Databricks Runtime 16.0 para Machine Learning (beta)
Importante
Databricks Runtime 16.0 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 los paquetes instalados.
Databricks Runtime 16.0 para Machine Learning proporciona un entorno listo para usar para el aprendizaje automático y la ciencia de datos basado en Databricks Runtime 16.0 (beta). 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 TorchDistributor, DeepSpeed y Ray.
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 16.0 ML se basa en Databricks Runtime 16.0. Para obtener información sobre las novedades de Databricks Runtime 16.0, incluidas apache Spark MLlib y SparkR, consulte las notas de la versión de Databricks Runtime 16.0 (beta).
Nuevos paquetes de Python
Los siguientes paquetes de Python se han agregado a Databricks Runtime ML:
- composer 0.24.1
- optuna 3.6.1
Ponderaciones de muestra de AutoML de mosaico para la previsión
AutoML ahora admite pesos de muestra para la previsión, lo que le permite ajustar la importancia de cada serie temporal para entrenar modelos de previsión de varias series temporales. Para más información, consulte los parámetros de previsión de la API de Python de AutoML.
Uso de una vista en el catálogo de Unity como tabla de características
Ahora puede usar una vista en el catálogo de Unity como tabla de características. Consulte Uso de una vista existente en el catálogo de Unity como tabla de características.
Otros cambios
Horovod, HorovodRunner, Petastorm, spark-tensorflow-distributor eliminado
Los siguientes paquetes incluidos en versiones anteriores de Databricks Runtime ML no se incluyen en Databricks Runtime 16.0 ML:
- Horovod
- HorovodRunner
- Petastorm
spark-tensorflow-distributor
Databricks recomienda los siguientes reemplazos:
- Para el aprendizaje profundo distribuido, Databricks recomienda usar TorchDistributor para el entrenamiento distribuido con PyTorch o la API para el
tf.distribute.Strategyentrenamiento distribuido con TensorFlow. - Para cargar grandes conjuntos de datos desde el almacenamiento en la nube, Databricks recomienda usar Mosaic Streaming.
- Para el entrenamiento distribuido para un modelo tensorFlow o Keras, Databricks recomienda usar Ray. Consulte Ray en Databricks y la documentación de Ray.
Entorno del sistema
El entorno del sistema en Databricks Runtime 16.0 ML difiere de Databricks Runtime 16.0 de la siguiente manera:
- En los clústeres de GPU, Databricks Runtime ML incluye las siguientes bibliotecas de GPU de NVIDIA:
- CUDA 12.6
- cublas 12.6.0.22-1
- cusolver 11.6.4.38-1
- cupti 12.6.37-1
- cusparse 12.5.2.23-1
- cuDNN 9.3.0.75-1
- NCCL 2.22.3
- TensorRT 10.2.0.19-1
Bibliotecas
En las secciones siguientes se enumeran las bibliotecas incluidas en Databricks Runtime 16.0 ML que difieren de las incluidas en Databricks Runtime 16.0.
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 16.0 ML incluye las siguientes bibliotecas de nivel superior:
- datasets
- GraphFrames
- MLflow
- PyTorch
- spark-tensorflow-connector
- Scikit-learn
- streaming
- TensorFlow
- TensorBoard
- transformers
Bibliotecas de Python
Databricks Runtime 16.0 ML usa virtualenv para la administración de paquetes de Python e incluye muchos paquetes populares de ML.
