 3.12.0
- langchain 1.0.3
- mlflow-skinny 3.5.1
- openai 2.7.0
- torch 2.9.0+cu129
- torchvision 0.24.0+cu129
- transformadores 4.57.1
- triton 3.5.0
- xgboost 3.1.1
Otros cambios
Se han realizado los siguientes cambios adicionales a partir de Databricks Runtime 18.0 ML:
- AutoML se ha quitado.
- TensorFlow ya no tiene soporte de primer nivel.
Entorno del sistema
El entorno del sistema en Databricks Runtime 18.0 ML difiere de Databricks Runtime 18.0 como se indica a continuación.
- En el caso de los clústeres de GPU, Databricks Runtime ML incluye las siguientes bibliotecas de GPU de NVIDIA:
- CUDA 12.9
- cublas 12.9.1.4-1
- cusolver 11.7.5.82
- cupti 12.9.79
- cusparse 12.5.10.65
- cuDNN 9.15.1.9-1
- NCCL 2.27.5
Libraries
En las secciones siguientes se enumeran las bibliotecas incluidas en Databricks Runtime 18.0 ML que difieren de las incluidas en Databricks Runtime 18.0.
Bibliotecas de nivel superior
Databricks Runtime 18.0 ML incluye las siguientes bibliotecas de nivel superior:
Bibliotecas de Python
Databricks Runtime 18.0 ML usa virtualenv para la administración de paquetes de Python e incluye muchos paquetes populares de ML.
Para reproducir el entorno de Databricks Runtime ML de Python en su entorno virtual local de Python, deberá descargar requirements-cpu-18.0.txt para clústeres de CPU o requirements-gpu-18.0.txt para clústeres de GPU. A continuación, ejecute pip install -r requirements-<cpu|gpu>-18.0.txt. Este comando instala todas las bibliotecas de código abierto que usa Databricks Runtime ML, pero no instala bibliotecas desarrolladas por Databricks.
Bibliotecas de Python en clústeres de CPU
| Biblioteca | Versión | Biblioteca | Versión | Biblioteca | Versión |
|---|---|---|---|---|---|
| absl-py | 2.3.1 | acelerar | 1.11.0 | aiohappyeyeballs | 2.4.4 |
| aiohttp | 3.11.10 | aiohttp-cors | 0.8.1 | aiosignal | 1.2.0 |
| alambique | 1.17.1 | documento anotado | 0.0.4 | tipos anotados | 0.7.0 |
| anyio | 4.7.0 | argon2-cffi | 21.3.0 | argon2-cffi-bindings | 21.2.0 |
| arro3-core | 0.6.5 | flecha | 1.3.0 | "asttokens" | 3.0.0 |
| astunparse | 1.6.3 | async-lru | 2.0.4 | atributos | 24.3.0 |
| Audioread | 3.1.0 | comando automático | 2.2.2 | azure-common | 1.1.28 |
| azure-core | 1.36.0 | azure-cosmos | 4.3.1 | azure-identity | 1.20.0 |
| azure-mgmt-core | 1.6.0 | azure-mgmt-web | 8.0.0 | azure-storage-blob | 12.27.1 |
| Servicio de Azure Storage File Data Lake | 12.22.0 | babel | 2.16.0 | backports.tarfile | 1.2.0 |
| bcrypt | 4.3.0 | beautifulsoup4 | 4.12.3 | negro | 24.10.0 |
| blanquear | 6.2.0 | intermitente | 1.7.0 | felicidad | 0.7.11 |
| boto3 | 1.40.45 | botocore | 1.40.45 | brotli | 1.2.0 |
| cachetools | 5.5.1 | catálogo | 2.0.10 | certifi | 2025.4.26 |
| cffi | 1.17.1 | chardet | 4.0.0 | charset-normalizer | 3.3.2 |
| circuitbreaker | 2.1.3 | Haz clic | 8.1.8 | cloudpathlib | 0.23.0 |
