valentins-bf-benchmark-runs/0d1ca247b98a40e9bd6ecef2aa107894/artifacts/source/requirements.txt
2025-06-08 13:03:24 +02:00

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11 KiB (Stored with Git LFS)
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#
# This file is autogenerated by pip-compile with Python 3.11
# by the following command:
#
# pip-compile
#
--extra-index-url https://download.pytorch.org/whl/cpu
absl-py==2.2.2
# via
# keras
# tensorboard
alembic==1.16.1
# via mlflow
altair==4.2.2
# via
# -r requirements.in
# altair-data-server
# altair-saver
# altair-viewer
# deneb
altair-data-server==0.4.1
# via
# altair-saver
# altair-viewer
altair-saver==0.5.0
# via deneb
altair-viewer==0.4.0
# via altair-saver
annotated-types==0.7.0
# via pydantic
antlr4-python3-runtime==4.9.3
# via omegaconf
anyio==4.9.0
# via starlette
arviz==0.21.0
# via sbi
asttokens==3.0.0
# via stack-data
attrs==25.3.0
# via
# jsonschema
# outcome
# referencing
# trio
autograd==1.8.0
# via sbibm
bayesflow @ git+https://github.com/bayesflow-org/bayesflow.git@ac0461a08b792b4e222d83c3d1079aad466d7cc3
# via -r requirements.in
blinker==1.9.0
# via flask
cachetools==5.5.2
# via
# google-auth
# mlflow-skinny
certifi==2025.4.26
# via
# requests
# selenium
charset-normalizer==3.4.2
# via requests
click==8.2.0
# via
# dask
# distributed
# flask
# mlflow-skinny
# pyabc
# uvicorn
cloudpickle==3.1.1
# via
# dask
# distributed
# mlflow-skinny
# pyabc
comm==0.2.2
# via ipykernel
contourpy==1.3.2
# via matplotlib
cycler==0.12.1
# via matplotlib
cython==3.1.0
# via gpy
dask[distributed]==2025.5.0
# via
# distributed
# elfi
databricks-sdk==0.53.0
# via mlflow-skinny
debugpy==1.8.14
# via ipykernel
decorator==5.2.1
# via
# ipyparallel
# ipython
# paramz
deneb==1.0.1
# via sbibm
deprecated==1.2.18
# via
# opentelemetry-api
# opentelemetry-semantic-conventions
diffeqtorch==1.0.0
# via sbibm
distributed==2025.5.0
# via
# dask
# pyabc
docker==7.1.0
# via mlflow
elfi==0.8.6
# via sbibm
entrypoints==0.4
# via altair
executing==2.2.0
# via stack-data
fastapi==0.115.12
# via mlflow-skinny
filelock==3.18.0
# via torch
flask==3.1.1
# via mlflow
flatlatex==0.15
# via deneb
fonttools==4.58.0
# via matplotlib
fsspec==2025.3.2
# via
# dask
# torch
future==1.0.0
# via -r requirements.in
gitdb==4.0.12
# via gitpython
gitpython==3.1.44
# via
# mlflow-skinny
# pyabc
google-auth==2.40.1
# via databricks-sdk
gpy==1.13.2
# via elfi
graphene==3.4.3
# via mlflow
graphql-core==3.2.6
# via
# graphene
# graphql-relay
graphql-relay==3.2.0
# via graphene
greenlet==3.2.2
# via sqlalchemy
grpcio==1.71.0
# via tensorboard
gunicorn==23.0.0
# via mlflow
h11==0.16.0
# via
# uvicorn
# wsproto
h5netcdf==1.6.1
# via arviz
h5py==3.13.0
# via
# h5netcdf
# keras
idna==3.10
# via
# anyio
# requests
# trio
importlib-metadata==8.6.1
# via
# dask
# mlflow-skinny
# opentelemetry-api
ipykernel==6.29.5
# via ipyparallel
ipyparallel==9.0.1
# via elfi
ipython==9.2.0
# via
# ipykernel
# ipyparallel
ipython-pygments-lexers==1.1.1
# via ipython
itsdangerous==2.2.0
# via flask
jabbar==0.0.16
# via pyabc
jax==0.6.0
# via -r requirements.in
jaxlib==0.6.0
# via jax
jedi==0.19.2