Además de los paquetes especificados en las secciones siguientes, Databricks Runtime 16.0 ML también incluye los siguientes paquetes:
- hyperopt 0.2.7+db5
- automl 1.29.0
Para reproducir el entorno de Python de Databricks Runtime ML en el entorno virtual local de Python, descargue el archivo requirements-16.0.txt y ejecute pip install -r requirements-16.0.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-engineering 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 | 0.33.0 | aiohttp | 3.9.5 |
| aiohttp-cors | 0.7.0 | aiosignal | 1.2.0 | alembic | 1.13.3 |
| tipos anotados | 0.7.0 | anyio | 4.2.0 | argcomplete | 3.5.0 |
| argon2-cffi | 21.3.0 | argon2-cffi-bindings | 21.2.0 | arrow | 1.2.3 |
| astor | 0.8.1 | asttokens | 2.0.5 | astunparse | 1.6.3 |
| async-lru | 2.0.4 | attrs | 23.1.0 | audioread | 3.0.1 |
| autocomando | 2.2.2 | azure-core | 1.31.0 | azure-cosmos | 4.3.1 |
| azure-identity | 1.18.0 | azure-storage-blob | 12.23.1 | azure-storage-file-datalake | 12.17.0 |
| Babel | 2.11.0 | backoff | 2.2.1 | backports.tarfile | 1.2.0 |
| bcrypt | 3.2.0 | beautifulsoup4 | 4.12.3 | black | 24.4.2 |
| bleach | 4.1.0 | blinker | 1.7.0 | blis | 0.7.11 |
| boto3 | 1.34.69 | botocore | 1.34.69 | Brotli | 1.0.9 |
| cachetools | 5.3.3 | catalogue | 2.0.10 | category-encoders | 2.6.3 |
| certifi | 2024.6.2 | cffi | 1.16.0 | chardet | 4.0.0 |
| charset-normalizer | 2.0.4 | circuitbreaker | 2.0.0 | click | 8.1.7 |
| cloudpathlib | 0.19.0 | cloudpickle | 2.2.1 | cmdstanpy | 1.2.4 |
| multicolor | 0.5.6 | colorlog | 6.8.2 | comm | 0.2.1 |
| composer | 0.24.1 | confection | 0.1.5 | configparser | 5.2.0 |
| contourpy | 1.2.0 | coolname | 2.2.0 | criptografía | 42.0.5 |
| cycler | 0.11.0 | cymem | 2.0.8 | Cython | 3.0.11 |
| dacite | 1.8.1 | databricks-automl-runtime | 0.2.21 | databricks-feature-engineering | 0.7.0 |
| databricks-sdk | 0.30.0 | conjuntos de datos | 2.20.0 | dbl-tempo | 0.1.26 |
| dbus-python | 1.3.2 | debugpy | 1.6.7 | decorator | 5.1.1 |
| deepspeed | 0.14.4 | defusedxml | 0.7.1 | En desuso | 1.2.14 |
| dill | 0.3.8 | distlib | 0.3.8 | dm-tree | 0.1.8 |
| docstring-to-markdown | 0,11 | entrypoints | 0,4 | evaluate | 0.4.2 |
| ejecutar | 0.8.3 | facets-overview | 1.1.1 | Farama-Notifications | 0.0.4 |
| fastjsonschema | 2.20.0 | fasttext-wheel | 0.9.2 | filelock | 3.13.1 |
| Flask | 2.2.5 | flatbuffers | 24.3.25 | fonttools | 4.51.0 |
| fqdn | 1.5.1 | frozenlist | 1.4.0 | fsspec | 2023.5.0 |
| future | 0.18.3 | gast | 0.4.0 | gitdb | 4.0.11 |
| GitPython | 3.1.37 | google-api-core | 2.20.0 | google-auth | 2.21.0 |
| google-auth-oauthlib | 1.0.0 | google-cloud-core | 2.4.1 | google-cloud-storage | 2.10.0 |
| google-crc32c | 1.6.0 | google-pasta | 0.2.0 | google-resumable-media | 2.7.2 |
| googleapis-common-protos | 1.65.0 | gql | 3.5.0 | graphql-core | 3.2.4 |