| cloudpickle | 3.0.0 | cmdstanpy | 1.3.0 | colorido | 0.5.8 |
| colorlog | 6.10.1 | Comunicación | 0.2.1 | confitería | 0.1.5 |
| contourpy | 1.3.1 | cramjam | 2.11.0 | criptografía | 44.0.1 |
| ciclista | 0.11.0 | cymem | 2.0.12 | Cython | 3.1.5 |
| dacita | 1.9.2 | databricks-agents | 1.4.0 | databricks-connect | 17.3.1 |
| databricks-feature-engineering | 0.13.0.1 | SDK de Databricks | 0.67.0 | dataclasses-json | 0.6.7 |
| Conjuntos de datos | 4.3.0 | dbl-tempo | 0.1.26 | dbus-python | 1.3.2 |
| debugpy | 1.8.11 | decorator | 5.1.1 | velocidad profunda | 0.18.1 |
| defusedxml | 0.7.1 | deltalake | 1.1.4 | Deprecated | 1.2.18 |
| dill | 0.3.8 | distlib | 0.3.9 | dm-tree | 0.1.9 |
| Conversión de docstring a markdown | 0.11 | einops | 0.8.1 | evaluar | 0.4.6 |
| executing | 1.2.0 | visión general de las facetas | 1.1.1 | Farama-Notifications | 0.0.4 |
| fastapi | 0.121.2 | fastjsonschema | 2.21.1 | bloqueo de archivos | 3.17.0 |
| filetype | 1.2.0 | Flask | 2.2.5 | flatbuffers | 25.9.23 |
| fonttools | 4.55.3 | Fqdn | 1.5.1 | frozenlist | 1.5.0 |
| fsspec | 2023.5.0 | gast | 0.6.0 | gitdb | 4.0.11 |
| GitPython | 3.1.43 | google-api-core | 2.28.1 | google-auth | 2.43.0 |
| google-cloud-core | 2.5.0 | Google Cloud Storage (almacenamiento en la nube de Google) | 3.2.0 | google-crc32c | 1.7.1 |
| google-pasta | 0.2.0 | google-resumable-media (medios reanudables de Google) | 2.7.2 | googleapis-common-protos | 1.65.0 |
| graphql-core | 3.2.4 | greenlet | 3.1.1 | grpcio | 1.67.0 |
| grpcio-status | 1.67.0 | gimnasio | 0.28.1 | h11 | 0.16.0 |
| h5py | 3.12.1 | hf-xet | 1.2.0 | hjson | 3.1.0 |
| vacaciones | 0.54 | httpcore | 1.0.9 | httplib2 | 0.20.4 |
| httpx | 0.28.1 | huggingface-hub | 0.36.0 | idna | 3.7 |
| Hash de imagen | 4.3.1 | imageio | 2.37.0 | imbalanced-learn | 0.13.0 |
| importlib-metadata | 6.6.0 | importlib_resources | 6.5.2 | inflect | 7.3.1 |
| iniconfig | 1.1.1 | ipyflow-core | 0.0.209 | ipykernel | 6.29.5 |
| ipython | 8.30.0 | ipython-genutils | 0.2.0 | ipywidgets | 7.8.1 |
| isodate | 0.7.2 | isoduration | 20.11.0 | Es peligroso | 2.2.0 |
| jaraco.collections | 5.1.0 | jaraco.context | 5.3.0 | jaraco.functools | 4.0.1 |
| jaraco.text | 3.12.1 | jax-jumpy | 1.0.0 | Jedi | 0.19.2 |
| Jinja2 | 3.1.6 | jiter | 0.12.0 | jmespath | 1.0.1 |
| joblib | 1.4.2 | joblibspark | 0.6.0 | json5 | 0.9.25 |
| jsonpatch | 1.33 | jsonpointer | 3.0.0 | jsonschema | 4.23.0 |
| jsonschema-specifications | 2023.7.1 | jupyter | 1.1.1 | jupyter-console | 6.6.3 |
| jupyter_events | 0.12.0 | jupyter-lsp | 2.2.5 | jupyter_client | 8.6.3 |
| jupyter_core | 5.7.2 | jupyter_server | 2.15.0 | jupyter_server_terminals | 0.5.3 |
| jupyterlab | 4.3.4 | jupyterlab_pygments | 0.3.0 | jupyterlab_server (servidor de JupyterLab) | 2.27.3 |
| jupyterlab_widgets | 1.1.11 | keras | 3.12.0 | kiwisolver | 1.4.8 |
| langchain | 1.0.3 | langchain-core | 1.0.4 | langchain-openai | 1.0.2 |