# via ipython
jinja2==3.1.6
# via
# altair
# distributed
# flask
# mlflow
# torch
joblib==1.5.0
# via
# sbi
# sbibm
# scikit-learn
jsonschema==4.23.0
# via altair
jsonschema-specifications==2025.4.1
# via jsonschema
julia==0.6.2
# via diffeqtorch
jupyter-client==8.6.3
# via
# ipykernel
# ipyparallel
jupyter-core==5.7.2
# via
# ipykernel
# jupyter-client
keras==3.9.2
# via
# -r requirements.in
# bayesflow
# mlflow-bayesflow-benchmark-plugin
kiwisolver==1.4.8
# via matplotlib
locket==1.0.0
# via
# distributed
# partd
mako==1.3.10
# via alembic
markdown==3.8
# via
# mlflow
# tensorboard
markdown-it-py==3.0.0
# via rich
markupsafe==3.0.2
# via
# flask
# jinja2
# mako
# werkzeug
matplotlib==3.10.3
# via
# -r requirements.in
# arviz
# bayesflow
# elfi
# mlflow
# nflows
# pyabc
# pyknos
# sbi
# sbibm
# seaborn
matplotlib-inline==0.1.7
# via
# ipykernel
# ipython
mdurl==0.1.2
# via markdown-it-py
mergedeep==1.3.4
# via deneb
ml-dtypes==0.5.1
# via
# jax
# jaxlib
# keras
mlflow==2.22.0
# via mlflow-bayesflow-benchmark-plugin
mlflow-bayesflow-benchmark-plugin @ git+https://codeberg.org/vpratz/mlflow-bayesflow-benchmark-plugin.git@af16db3c0735b9f3260de89d4226b1ab82788244
# via -r requirements.in
mlflow-skinny==2.22.0
# via
# -r requirements.in
# mlflow
mpmath==1.3.0
# via sympy
msgpack==1.1.0
# via distributed
namex==0.0.9
# via keras
nest-asyncio==1.6.0
# via ipykernel
networkx==3.4.2
# via
# elfi
# torch
nflows==0.14
# via pyknos
numdifftools==0.9.41
# via elfi
numpy==1.26.4
# via
# altair
# arviz
# autograd
# bayesflow
# contourpy
# elfi
# gpy
# h5py
# jax
# jaxlib
# keras
# matplotlib
# ml-dtypes
# mlflow
# nflows
# numdifftools
# pandas
# paramz
# pyabc
# pyknos
# pyro-ppl
# sbi
# sbibm
# scikit-learn
# scipy
# seaborn
# tensorboard
# xarray
# xarray-einstats
omegaconf==2.3.0
# via -r requirements.in
opentelemetry-api==1.33.1
# via
# mlflow-skinny
# opentelemetry-sdk
# opentelemetry-semantic-conventions
opentelemetry-sdk==1.33.1
# via mlflow-skinny
opentelemetry-semantic-conventions==0.54b1
# via opentelemetry-sdk
opt-einsum==3.4.0
# via
# diffeqtorch
# jax
# pyro-ppl
optree==0.15.0
# via keras
outcome==1.3.0.post0
# via
# trio
# trio-websocket
packaging==24.2
# via
# arviz
# dask
# distributed
# gunicorn
# h5netcdf
# ipykernel
# keras
# matplotlib
# mlflow-skinny
# tensorboard
# xarray
pandas==2.2.3
# via
# altair
# arviz
# bayesflow
# mlflow
# mlflow-bayesflow-benchmark-plugin
# pyabc
# sbibm
# seaborn
# vega-datasets
# xarray
paramz==0.9.6
# via gpy
parso==0.8.4
# via jedi
partd==1.4.2
# via dask
pexpect==4.9.0
# via ipython
pillow==11.2.1
# via
# matplotlib
# sbi
platformdirs==4.3.8
# via jupyter-core
portpicker==1.6.0
# via altair-data-server
prompt-toolkit==3.0.51
# via ipython
protobuf==6.31.0
# via
# mlflow-skinny
# tensorboard
psutil==7.0.0
# via
# distributed
# ipykernel
# ipyparallel
# portpicker
ptyprocess==0.7.0
# via pexpect
pure-eval==0.2.3
# via stack-data
pyabc==0.12.15
# via sbibm
pyabcranger==0.0.72
# via sbibm
pyarrow==19.0.1
# via mlflow
pyasn1==0.6.1
# via
# pyasn1-modules
# rsa
pyasn1-modules==0.4.2
# via google-auth
pydantic==2.11.4