| greenlet | 3.0.1 | 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 | 3.11.0 | hjson | 3.1.0 |
| holidays | 0,54 | htmlmin | 0.1.12 | httpcore | 1.0.5 |
| httplib2 | 0.20.4 | httpx | 0.27.2 | huggingface-hub | 0.24.5 |
| idna | 3.7 | ImageHash | 4.3.1 | imageio | 2.33.1 |
| imbalanced-learn | 0.12.3 | importlib-metadata | 6.0.0 | importlib_resources | 6.4.5 |
| declinar | 7.3.1 | ipyflow-core | 0.0.201 | ipykernel | 6.28.0 |
| ipython | 8.25.0 | ipython-genutils | 0.2.0 | ipywidgets | 7.7.2 |
| isodate | 0.6.1 | isoduration | 20.11.0 | itsdangerous | 2.2.0 |
| jaraco.context | 5.3.0 | jaraco.functools | 4.0.1 | jaraco.text | 3.12.1 |
| jax-jumpy | 1.0.0 | jedi | 0.19.1 | Jinja2 | 3.1.4 |
| jiter | 0.5.0 | jmespath | 1.0.1 | joblib | 1.4.2 |
| joblibspark | 0.5.1 | json5 | 0.9.6 | jsonpatch | 1.33 |
| jsonpointer | 3.0.0 | jsonschema | 4.19.2 | jsonschema-specifications | 2023.7.1 |
| jupyter-events | 0.10.0 | jupyter-lsp | 2.2.0 | jupyter_client | 8.6.0 |
| jupyter_core | 5.7.2 | jupyter_server | 2.14.1 | jupyter_server_terminals | 0.4.4 |
| jupyterlab | 4.0.11 | jupyterlab-pygments | 0.1.2 | jupyterlab_server | 2.25.1 |
| keras | 3.5.0 | kiwisolver | 1.4.4 | langchain | 0.2.12 |
| langchain-core | 0.2.41 | langchain-text-splitters | 0.2.4 | langcodes | 3.4.1 |
| langsmith | 0.1.129 | language_data | 1.2.0 | launchpadlib | 1.11.0 |
| lazr.restfulclient | 0.14.6 | lazr.uri | 1.0.6 | lazy_loader | 0,4 |
| libclang | 15.0.6.1 | librosa | 0.10.2 | lightgbm | 4.5.0 |
| utilidades lightning-utilities | 0.11.7 | linkify-it-py | 2.0.0 | llvmlite | 0.42.0 |
| lz4 | 4.3.2 | Mako | 1.2.0 | marisa-trie | 1.2.0 |
| Markdown | 3.4.1 | markdown-it-py | 2.2.0 | MarkupSafe | 2.1.3 |
| matplotlib | 3.8.4 | matplotlib-inline | 0.1.6 | mccabe | 0.7.0 |
| mdit-py-plugins | 0.3.0 | mdurl | 0.1.0 | memray | 1.14.0 |
| mistune | 2.0.4 | ml-dtypes | 0.4.1 | mlflow-skinny | 2.15.1 |
| more-itertools | 10.3.0 | mosaicml-cli | 0.6.41 | mosaicml-streaming | 0.8.0 |
| mpmath | 1.3.0 | msal | 1.31.0 | msal-extensions | 1.2.0 |
| msgpack | 1.1.0 | multidict | 6.0.4 | multimethod | 1.12 |
| multiprocess | 0.70.16 | murmurhash | 1.0.10 | mypy | 1.10.0 |
| mypy-extensions | 1.0.0 | namex | 0.0.8 | nbclient | 0.8.0 |
| nbconvert | 7.10.0 | nbformat | 5.9.2 | nest-asyncio | 1.6.0 |
| networkx | 3.2.1 | ninja | 1.11.1.1 | nltk | 3.8.1 |
| nodeenv | 1.9.1 | notebook | 7.0.8 | notebook_shim | 0.2.3 |
| numba | 0.59.1 | numpy | 1.26.4 | nvidia-ml-py | 12.560.30 |
| oauthlib | 3.2.0 | oci | 2.135.0 | openai | 1.40.2 |
| opencensus==0.7.13 | 0.11.4 | opencensus-context==0.1.2 | 0.1.3 | opentelemetry-api | 1.27.0 |
| opentelemetry-sdk | 1.27.0 | opentelemetry-semantic-conventions | 0.48b0 | opt_einsum | 3.4.0 |
| optree | 0.12.1 | optuna | 3.6.1 | optuna-integration | 3.6.0 |