| códigos de idioma | 3.5.0 | langgraph | 1.0.3 | langgraph-checkpoint | 3.0.1 |
| langgraph-prebuilt | 1.0.4 | langgraph-sdk | 0.2.9 | langsmith | 0.4.41 |
| datos_de_idioma | 1.3.0 | launchpadlib | 1.11.0 | lazr.restfulclient | 0.14.6 |
| lazr.uri | 1.0.6 | lazy_loader | 0.4 | libclang | 15.0.6.1 |
| librosa | 0.11.0 | lightgbm | 4.6.0 | linkify-it-py | 2.0.0 |
| llvmlite | 0.44.0 | lz4 | 4.3.2 | Mako | 1.3.10 |
| marisa-trie | 1.2.0 | Markdown | 3.8 | markdown-it-py | 2.2.0 |
| MarkupSafe | 3.0.2 | malvavisco | 3.26.1 | matplotlib | 3.10.0 |
| matplotlib-inline | 0.1.7 | Mccabe | 0.7.0 | mdit-py-plugins | 0.3.0 |
| mdurl | 0.1.0 | memray | 1.19.1 | minify_html | 0.18.1 |
| mistune | 3.1.2 | ml_dtypes | 0.5.3 | mlflow-skinny | 3.5.1 |
| mmh3 | 5.2.0 | more-iterators | 10.3.0 | mosaicml-streaming | 0.13.0 |
| mpmath | 1.3.0 | msal | 1.34.0 | msal-extensions | 1.3.1 |
| msgpack | 1.1.2 | Multidic | 6.1.0 | multimétodo | 1.12 |
| multiprocess | 0.70.16 | murmurhash | 1.0.14 | mypy-extensions | 1.0.0 |
| namex | 0.1.0 | nbclient | 0.10.2 | nbconvert | 7.16.6 |
| nbformat | 5.10.4 | nest-asyncio | 1.6.0 | networkx | 3.4.2 |
| ninja | 1.13.0 | NLTK | 3.9.1 | nodeenv | 1.9.1 |
| notebook | 7.3.2 | notebook_shim | 0.2.4 | numba | 0.61.0 |
| numpy | 2.1.3 | nvidia-nccl-cu12 | 2.28.7 | oauthlib | 3.2.0 |
| oci | 2.163.1 | openai | 2.7.0 | opencensus | 0.11.4 |
| opencensus-context==0.1.2 | 0.1.3 | opentelemetry-api | 1.38.0 | opentelemetry-proto | 1.38.0 |
| opentelemetry-sdk | 1.38.0 | convenciones-semánticas-de-opentelemetry | 0,59b0 | opt_einsum | 3.4.0 |
| optree | 0.17.0 | optuna | 3.6.1 | optuna-integration | 3.6.0 |
| orjson | 3.11.4 | ormsgpack | 1.12.0 | overrides | 7.4.0 |
| embalaje | 24,2 | Pandas | 2.2.3 | pandocfilters | 1.5.0 |
| paramiko | 3.5.1 | parso | 0.8.4 | pathspec | 0.10.3 |
| chivo expiatorio | 1.0.1 | pexpect | 4.8.0 | phik | 0.12.5 |
| almohada | 11.1.0 | pip | 25.0.1 | platformdirs | 4.3.7 |
| plotly | 5.24.1 | pluggy | 1.5.0 | chucho | 1.8.2 |
| preshed | 3.0.11 | prometheus_client | 0.21.1 | prompt-toolkit | 3.0.43 |
| propcache | 0.3.1 | profeta | 1.2.1 | proto-plus | 1.26.1 |
| protobuf | 5.29.4 | psutil | 5.9.0 | psycopg2 | 2.9.11 |
| ptyprocess | 0.7.0 | pure-eval | 0.2.2 | puremagic | 1.30 |
| py-cpuinfo | 9.0.0 | py-spy | 0.4.1 | py4j | 0.10.9.9 |
| pyarrow | 21.0.0 | pyasn1 | 0.4.8 | pyasn1-modules | 0.2.8 |
| pyccolo | 0.0.71 | pycparser | 2.21 | pydantic | 2.10.6 |
| pydantic_core | 2.27.2 | pyflakes | 3.2.0 | Pygments | 2.19.1 |
| PyGObject | 3.48.2 | pyiceberg | 0.10.0 | PyJWT | 2.10.1 |
| PyNaCl | 1.5.0 | pyodbc | 5.2.0 | pyOpenSSL | 25.0.0 |
| pyparsing | 3.2.0 | pyright | 1.1.394 | piroaring | 1.0.3 |
| pytesseract | 0.3.10 | pytest | 8.3.5 | Python-dateutil | 2.9.0.post0 |
| python-dotenv | 1.2.1 | editor de Python | 1.0.4 | python-json-logger | 3.2.1 |
| python-lsp-jsonrpc | 1.1.2 | python-lsp-servidor | 1.12.2 | python-snappy | 0.7.3 |
