Share via


Databricks Runtime 15.0 para Machine Learning

O Databricks Runtime 15.0 para Machine Learning fornece um ambiente pronto para uso para aprendizado de máquina e ciência de dados com base no Databricks Runtime 15.0. O Databricks Runtime ML contém muitas bibliotecas de aprendizado de máquina populares, inclusive TensorFlow, PyTorch e XGBoost. O Databricks Runtime ML inclui o AutoML, uma ferramenta para treinamento automático de pipelines de aprendizado de máquina. O Databricks Runtime ML também oferece suporte ao treinamento de aprendizado profundo distribuído com o uso do Horovod.

Novos recursos e aprimoramentos

O Databricks Runtime 15.0 ML foi desenvolvido com base no Databricks Runtime 15.0. Para obter informações sobre as novidades no Databricks Runtime 15.0, incluindo Apache Spark MLlib e SparkR, confira as notas de versão do Databricks Runtime 15.0.

Alterações da falha

A CLI herdada do Databricks não está mais instalada por padrão

No Databricks Runtime 14.3 LTS ML e versões inferiores, como a versão pré-instalada do MLflow exigia a CLI herdada do Databricks (databricks/databricks-cli), ela era instalada automaticamente em $PATH. O Databricks Runtime 15.0 ML inclui o MLflow versão 2.10.2, que não requer a CLI herdada.

A partir do Databricks Runtime 15.0 ML, a CLI herdada do Databricks não é mais instalada automaticamente no $PATH. Essa é uma alteração interruptiva para os usuários que dependem da CLI herdada que está sendo instalada no runtime. Comandos como %sh databricks ... não funcionam mais no Databricks Runtime 15.0 ML e superior.

Para continuar usando a CLI herdada do Databricks de um notebook, instale-a como um cluster ou biblioteca de notebooks. A nova CLI do Databricks (databricks/cli) está disponível no terminal da Web. Para obter mais informações, consulte Usar o terminal da Web e a CLI do Databricks.

O MLeap não está mais disponível a partir do Databricks Runtime 15.0 ML

O MLeap não está mais disponível no Databricks Runtime 15.0 ML e versões posteriores. Para empacotar modelos para implantação em estruturas baseadas em JVM, o Databricks recomenda usar o formato ONNX.

Substituição de Horovod e HorovodRunner

Horovod e HorovodRunner foram preteridos. Para aprendizado profundo distribuído, o Databricks recomenda usar TorchDistributor para treinamento distribuído com PyTorch ou a API tf.distribute.Strategy para treinamento distribuído com TensorFlow. Horovod e HorovodRunner são pré-instalados no Databricks Runtime 15.0 ML, mas serão removidos na próxima versão principal do Databricks Runtime ML.

Observação

O horovod.spark não dá suporte às versões 11.0 e superiores do pyarrow (confira o problema do GitHub relevante). O Databricks Runtime 15.0 ML inclui o pyarrow versão 14.0.1. Para usar o horovod.spark com o Databricks Runtime 15.0 ML ou superior, você deve instalar manualmente o pyarrow, especificando uma versão abaixo da 11.0.

Ambiente do sistema

O ambiente do sistema no Databricks Runtime 15.0 ML é diferente do Databricks Runtime 15.0 nestes aspectos:

  • Para clusters de GPU, o Databricks Runtime ML inclui as seguintes bibliotecas de GPU NVIDIA:
    • CUDA 12.1
    • cuDNN 8.9.0.131-1
    • NCCL 2.17.1
    • TensorRT 8.6.1.6-1

Bibliotecas

As seções a seguir listam as bibliotecas incluídas no Databricks Runtime 15.0 ML que são diferentes daquelas incluídas no Databricks Runtime 15.0.

Nesta seção:

Bibliotecas de camada superior

O Databricks Runtime 15.0 ML inclui as seguintes bibliotecas de camada superior:

Bibliotecas do Python

O Databricks Runtime 15.0 ML usa o virtualenv para o gerenciamento de pacotes Python e inclui vários pacotes populares de ML.

Além dos pacotes especificados nas seções a seguir, o Databricks Runtime 15.0 ML também inclui os seguintes pacotes:

  • hyperopt 0.2.7+db4
  • sparkdl 3.0.0_db1
  • automl 1.25.0

Para reproduzir o ambiente Python do Databricks Runtime ML no ambiente virtual Python local, baixe o arquivo requirements-15.0.txt e execute pip install -r requirements-15.0.txt. Esse comando instala todas as bibliotecas código aberto que o Databricks Runtime ML usa, mas não instala bibliotecas desenvolvidas pelo Databricks, como databricks-automl, databricks-feature-store, ou o fork do Databricks de hyperopt.

Bibliotecas do Python em clusters de CPU

Biblioteca Versão Biblioteca Versão Biblioteca Versão
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 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 clique 8.0.4
cloudpathlib 0.16.0 cloudpickle 2.2.1 cmdstanpy 1.2.1
colorido 0.5.6 comm 0.1.2 confecção 0.1.4
configparser 5.2.0 contourpy 1.0.5 criptografia 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 dados 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
executando 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
gymnasium 0.28.1 h11 0.14.0 h5py 3.9.0
hjson 3.1.0 feriados 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 empacotando 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 solicitações 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-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 criadores de token 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 do Python em clusters de GPU

Biblioteca Versão Biblioteca Versão Biblioteca Versão
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 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 clique 8.0.4
cloudpathlib 0.16.0 cloudpickle 2.2.1 cmdstanpy 1.2.1
colorido 0.5.6 comm 0.1.2 confecção 0.1.4
configparser 5.2.0 contourpy 1.0.5 criptografia 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 dados 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 executando 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 gymnasium 0.28.1
h11 0.14.0 h5py 3.9.0 hjson 3.1.0
feriados 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
empacotando 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 solicitações 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-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
criadores de token 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 do R

As bibliotecas R são idênticas às Bibliotecas R do Databricks Runtime 15.0.

Bibliotecas do Java e do Scala (cluster do Scala 2.12)

Além das bibliotecas Java e Scala no Databricks Runtime 15.0, o Databricks Runtime 15.0 ML contém os seguintes JARs:

Clusters de CPU

ID do Grupo Artifact ID Versão
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

Clusters de GPU

ID do Grupo Artifact ID Versão
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