| orjson | 3.10.7 | invalida | 7.4.0 | empaquetado | 24.1 |
| pandas | 1.5.3 | pandocfilters | 1.5.0 | paramiko | 3.4.0 |
| parso | 0.8.3 | pathspec | 0.10.3 | patsy | 0.5.6 |
| pexpect | 4.8.0 | phik | 0.12.4 | pillow | 10.3.0 |
| pip | 24.2 | platformdirs | 3.10.0 | plotly | 5.22.0 |
| pluggy | 1.0.0 | pmdarima | 2.0.4 | pooch | 1.8.2 |
| portalocker | 2.10.1 | preshed | 3.0.9 | prometheus-client | 0.14.1 |
| prompt-toolkit | 3.0.43 | prophet | 1.1.5 | proto-plus | 1.24.0 |
| protobuf | 4.24.1 | psutil | 5.9.0 | psycopg2 | 2.9.3 |
| ptyprocess | 0.7.0 | pure-eval | 0.2.2 | py-cpuinfo | 9.0.0 |
| py-spy | 0.3.14 | pyarrow | 15.0.2 | pyarrow-hotfix | 0.6 |
| pyasn1 | 0.4.8 | pyasn1-modules | 0.2.8 | pybind11 | 2.13.6 |
| pyccolo | 0.0.65 | pycparser | 2.21 | pydantic | 2.8.2 |
| pydantic_core | 2.20.1 | pyflakes | 3.2.0 | Pygments | 2.15.1 |
| PyGObject | 3.48.2 | PyJWT | 2.7.0 | PyNaCl | 1.5.0 |
| pyodbc | 5.0.1 | pyOpenSSL | 24.0.0 | pyparsing | 3.0.9 |
| pyright | 1.1.294 | pytesseract | 0.3.10 | Python-dateutil | 2.9.0.post0 |
| python-editor | 1.0.4 | python-json-logger | 2.0.7 | python-lsp-jsonrpc | 1.1.2 |
| python-lsp-server | 1.10.0 | python-snappy | 0.6.1 | pytoolconfig | 1.2.6 |
| pytorch-ranger | 0.1.1 | pytz | 2024.1 | PyWavelets | 1.5.0 |
| PyYAML | 6.0.1 | pyzmq | 25.1.2 | questionary | 1.10.0 |
| Ray | 2.35.0 | referencing | 0.30.2 | regex | 2023.10.3 |
| requests | 2.32.2 | requests-oauthlib | 1.3.1 | rfc3339-validator | 0.1.4 |
| rfc3986-validator | 0.1.1 | rich | 13.3.5 | rope | 1.12.0 |
| rpds-py | 0.10.6 | rsa | 4,9 | ruamel.yaml | 0.18.6 |
| ruamel.yaml.clib | 0.2.8 | s3transfer | 0.10.2 | safetensors | 0.4.4 |
| scikit-image | 0.23.2 | scikit-learn | 1.4.2 | scipy | 1.13.1 |
| seaborn | 0.13.2 | Send2Trash | 1.8.2 | sentence-transformers | 3.0.1 |
| sentencepiece | 0.2.0 | setuptools | 74.0.0 | shap | 0.46.0 |
| shellingham | 1.5.4 | simplejson | 3.17.6 | six (seis) | 1.16.0 |
| segmentación | 0.0.8 | smart-open | 5.2.1 | smmap | 5.0.0 |
| sniffio | 1.3.0 | soundfile | 0.12.1 | soupsieve | 2.5 |
| soxr | 0.5.0.post1 | spacy | 3.7.5 | spacy-legacy | 3.0.12 |
| spacy-loggers | 1.0.5 | SQLAlchemy | 2.0.30 | sqlparse | 0.4.2 |
| srsly | 2.4.8 | ssh-import-id | 5.11 | stack-data | 0.2.0 |
| stanio | 0.5.1 | statsmodels | 0.14.2 | sympy | 1.12 |
| tabulate | 0.9.0 | tangled-up-in-unicode | 0.2.0 | tenacity | 8.2.2 |
| tensorboard | 2.17.0 | tensorboard-data-server | 0.7.2 | tensorboard-plugin-profile | 2.17.0 |
| tensorboardX | 2.6.2.2 | tensorflow | 2.17.0 | tensorflow-estimator | 2.15.0 |
| termcolor | 2.4.0 | terminado | 0.17.1 | textual | 0.81.0 |
| tf_keras | 2.17.0 | thinc | 8.2.5 | threadpoolctl | 2.2.0 |
| tifffile | 2023.4.12 | tiktoken | 0.7.0 | tinycss2 | 1.2.1 |
| tokenize-rt | 4.2.1 | tokenizers | 0.19.1 | tomli | 2.0.1 |