| configuración de herramienta Python | 1.2.6 | pytz | 2024.1 | PyWavelets | 1.8.0 |
| PyYAML | 6.0.2 | pyzmq | 26.2.0 | ray | 2.37.0 |
| referencing | 0.30.2 | regex | 2024.11.6 | solicitudes | 2.32.3 |
| requests-toolbelt | 1.0.0 | rfc3339-validator | 0.1.4 | rfc3986-validator | 0.1.1 |
| rico | 13.9.4 | cuerda | 1.13.0 | rpds-py | 0.22.3 |
| rsa | 4.9.1 | s3transfer | 0.14.0 | safetensors | 0.6.2 |
| scikit-image | 0.25.0 | scikit-learn | 1.6.1 | scipy | 1.15.3 |
| biblioteca de visualización de datos de Python llamada seaborn | 0.13.2 | Send2Trash | 1.8.2 | transformadores de frases | 5.1.2 |
| frase | 0.2.1 | setuptools | 78.1.1 | shap | 0.49.1 |
| Shellingham | 1.5.4 | six | 1.17.0 | sklearn-compat | 0.1.3 |
| rebanador | 0.0.8 | smart_open | 7.5.0 | smmap | 5.0.0 |
| sniffio | 1.3.0 | sortedcontainers | 2.4.0 | archivo de sonido | 0.13.1 |
| soupsieve | 2,5 | soxr | 1.0.0 | spacy | 3.7.5 |
| spacy-legacy | 3.0.12 | espacy-loggers | 1.0.5 | SQLAlchemy | 2.0.39 |
| sqlparse | 0.5.3 | srsly | 2.5.1 | ssh-import-id | 5.11 |
| stack-data | 0.6.3 | estaño | 0.5.1 | Starlette | 0.49.3 |
| statsmodels (paquete de Python para análisis estadístico) | 0.14.4 | strictyaml | 1.7.3 | Sintonía | 1.13.3 |
| tenacidad | 9.0.0 | tensorboard | 2.20.0 | servidor-de-datos-de-tensorboard | 0.7.2 |
| tensorboardX | 2.6.4 | TensorFlow | 2.20.0 | termcolor | 3.2.0 |
| terminado | 0.17.1 | textual | 4.0.0 | tf_keras | 2.20.1 |
| thinc | 8.2.4 | threadpoolctl | 3.5.0 | tifffile | 2025.2.18 |
| tiktoken | 0.9.0 | tinycss2 | 1.4.0 | tokenize_rt | 6.1.0 |
| tokenizers | 0.22.1 | tomli | 2.0.1 | antorcha | 2.9.0+cpu |
| torcheval | 0.0.7 | antorcha | 0.24.0+cpu | tornado | 6.5.1 |
| tqdm | 4.67.1 | traitlets | 5.14.3 | Transformadores | 4.57.1 |
| typeguard | 4.4.2 | typer | 0.20.0 | typer-slim | 0.20.0 |
| types-python-dateutil | 2.9.0.20251108 | inspección de escritura | 0.9.0 | typing_extensions | 4.12.2 |
| tzdata | 2024.1 | uc-micro-py | 1.0.1 | ujson | 5.10.0 |
| unattended-upgrades | 0,1 | uri-template | 1.3.0 | urllib3 | 2.3.0 |
| uvicorn | 0.38.0 | virtualenv | 20.29.3 | Visiones | 0.8.1 |
| wadllib | 1.3.6 | wasabi | 1.1.3 | wcwidth | 0.2.5 |
| weasel | 0.4.3 | webcolores | 25.10.0 | codificaciones web | 0.5.1 |
| cliente de websocket | 1.8.0 | Werkzeug | 3.1.3 | ¿Qué es el parche? | 1.0.2 |
| rueda | 0.45.1 | cuando quiera | 0.7.3 | widgetsnbextension | 3.6.6 |
| nube de palabras | 1.9.4 | envuelto | 1.17.0 | xgboost | 3.1.1 |
| xgboost-ray | 0.1.19 | xxhash | 3.5.0 | yapf | 0.40.2 |
| yarl | 1.18.0 | ydata-profiling | 4.17.0 | zipp | 3.21.0 |
| zstandard | 0.23.0 | zstd | 1.5.5.1 |
Bibliotecas de Python en clústeres de GPU
Nota:
PyTorch usa las dependencias de PYPI de CUDA para proporcionar compatibilidad con CUDA en lugar de las versiones de biblioteca de CUDA integradas en Databricks Runtime 18.0 ML.
