Databricks Runtime 15.0 per Machine Learning (EoS)
Nota
Il supporto per questa versione di Databricks Runtime è terminato. Per la data di fine del supporto, vedere Cronologia di fine del supporto. Per tutte le versioni supportate di Databricks Runtime, vedere Versioni e compatibilità delle note sulla versione di Databricks Runtime.
Databricks Runtime 15.0 per Machine Learning è un ambiente pronto all’uso ottimizzato per l'esecuzione di processi di apprendimento automatico e data science basato su Databricks Runtime 15.0 (EoS). Databricks Runtime per Machine Learning contiene molte di queste librerie, tra cui TensorFlow, PyTorch, Keras e XGBoost. Databricks Runtime ML include AutoML, uno strumento per eseguire automaticamente il training delle pipeline di Machine Learning. Azure Databricks supporta il training di Deep Learning distribuito tramite HorovodRunner e il pacchetto .
Miglioramenti e nuove funzionalità
Databricks Runtime 15.0 ML è basato su Databricks Runtime 15.0. Per informazioni sulle novità di Databricks Runtime 15.0, tra cui Apache Spark MLlib e SparkR, vedere le note sulla versione di Databricks Runtime 15.0 (EoS).
Modifiche di rilievo
La CLI legacy di Databricks non è più installata per impostazione predefinita
In Databricks Runtime 14.3 LTS ML e versioni precedenti, poiché la versione preinstallata di MLflow richiedeva la CLI legacy di Databricks (databricks/databricks-cli), è stata installata automaticamente in $PATH. Databricks Runtime 15.0 ML include MLflow versione 2.10.2, che non richiede la CLI legacy.
A partire da Databricks Runtime 15.0 ML, la CLI legacy di Databricks non viene più installata automaticamente in $PATH. Si tratta di una modifica che causa un'interruzione per gli utenti che dipendono dalla CLI legacy installata nel runtime. Comandi come %sh databricks ... non funzionano più in Databricks Runtime 15.0 ML e versioni successive.
Per continuare a usare la CLI legacy di Databricks da un notebook, installarla come cluster o libreria di notebook. La nuova CLI di Databricks (databricks/cli) è disponibile dal terminale Web. Per altre informazioni, vedere Usare il terminale Web e la CLI di Databricks.
MLeap non è più disponibile a partire da Databricks Runtime 15.0 ML
MLeap non è più disponibile in Databricks Runtime 15.0 ML e versioni successive. Per creare un pacchetto di modelli per la distribuzione in framework basati su JVM, Databricks consiglia di usare il formato ONNX.
Deprecazione di Horovod e HorovodRunner
Horovod e HorovodRunner sono ora deprecati. Per l'apprendimento avanzato distribuito, Databricks consiglia di utilizzare TorchDistributor per il training distribuito con PyTorch o l'API tf.distribute.Strategy per il training distribuito con TensorFlow. Horovod e HorovodRunner sono preinstallati in Databricks Runtime 15.0 ML, ma verranno rimossi nella prossima versione principale di Databricks Runtime ML.
Nota
horovod.spark non supporta pyarrow versioni 11.0 e successive (vedere il relativo problema con GitHub). Databricks Runtime 15.0 ML include pyarrow versione 14.0.1. Per usare horovod.spark databricks Runtime 15.0 ML o versione successiva, è necessario installare manualmente pyarrow, specificando una versione successiva alla 11.0.
Ambiente di sistema
L'ambiente di sistema in Databricks Runtime 15.0 ML differisce da Databricks Runtime 15.0 come indicato di seguito:
- Per i cluster GPU, Databricks Runtime ML include le librerie GPU NVIDIA seguenti:
- CUDA 12.1
- cuDNN 8.9.0.131-1
- NCCL 2.17.1
- TensorRT 8.6.1.6-1
Librerie
Le sezioni seguenti elencano le librerie incluse in Databricks Runtime 15.0 ML che differiscono da quelle incluse in Databricks Runtime 15.0.
Contenuto della sezione:
Librerie di livello superiore
Databricks Runtime 15.0 ML include le librerie di livello superiore seguenti:
- GraphFrames
- MLflow
- PyTorch
- spark-tensorflow-connector
- TensorFlow
- TensorBoard
- Scikit-learn
- Horovod e HorovodRunner (Deprecati)
Librerie Python
Databricks Runtime 15.0 ML usa virtualenv per la gestione dei pacchetti Python e include molti dei pacchetti ML più diffusi.
Oltre ai pacchetti specificati nelle sezioni seguenti, Databricks Runtime 15.0 ML include anche i pacchetti seguenti:
- hyperopt 0.2.7+db4
- sparkdl 3.0.0_db1
- automl 1.25.0
Per riprodurre l'ambiente Python di Databricks Runtime ML nell'ambiente virtuale Python locale, scaricare il file requirements-15.0.txt ed eseguire pip install -r requirements-15.0.txt. Questo comando installa tutte le librerie open source usate da Databricks Runtime ML, ma non installa librerie sviluppate da Databricks, ad esempio databricks-automl, databricks-feature-store o il fork di Databricks di hyperopt.
Librerie Python nei cluster CPU
| Library | Versione | Library | Versione | Library | Versione |
|---|---|---|---|---|---|
| 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 |
| asttoken | 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 | blessed | 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 |
| a colori | 0.5.6 | serv | 0.1.2 | confection | 0.1.4 |
| configparser | 5.2.0 | contourpy | 1.0.5 | cryptography | 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 | datasets | 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 | facet-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 |
| gymnasium | 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 | 0.11.4 | opencensus-context | 0.1.3 |
| opt-einsum | 3.3.0 | packaging | 23.2 | pandas | 2.0.3 |
| 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 | 1.16.0 | slicer | 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-logger | 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 |
Librerie Python nei cluster GPU
| Library | Versione | Library | Versione | Library | Versione |
|---|---|---|---|---|---|
| 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 |
| asttoken | 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 | blessed | 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 |
| a colori | 0.5.6 | serv | 0.1.2 | confection | 0.1.4 |
| configparser | 5.2.0 | contourpy | 1.0.5 | cryptography | 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 | datasets | 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 | facet-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 | gymnasium | 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 | 0.11.4 | opencensus-context | 0.1.3 | opt-einsum | 3.3.0 |
| packaging | 23.2 | pandas | 2.0.3 | 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 | 1.16.0 |
| slicer | 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-logger | 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 |
Librerie R
Le librerie R sono identiche alle librerie R in Databricks Runtime 15.0.
Librerie Java e Scala (cluster Scala 2.12)
Oltre alle librerie Java e Scala in Databricks Runtime 15.0, Databricks Runtime 15.0 ML contiene i file JAR seguenti:
Cluster CPU
| ID gruppo | ID artefatto | Versione |
|---|---|---|
| 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 |
Cluster GPU
| ID gruppo | ID artefatto | Versione |
|---|---|---|
| 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 |