| torch | 2.4.0+cpu | optimizador de antorchas | 0.3.0 | torcheval | 0.0.7 |
| torchmetrics | 1.4.0.post0 | torchvision | 0.19.0+cpu | tornado | 6.4.1 |
| tqdm | 4.66.4 | traitlets | 5.14.3 | transformers | 4.44.0 |
| typeguard | 4.3.0 | typer | 0.12.5 | types-protobuf | 3.20.3 |
| types-psutil | 5.9.0 | types-pytz | 2023.3.1.1 | types-PyYAML | 6.0.0 |
| types-requests | 2.31.0.0 | types-setuptools | 68.0.0.0 | types-six | 1.16.0 |
| types-urllib3 | 1.26.25.14 | typing_extensions | 4.11.0 | uc-micro-py | 1.0.1 |
| ujson | 5.10.0 | unattended-upgrades | 0,1 | uri-template | 1.3.0 |
| urllib3 | 1.26.16 | validadores | 0.34.0 | virtualenv | 20.26.2 |
| visions | 0.7.5 | wadllib | 1.3.6 | wasabi | 1.1.3 |
| wcwidth | 0.2.5 | weasel | 0.4.1 | webcolors | 24.8.0 |
| webencodings | 0.5.1 | websocket-client | 1.8.0 | websockets | 11.0.3 |
| Werkzeug | 3.0.3 | whatthepatch | 1.0.2 | wheel | 0.43.0 |
| wordcloud | 1.9.3 | wrapt | 1.14.1 | xgboost | 2.0.3 |
| xgboost-ray | 0.1.19 | xxhash | 3.4.1 | yapf | 0.33.0 |
| yarl | 1.9.3 | ydata-profiling | 4.9.0 | zipp | 3.17.0 |
| zstd | 1.5.5.1 |
Bibliotecas de Python en clústeres de GPU
| Biblioteca | Versión | Biblioteca | Versión | Biblioteca | Versión |
|---|---|---|---|---|---|
| absl-py | 1.0.0 | accelerate | 0.33.0 | aiohttp | 3.9.5 |
| aiohttp-cors | 0.7.0 | aiosignal | 1.2.0 | tipos anotados | 0.7.0 |
| anyio | 4.2.0 | argcomplete | 3.5.0 | argon2-cffi | 21.3.0 |
| argon2-cffi-bindings | 21.2.0 | arrow | 1.2.3 | astor | 0.8.1 |
| asttokens | 2.0.5 | astunparse | 1.6.3 | async-lru | 2.0.4 |
| attrs | 23.1.0 | audioread | 3.0.1 | autocomando | 2.2.2 |
| azure-core | 1.31.0 | azure-cosmos | 4.3.1 | azure-identity | 1.18.0 |
| azure-storage-blob | 12.23.1 | azure-storage-file-datalake | 12.17.0 | Babel | 2.11.0 |
| backoff | 2.2.1 | backports.tarfile | 1.2.0 | bcrypt | 3.2.0 |
| beautifulsoup4 | 4.12.3 | black | 24.4.2 | bleach | 4.1.0 |
| blinker | 1.7.0 | blis | 0.7.11 | boto3 | 1.34.69 |
| botocore | 1.34.69 | Brotli | 1.0.9 | cachetools | 5.3.3 |
| catalogue | 2.0.10 | category-encoders | 2.6.3 | certifi | 2024.6.2 |
| cffi | 1.16.0 | chardet | 4.0.0 | charset-normalizer | 2.0.4 |
| circuitbreaker | 2.0.0 | click | 8.1.7 | cloudpathlib | 0.19.0 |
| cloudpickle | 2.2.1 | cmdstanpy | 1.2.4 | multicolor | 0.5.6 |
| colorlog | 6.8.2 | comm | 0.2.1 | composer | 0.24.1 |
| confection | 0.1.5 | configparser | 5.2.0 | contourpy | 1.2.0 |
| coolname | 2.2.0 | criptografía | 42.0.5 | cycler | 0.11.0 |
| cymem | 2.0.8 | Cython | 3.0.11 | dacite | 1.8.1 |
| databricks-automl-runtime | 0.2.21 | databricks-feature-engineering | 0.7.0 | databricks-sdk | 0.30.0 |
| conjuntos de datos | 2.20.0 | dbl-tempo | 0.1.26 | dbus-python | 1.3.2 |
| debugpy | 1.6.7 | decorator | 5.1.1 | deepspeed | 0.14.4 |
| defusedxml | 0.7.1 | En desuso | 1.2.14 | dill | 0.3.8 |