| Biblioteca | Versión | Biblioteca | Versión | Biblioteca | Versión |
|---|---|---|---|---|---|
| absl-py | 2.3.1 | acelerar | 1.11.0 | aiohappyeyeballs | 2.4.4 |
| aiohttp | 3.11.10 | aiohttp-cors | 0.8.1 | aiosignal | 1.2.0 |
| documento anotado | 0.0.4 | tipos anotados | 0.7.0 | anyio | 4.7.0 |
| argon2-cffi | 21.3.0 | argon2-cffi-bindings | 21.2.0 | arro3-core | 0.6.5 |
| flecha | 1.3.0 | "asttokens" | 3.0.0 | astunparse | 1.6.3 |
| async-lru | 2.0.4 | atributos | 24.3.0 | Audioread | 3.1.0 |
| comando automático | 2.2.2 | azure-common | 1.1.28 | azure-core | 1.36.0 |
| azure-cosmos | 4.3.1 | azure-identity | 1.20.0 | azure-mgmt-core | 1.6.0 |
| azure-mgmt-web | 8.0.0 | azure-storage-blob | 12.27.1 | Servicio de Azure Storage File Data Lake | 12.22.0 |
| babel | 2.16.0 | backports.tarfile | 1.2.0 | bcrypt | 4.3.0 |
| beautifulsoup4 | 4.12.3 | negro | 24.10.0 | blanquear | 6.2.0 |
| intermitente | 1.7.0 | felicidad | 0.7.11 | boto3 | 1.40.45 |
| botocore | 1.40.45 | brotli | 1.2.0 | cachetools | 5.5.1 |
| catálogo | 2.0.10 | certifi | 2025.4.26 | cffi | 1.17.1 |
| chardet | 4.0.0 | charset-normalizer | 3.3.2 | circuitbreaker | 2.1.3 |
| Haz clic | 8.1.8 | cloudpathlib | 0.23.0 | cloudpickle | 3.0.0 |
| cmdstanpy | 1.3.0 | colorido | 0.5.8 | colorlog | 6.10.1 |
| Comunicación | 0.2.1 | confitería | 0.1.5 | contourpy | 1.3.1 |
| cramjam | 2.11.0 | criptografía | 44.0.1 | ciclista | 0.11.0 |
| cymem | 2.0.12 | Cython | 3.1.5 | dacita | 1.9.2 |
| databricks-agents | 1.4.0 | databricks-connect | 17.3.1 | databricks-feature-engineering | 0.13.0.1 |
| SDK de Databricks | 0.67.0 | dataclasses-json | 0.6.7 | Conjuntos de datos | 4.3.0 |
| dbl-tempo | 0.1.26 | dbus-python | 1.3.2 | debugpy | 1.8.11 |
| decorator | 5.1.1 | velocidad profunda | 0.18.1 | defusedxml | 0.7.1 |
| deltalake | 1.1.4 | Deprecated | 1.2.18 | dill | 0.3.8 |
| distlib | 0.3.9 | dm-tree | 0.1.9 | Conversión de docstring a markdown | 0.11 |
| einops | 0.8.1 | evaluar | 0.4.6 | executing | 1.2.0 |
| visión general de las facetas | 1.1.1 | Farama-Notifications | 0.0.4 | fastapi | 0.121.2 |
| fastjsonschema | 2.21.1 | bloqueo de archivos | 3.17.0 | filetype | 1.2.0 |
| flash_attn | 2.8.3 | Flask | 2.2.5 | flatbuffers | 25.9.23 |
| fonttools | 4.55.3 | Fqdn | 1.5.1 | frozenlist | 1.5.0 |
| fsspec | 2023.5.0 | gast | 0.6.0 | gitdb | 4.0.11 |
| GitPython | 3.1.43 | google-api-core | 2.28.1 | google-auth | 2.43.0 |
| google-cloud-core | 2.5.0 | Google Cloud Storage (almacenamiento en la nube de Google) | 3.2.0 | google-crc32c | 1.7.1 |
| google-pasta | 0.2.0 | google-resumable-media (medios reanudables de Google) | 2.7.2 | googleapis-common-protos | 1.65.0 |
| graphql-core | 3.2.4 | greenlet | 3.1.1 | grpcio | 1.67.0 |
| grpcio-status | 1.67.0 | gimnasio | 0.28.1 | h11 | 0.16.0 |
| h5py | 3.12.1 | hf-xet | 1.2.0 | hjson | 3.1.0 |
| vacaciones | 0.54 | httpcore | 1.0.9 | httplib2 | 0.20.4 |