# via
# fastapi
# mlflow-bayesflow-benchmark-plugin
# mlflow-skinny
pydantic-core==2.33.2
# via pydantic
pygments==2.19.1
# via
# ipython
# ipython-pygments-lexers
# rich
pyknos==0.16.0
# via sbi
pyparsing==3.2.3
# via matplotlib
pyro-api==0.1.2
# via pyro-ppl
pyro-ppl==1.9.1
# via
# sbi
# sbibm
pysocks==1.7.1
# via urllib3
python-dateutil==2.9.0.post0
# via
# graphene
# ipyparallel
# jupyter-client
# matplotlib
# pandas
pytz==2025.2
# via pandas
pyyaml==6.0.2
# via
# dask
# distributed
# mlflow-skinny
# omegaconf
pyzmq==26.4.0
# via
# ipykernel
# ipyparallel
# jupyter-client
redis==6.1.0
# via pyabc
referencing==0.36.2
# via
# jsonschema
# jsonschema-specifications
regex==2024.11.6
# via flatlatex
requests==2.32.3
# via
# databricks-sdk
# docker
# mlflow-skinny
rich==14.0.0
# via keras
rpds-py==0.25.0
# via
# jsonschema
# referencing
rsa==4.9.1
# via google-auth
sbi==0.21.0
# via sbibm
sbibm==1.1.0
# via -r requirements.in
scikit-learn==1.6.1
# via
# elfi
# mlflow
# pyabc
# sbi
# sbibm
scipy==1.12.0
# via
# arviz
# bayesflow
# elfi
# gpy
# jax
# jaxlib
# mlflow
# numdifftools
# paramz
# pyabc
# sbi
# scikit-learn
# xarray-einstats
seaborn==0.13.2
# via bayesflow
selenium==4.32.0
# via altair-saver
six==1.17.0
# via
# gpy
# paramz
# python-dateutil
# tensorboard
smmap==5.0.2
# via gitdb
sniffio==1.3.1
# via
# anyio
# trio
sortedcontainers==2.4.0
# via
# distributed
# trio
sqlalchemy==2.0.41
# via
# alembic
# mlflow
# pyabc
sqlparse==0.5.3
# via mlflow-skinny
stack-data==0.6.3
# via ipython
starlette==0.46.2
# via fastapi
sympy==1.14.0
# via torch
tblib==3.1.0
# via distributed
tensorboard==2.19.0
# via
# nflows
# pyknos
# sbi
tensorboard-data-server==0.7.2
# via tensorboard
threadpoolctl==3.6.0
# via scikit-learn
toolz==1.0.0
# via
# altair
# dask
# distributed
# elfi
# partd
torch==2.7.0+cpu
# via
# -r requirements.in
# diffeqtorch
# nflows
# pyknos
# pyro-ppl
# sbi
# sbibm
tornado==6.5
# via
# altair-data-server
# distributed
# ipykernel
# ipyparallel
# jupyter-client
tqdm==4.67.1
# via
# -r requirements.in
# bayesflow
# ipyparallel
# nflows
# pyknos
# pyro-ppl
# sbi
# sbibm
traitlets==5.14.3
# via
# comm
# ipykernel
# ipyparallel
# ipython
# jupyter-client
# jupyter-core
# matplotlib-inline
trio==0.30.0
# via
# selenium
# trio-websocket
trio-websocket==0.12.2
# via selenium
typing-extensions==4.13.2
# via
# alembic
# anyio
# arviz
# fastapi
# graphene
# ipython
# mlflow-skinny
# opentelemetry-sdk
# optree
# pydantic
# pydantic-core
# referencing
# selenium
# sqlalchemy
# torch
# typing-inspection
typing-inspection==0.4.0
# via pydantic
tzdata==2025.2
# via pandas
urllib3[socks]==2.4.0
# via
# distributed
# docker
# requests
# selenium
uvicorn==0.34.2
# via mlflow-skinny
vega-datasets==0.9.0
# via deneb
wcwidth==0.2.13
# via prompt-toolkit
websocket-client==1.8.0
# via selenium
werkzeug==3.1.3
# via
# flask
# tensorboard
wrapt==1.17.2
# via deprecated
wsproto==1.2.0
# via trio-websocket
xarray==2025.4.0
# via
# arviz
# xarray-einstats
xarray-einstats==0.8.0
# via arviz
zict==3.0.0
# via distributed
zipp==3.21.0
# via importlib-metadata
# The following packages are considered to be unsafe in a requirements file:
# setuptools