| distlib | 0.3.8 | dm-tree | 0.1.8 | docstring-to-markdown | 0,11 |
| einops | 0.8.0 | entrypoints | 0,4 | evaluate | 0.4.2 |
| ejecutar | 0.8.3 | facets-overview | 1.1.1 | Farama-Notifications | 0.0.4 |
| fastjsonschema | 2.20.0 | fasttext-wheel | 0.9.2 | filelock | 3.13.1 |
| flash_attn | 2.5.6 | Flask | 2.2.5 | flatbuffers | 24.3.25 |
| fonttools | 4.51.0 | fqdn | 1.5.1 | frozenlist | 1.4.0 |
| fsspec | 2023.5.0 | future | 0.18.3 | gast | 0.4.0 |
| gitdb | 4.0.11 | GitPython | 3.1.37 | google-api-core | 2.20.0 |
| google-auth | 2.21.0 | google-auth-oauthlib | 1.0.0 | google-cloud-core | 2.4.1 |
| google-cloud-storage | 2.10.0 | google-crc32c | 1.6.0 | google-pasta | 0.2.0 |
| google-resumable-media | 2.7.2 | googleapis-common-protos | 1.65.0 | gql | 3.5.0 |
| graphql-core | 3.2.4 | greenlet | 3.0.1 | 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 | 3.11.0 |
| hjson | 3.1.0 | holidays | 0,54 | htmlmin | 0.1.12 |
| httpcore | 1.0.5 | httplib2 | 0.20.4 | httpx | 0.27.2 |
| huggingface-hub | 0.24.5 | idna | 3.7 | ImageHash | 4.3.1 |
| imageio | 2.33.1 | imbalanced-learn | 0.12.3 | importlib-metadata | 6.0.0 |
| importlib_resources | 6.4.5 | declinar | 7.3.1 | ipyflow-core | 0.0.201 |
| ipykernel | 6.28.0 | ipython | 8.25.0 | ipython-genutils | 0.2.0 |
| ipywidgets | 7.7.2 | isodate | 0.6.1 | isoduration | 20.11.0 |
| itsdangerous | 2.2.0 | jaraco.context | 5.3.0 | jaraco.functools | 4.0.1 |
| jaraco.text | 3.12.1 | jax-jumpy | 1.0.0 | jedi | 0.19.1 |
| Jinja2 | 3.1.4 | jiter | 0.5.0 | jmespath | 1.0.1 |
| joblib | 1.4.2 | joblibspark | 0.5.1 | json5 | 0.9.6 |
| jsonpatch | 1.33 | jsonpointer | 3.0.0 | jsonschema | 4.19.2 |
| jsonschema-specifications | 2023.7.1 | jupyter-events | 0.10.0 | jupyter-lsp | 2.2.0 |
| jupyter_client | 8.6.0 | jupyter_core | 5.7.2 | jupyter_server | 2.14.1 |
| jupyter_server_terminals | 0.4.4 | jupyterlab | 4.0.11 | jupyterlab-pygments | 0.1.2 |
| jupyterlab_server | 2.25.1 | keras | 3.5.0 | kiwisolver | 1.4.4 |
| langchain | 0.2.12 | langchain-core | 0.2.41 | langchain-text-splitters | 0.2.4 |
| langcodes | 3.4.1 | langsmith | 0.1.129 | language_data | 1.2.0 |
| launchpadlib | 1.11.0 | lazr.restfulclient | 0.14.6 | lazr.uri | 1.0.6 |
| lazy_loader | 0,4 | libclang | 15.0.6.1 | librosa | 0.10.2 |
| lightgbm | 4.5.0 | utilidades lightning-utilities | 0.11.7 | linkify-it-py | 2.0.0 |
| llvmlite | 0.42.0 | lz4 | 4.3.2 | Mako | 1.2.0 |
| marisa-trie | 1.2.0 | Markdown | 3.4.1 | markdown-it-py | 2.2.0 |
| MarkupSafe | 2.1.3 | matplotlib | 3.8.4 | matplotlib-inline | 0.1.6 |
| mccabe | 0.7.0 | mdit-py-plugins | 0.3.0 | mdurl | 0.1.0 |
| memray | 1.14.0 | mistune | 2.0.4 | ml-dtypes | 0.4.1 |
| mlflow-skinny | 2.15.1 | more-itertools | 10.3.0 | mosaicml-cli | 0.6.41 |
| mosaicml-streaming | 0.8.0 | mpmath | 1.3.0 | msal | 1.31.0 |