| httpx | 0.28.1 | huggingface-hub | 0.36.0 | idna | 3.7 |
| Hash de imagen | 4.3.1 | imageio | 2.37.0 | imbalanced-learn | 0.13.0 |
| importlib-metadata | 6.6.0 | importlib_resources | 6.5.2 | inflect | 7.3.1 |
| iniconfig | 1.1.1 | ipyflow-core | 0.0.209 | ipykernel | 6.29.5 |
| ipython | 8.30.0 | ipython-genutils | 0.2.0 | ipywidgets | 7.8.1 |
| isodate | 0.7.2 | isoduration | 20.11.0 | Es peligroso | 2.2.0 |
| jaraco.collections | 5.1.0 | jaraco.context | 5.3.0 | jaraco.functools | 4.0.1 |
| jaraco.text | 3.12.1 | jax-jumpy | 1.0.0 | Jedi | 0.19.2 |
| Jinja2 | 3.1.6 | jiter | 0.12.0 | jmespath | 1.0.1 |
| joblib | 1.4.2 | joblibspark | 0.6.0 | json5 | 0.9.25 |
| jsonpatch | 1.33 | jsonpointer | 3.0.0 | jsonschema | 4.23.0 |
| jsonschema-specifications | 2023.7.1 | jupyter | 1.1.1 | jupyter-console | 6.6.3 |
| jupyter_events | 0.12.0 | jupyter-lsp | 2.2.5 | jupyter_client | 8.6.3 |
| jupyter_core | 5.7.2 | jupyter_server | 2.15.0 | jupyter_server_terminals | 0.5.3 |
| jupyterlab | 4.3.4 | jupyterlab_pygments | 0.3.0 | jupyterlab_server (servidor de JupyterLab) | 2.27.3 |
| jupyterlab_widgets | 1.1.11 | keras | 3.12.0 | kiwisolver | 1.4.8 |
| langchain | 1.0.3 | langchain-core | 1.0.4 | langchain-openai | 1.0.2 |
| códigos de idioma | 3.5.0 | langgraph | 1.0.3 | langgraph-checkpoint | 3.0.1 |
| langgraph-prebuilt | 1.0.4 | langgraph-sdk | 0.2.9 | langsmith | 0.4.41 |
| datos_de_idioma | 1.3.0 | launchpadlib | 1.11.0 | lazr.restfulclient | 0.14.6 |
| lazr.uri | 1.0.6 | lazy_loader | 0.4 | libclang | 15.0.6.1 |
| librosa | 0.11.0 | lightgbm | 4.6.0 | linkify-it-py | 2.0.0 |
| llvmlite | 0.44.0 | lz4 | 4.3.2 | Mako | 1.3.10 |
| marisa-trie | 1.2.0 | Markdown | 3.8 | markdown-it-py | 2.2.0 |
| MarkupSafe | 3.0.2 | malvavisco | 3.26.1 | matplotlib | 3.10.0 |
| matplotlib-inline | 0.1.7 | Mccabe | 0.7.0 | mdit-py-plugins | 0.3.0 |
| mdurl | 0.1.0 | memray | 1.19.1 | minimizar_html | 0.18.1 |
| mistune | 3.1.2 | ml_dtypes | 0.5.3 | mlflow-skinny | 3.5.1 |
| mmh3 | 5.2.0 | más iteradores | 10.3.0 | mosaicml-streaming | 0.13.0 |
| mpmath | 1.3.0 | msal | 1.34.0 | msal-extensions | 1.3.1 |
| msgpack | 1.1.2 | Multidic | 6.1.0 | multimétodo | 1.12 |
| multiprocess | 0.70.16 | murmurhash | 1.0.14 | mypy-extensions | 1.0.0 |
| namex | 0.1.0 | nbclient | 0.10.2 | nbconvert | 7.16.6 |
| nbformat | 5.10.4 | nest-asyncio | 1.6.0 | networkx | 3.4.2 |
| ninja | 1.13.0 | NLTK | 3.9.1 | nodeenv | 1.9.1 |
| notebook | 7.3.2 | notebook_shim | 0.2.4 | numba | 0.61.0 |
| numpy | 2.1.3 | nvidia-cublas-cu12 | 12.9.1.4 | nvidia-cuda-cupti-cu12 | 12.9.79 |
| nvidia-cuda-nvrtc-cu12 | 12.9.86 | nvidia-cuda-runtime-cu12 | 12.9.79 | nvidia-cudnn-cu12 | 9.10.2.21 |
| nvidia-cufft-cu12 | 11.4.1.4 | nvidia-cufile-cu12 | 1.14.1.1 | nvidia-curand-cu12 | 10.3.10.19 |
| nvidia-cusolver-cu12 | 11.7.5.82 | nvidia-cusparse-cu12 | 12.5.10.65 | nvidia-cusparselt-cu12 | 0.7.1 |
| nvidia-ml-py | 13.580.82 | nvidia-nccl-cu12 | 2.27.5 | nvidia-nvjitlink-cu12 | 12.9.86 |
| nvidia-nvshmem-cu12 | 3.3.20 | nvidia-nvtx-cu12 | 12.9.79 | oauthlib | 3.2.0 |
| oci | 2.163.1 | openai | 2.7.0 | opencensus | 0.11.4 |
| opencensus-context==0.1.2 | 0.1.3 | opentelemetry-api | 1.38.0 | opentelemetry-proto | 1.38.0 |
| opentelemetry-sdk | 1.38.0 | convenciones-semánticas-de-opentelemetry | 0,59b0 | opt_einsum | 3.4.0 |
| optree | 0.17.0 | optuna | 3.6.1 | optuna-integration | 3.6.0 |
| orjson | 3.11.4 | ormsgpack | 1.12.0 | overrides | 7.4.0 |
| embalaje | 24,2 | Pandas | 2.2.3 | pandocfilters | 1.5.0 |
| paramiko | 3.5.1 | parso | 0.8.4 | pathspec | 0.10.3 |
| chivo expiatorio | 1.0.1 | pexpect | 4.8.0 | phik | 0.12.5 |
| almohada | 11.1.0 | pip | 25.0.1 | platformdirs | 4.3.7 |
| plotly | 5.24.1 | pluggy | 1.5.0 | chucho | 1.8.2 |
| preshed | 3.0.11 | prometheus_client | 0.21.1 | prompt-toolkit | 3.0.43 |
| propcache | 0.3.1 | profeta | 1.2.1 | proto-plus | 1.26.1 |
| protobuf | 5.29.4 | psutil | 5.9.0 | psycopg2 | 2.9.11 |
| ptyprocess | 0.7.0 | pure-eval | 0.2.2 | puremagic | 1.30 |
| py-cpuinfo | 9.0.0 | py-spy | 0.4.1 | py4j | 0.10.9.9 |
| pyarrow | 21.0.0 | pyasn1 | 0.4.8 | pyasn1-modules | 0.2.8 |
| pyccolo | 0.0.71 | pycparser | 2.21 | pydantic | 2.10.6 |
| pydantic_core | 2.27.2 | pyflakes | 3.2.0 | Pygments | 2.19.1 |
| PyGObject | 3.48.2 | pyiceberg | 0.10.0 | PyJWT | 2.10.1 |
| PyNaCl | 1.5.0 | pyodbc | 5.2.0 | pyOpenSSL | 25.0.0 |
| pyparsing | 3.2.0 | pyright | 1.1.394 | piroaring | 1.0.3 |
| pytesseract | 0.3.10 | pytest | 8.3.5 | Python-dateutil | 2.9.0.post0 |
| python-dotenv | 1.2.1 | editor de Python | 1.0.4 | python-json-logger | 3.2.1 |
| python-lsp-jsonrpc | 1.1.2 | python-lsp-servidor | 1.12.2 | python-snappy | 0.7.3 |
| configuración de herramienta Python | 1.2.6 | pytz | 2024.1 | PyWavelets | 1.8.0 |
| PyYAML | 6.0.2 | pyzmq | 26.2.0 | ray | 2.37.0 |
| referencing | 0.30.2 | regex | 2024.11.6 | solicitudes | 2.32.3 |
| requests-toolbelt | 1.0.0 | rfc3339-validator | 0.1.4 | rfc3986-validator | 0.1.1 |
| rico | 13.9.4 | cuerda | 1.13.0 | rpds-py | 0.22.3 |
| rsa | 4.9.1 | s3transfer | 0.14.0 | safetensors | 0.6.2 |
| scikit-image | 0.25.0 | scikit-learn | 1.6.1 | scipy | 1.15.3 |
| biblioteca de visualización de datos de Python llamada seaborn | 0.13.2 | Send2Trash | 1.8.2 | transformadores de frases | 5.1.2 |
| frase | 0.2.1 | setuptools | 78.1.1 | shap | 0.49.1 |
| Shellingham | 1.5.4 | six | 1.17.0 | sklearn-compat | 0.1.3 |
| rebanador | 0.0.8 | smart_open | 7.5.0 | smmap | 5.0.0 |
| sniffio | 1.3.0 | sortedcontainers | 2.4.0 | archivo de sonido | 0.13.1 |
| soupsieve | 2,5 | soxr | 1.0.0 | spacy | 3.7.5 |
| spacy-legacy | 3.0.12 | espacy-loggers | 1.0.5 | SQLAlchemy | 2.0.39 |
| sqlparse | 0.5.3 | srsly | 2.5.1 | ssh-import-id | 5.11 |
| stack-data | 0.6.3 | estaño | 0.5.1 | Starlette | 0.49.3 |