| msal-extensions | 1.2.0 | msgpack | 1.1.0 | multidict | 6.0.4 |
| multimethod | 1.12 | multiprocess | 0.70.16 | murmurhash | 1.0.10 |
| mypy | 1.10.0 | mypy-extensions | 1.0.0 | namex | 0.0.8 |
| nbclient | 0.8.0 | nbconvert | 7.10.0 | nbformat | 5.9.2 |
| nest-asyncio | 1.6.0 | networkx | 3.2.1 | ninja | 1.11.1.1 |
| nltk | 3.8.1 | nodeenv | 1.9.1 | notebook | 7.0.8 |
| notebook_shim | 0.2.3 | numba | 0.59.1 | numpy | 1.26.4 |
| nvidia-cublas-cu12 | 12.4.2.65 | nvidia-cuda-cupti-cu12 | 12.4.99 | nvidia-cuda-nvrtc-cu12 | 12.4.99 |
| nvidia-cuda-runtime-cu12 | 12.4.99 | nvidia-cudnn-cu12 | 9.1.0.70 | nvidia-cufft-cu12 | 11.2.0.44 |
| nvidia-curand-cu12 | 10.3.5.119 | nvidia-cusolver-cu12 | 11.6.0.99 | nvidia-cusparse-cu12 | 12.3.0.142 |
| nvidia-ml-py | 12.560.30 | nvidia-nccl-cu12 | 2.20.5 | nvidia-nvjitlink-cu12 | 12.4.99 |
| nvidia-nvtx-cu12 | 12.4.99 | oauthlib | 3.2.0 | oci | 2.135.0 |
| openai | 1.40.2 | opencensus==0.7.13 | 0.11.4 | opencensus-context==0.1.2 | 0.1.3 |
| opentelemetry-api | 1.27.0 | opentelemetry-sdk | 1.27.0 | opentelemetry-semantic-conventions | 0.48b0 |
| opt_einsum | 3.4.0 | optree | 0.12.1 | optuna | 3.6.1 |
| optuna-integration | 3.6.0 | orjson | 3.10.7 | invalida | 7.4.0 |
| empaquetado | 24.1 | pandas | 1.5.3 | pandocfilters | 1.5.0 |
| paramiko | 3.4.0 | parso | 0.8.3 | pathspec | 0.10.3 |
| patsy | 0.5.6 | pexpect | 4.8.0 | phik | 0.12.4 |
| pillow | 10.3.0 | pip | 24.2 | platformdirs | 3.10.0 |
| plotly | 5.22.0 | pluggy | 1.0.0 | pmdarima | 2.0.4 |
| pooch | 1.8.2 | portalocker | 2.10.1 | preshed | 3.0.9 |
| prometheus-client | 0.14.1 | prompt-toolkit | 3.0.43 | prophet | 1.1.5 |
| proto-plus | 1.24.0 | protobuf | 4.24.1 | psutil | 5.9.0 |
| psycopg2 | 2.9.3 | ptyprocess | 0.7.0 | pure-eval | 0.2.2 |
| py-cpuinfo | 9.0.0 | py-spy | 0.3.14 | pyarrow | 15.0.2 |
| pyarrow-hotfix | 0.6 | pyasn1 | 0.4.8 | pyasn1-modules | 0.2.8 |
| pybind11 | 2.13.6 | pyccolo | 0.0.65 | pycparser | 2.21 |
| pydantic | 2.8.2 | pydantic_core | 2.20.1 | pyflakes | 3.2.0 |
| Pygments | 2.15.1 | PyGObject | 3.48.2 | PyJWT | 2.7.0 |
| PyNaCl | 1.5.0 | pyodbc | 5.0.1 | pyOpenSSL | 24.0.0 |
| pyparsing | 3.0.9 | pyright | 1.1.294 | pytesseract | 0.3.10 |
| Python-dateutil | 2.9.0.post0 | python-editor | 1.0.4 | python-json-logger | 2.0.7 |
| python-lsp-jsonrpc | 1.1.2 | python-lsp-server | 1.10.0 | python-snappy | 0.6.1 |
| pytoolconfig | 1.2.6 | pytorch-ranger | 0.1.1 | pytz | 2024.1 |
| PyWavelets | 1.5.0 | PyYAML | 6.0.1 | pyzmq | 25.1.2 |
| questionary | 1.10.0 | Ray | 2.35.0 | referencing | 0.30.2 |
| regex | 2023.10.3 | requests | 2.32.2 | requests-oauthlib | 1.3.1 |
| rfc3339-validator | 0.1.4 | rfc3986-validator | 0.1.1 | rich | 13.3.5 |
| rope | 1.12.0 | rpds-py | 0.10.6 | rsa | 4,9 |
| ruamel.yaml | 0.18.6 | ruamel.yaml.clib | 0.2.8 | s3transfer | 0.10.2 |