| statsmodels (paquete de Python para análisis estadístico) | 0.14.4 | strictyaml | 1.7.3 | Sintonía | 1.13.3 |
| tenacidad | 9.0.0 | tensorboard | 2.20.0 | servidor-de-datos-de-tensorboard | 0.7.2 |
| tensorboardX | 2.6.4 | TensorFlow | 2.20.0 | termcolor | 3.2.0 |
| terminado | 0.17.1 | textual | 4.0.0 | tf_keras | 2.20.1 |
| thinc | 8.2.4 | threadpoolctl | 3.5.0 | tifffile | 2025.2.18 |
| tiktoken | 0.9.0 | tinycss2 | 1.4.0 | tokenize_rt | 6.1.0 |
| tokenizers | 0.22.1 | tomli | 2.0.1 | antorcha | 2.9.0+cu129 |
| torcheval | 0.0.7 | antorcha | 0.24.0+cu129 | tornado | 6.5.1 |
| tqdm | 4.67.1 | traitlets | 5.14.3 | Transformadores | 4.57.1 |
| Tritón | 3.5.0 | typeguard | 4.4.2 | typer | 0.20.0 |
| typer-slim | 0.20.0 | types-python-dateutil | 2.9.0.20251108 | inspección de escritura | 0.9.0 |
| typing_extensions | 4.12.2 | tzdata | 2024.1 | uc-micro-py | 1.0.1 |
| ujson | 5.10.0 | unattended-upgrades | 0,1 | uri-template | 1.3.0 |
| urllib3 | 2.3.0 | uvicorn | 0.38.0 | virtualenv | 20.29.3 |
| Visiones | 0.8.1 | wadllib | 1.3.6 | wasabi | 1.1.3 |
| wcwidth | 0.2.5 | weasel | 0.4.3 | webcolores | 25.10.0 |
| codificaciones web | 0.5.1 | cliente de websocket | 1.8.0 | Werkzeug | 3.1.3 |
| ¿Qué es el parche? | 1.0.2 | rueda | 0.45.1 | cuando quiera | 0.7.3 |
| widgetsnbextension | 3.6.6 | nube de palabras | 1.9.4 | envuelto | 1.17.0 |
| xgboost | 3.1.1 | xgboost-ray | 0.1.19 | xxhash | 3.5.0 |
| yapf | 0.40.2 | yarl | 1.18.0 | ydata-profiling | 4.17.0 |
| zipp | 3.21.0 | zstandard | 0.23.0 | zstd | 1.5.5.1 |
Bibliotecas de R
Las bibliotecas de R son idénticas a las bibliotecas de R en Databricks Runtime 18.0.
Bibliotecas de Java y Scala (clúster de Scala 2.13)
Además de las bibliotecas de Java y Scala en Databricks Runtime 18.0, Databricks Runtime 18.0 ML contiene los siguientes JAR:
Clústeres de CPU
| Identificador de grupo | Id. de artefacto | Versión |
|---|---|---|
| ml.dmlc | xgboost4j-spark_2.13 | 2.1.3 |
| ml.dmlc | xgboost4j_2.13 | 2.1.3 |
| org.graphframes | graphframes_2.13 | 0.8.4-db1-spark3.5 |
| org.mlflow | mlflow-client | 2.15.1 |
| org.scala-lang.modules | scala-collection-compat_2.13 | 2.12.0 |
| org.tensorflow | spark-tensorflow-connector_2.13 | 1.15.0 |
Clústeres de GPU
| Identificador de grupo | Id. de artefacto | Versión |
|---|---|---|
| ml.dmlc | xgboost4j-spark_2.13 | 2.1.3 |
| ml.dmlc | xgboost4j_2.13 | 2.1.3 |
| org.graphframes | graphframes_2.13 | 0.8.4-db1-spark3.5 |
| org.mlflow | mlflow-client | 2.15.1 |
| org.scala-lang.modules | scala-collection-compat_2.13 | 2.12.0 |
| org.tensorflow | spark-tensorflow-connector_2.13 | 1.15.0 |
Versiones no compatibles
Sugerencia
Para ver las notas de las versiones de Databricks Runtime que han llegado al fin de soporte (EoS), consulte las Notas de lanzamiento de fin de soporte de Databricks Runtime. Las versiones de EoS Databricks Runtime se han retirado y es posible que no se actualicen.