| safetensors | 0.4.4 | scikit-image | 0.23.2 | scikit-learn | 1.4.2 |
| scipy | 1.13.1 | seaborn | 0.13.2 | Send2Trash | 1.8.2 |
| sentence-transformers | 3.0.1 | sentencepiece | 0.2.0 | setuptools | 74.0.0 |
| shap | 0.46.0 | shellingham | 1.5.4 | simplejson | 3.17.6 |
| six (seis) | 1.16.0 | segmentación | 0.0.8 | smart-open | 5.2.1 |
| smmap | 5.0.0 | sniffio | 1.3.0 | soundfile | 0.12.1 |
| soupsieve | 2.5 | soxr | 0.5.0.post1 | spacy | 3.7.5 |
| spacy-legacy | 3.0.12 | spacy-loggers | 1.0.5 | SQLAlchemy | 2.0.30 |
| sqlparse | 0.4.2 | srsly | 2.4.8 | ssh-import-id | 5.11 |
| stack-data | 0.2.0 | stanio | 0.5.1 | statsmodels | 0.14.2 |
| sympy | 1.12 | tabulate | 0.9.0 | tangled-up-in-unicode | 0.2.0 |
| tenacity | 8.2.2 | tensorboard | 2.17.0 | tensorboard-data-server | 0.7.2 |
| tensorboard-plugin-profile | 2.17.0 | tensorboardX | 2.6.2.2 | tensorflow | 2.17.0 |
| tensorflow-estimator | 2.15.0 | termcolor | 2.4.0 | terminado | 0.17.1 |
| textual | 0.81.0 | tf_keras | 2.17.0 | thinc | 8.2.5 |
| threadpoolctl | 2.2.0 | tifffile | 2023.4.12 | tiktoken | 0.7.0 |
| tinycss2 | 1.2.1 | tokenize-rt | 4.2.1 | tokenizers | 0.19.1 |
| tomli | 2.0.1 | torch | 2.4.0+cu124 | optimizador de antorchas | 0.3.0 |
| torcheval | 0.0.7 | torchmetrics | 1.4.0.post0 | torchvision | 0.19.0+cu124 |
| tornado | 6.4.1 | tqdm | 4.66.4 | traitlets | 5.14.3 |
| transformers | 4.44.0 | triton | 3.0.0 | typeguard | 4.3.0 |
| typer | 0.12.5 | types-protobuf | 3.20.3 | types-psutil | 5.9.0 |
| types-pytz | 2023.3.1.1 | types-PyYAML | 6.0.0 | types-requests | 2.31.0.0 |
| types-setuptools | 68.0.0.0 | types-six | 1.16.0 | types-urllib3 | 1.26.25.14 |
| typing_extensions | 4.11.0 | uc-micro-py | 1.0.1 | ujson | 5.10.0 |
| unattended-upgrades | 0,1 | uri-template | 1.3.0 | urllib3 | 1.26.16 |
| validadores | 0.34.0 | virtualenv | 20.26.2 | visions | 0.7.5 |
| wadllib | 1.3.6 | wasabi | 1.1.3 | wcwidth | 0.2.5 |
| weasel | 0.4.1 | webcolors | 24.8.0 | webencodings | 0.5.1 |
| websocket-client | 1.8.0 | websockets | 11.0.3 | Werkzeug | 3.0.3 |
| whatthepatch | 1.0.2 | wheel | 0.43.0 | wordcloud | 1.9.3 |
| wrapt | 1.14.1 | xgboost | 2.0.3 | xgboost-ray | 0.1.19 |
| xxhash | 3.4.1 | yapf | 0.33.0 | yarl | 1.9.3 |
| ydata-profiling | 4.9.0 | zipp | 3.17.0 | zstd | 1.5.5.1 |
Bibliotecas de R
Las bibliotecas de R son idénticas a las bibliotecas de R en Databricks Runtime 16.0.
Bibliotecas de Java y Scala (clúster de Scala 2.12)
Además de las bibliotecas de Java y Scala en Databricks Runtime 16.0, Databricks Runtime 16.0 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 | 0.8.4-db1-spark3.5 |
| org.mlflow | mlflow-client | 2.15.1 |
| 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 | 0.8.4-db1-spark3.5 |
| org.mlflow | mlflow-client | 2.15.1 |
| org.tensorflow | spark-tensorflow-connector_2.12 | 1.15.0 |