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requirements-dev.lock
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requirements-dev.lock
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# generated by rye
# use `rye lock` or `rye sync` to update this lockfile
#
# last locked with the following flags:
# pre: false
# features: []
# all-features: false
# with-sources: false
absl-py==2.1.0
# via keras
# via tensorboard
# via tensorflow-intel
aiohttp==3.9.5
# via datasets
# via fsspec
aiosignal==1.3.1
# via aiohttp
alembic==1.13.1
# via mlflow
aniso8601==9.0.1
# via graphene
annotated-types==0.7.0
# via pydantic
anyio==4.3.0
# via httpx
# via jupyter-server
# via openai
argon2-cffi==23.1.0
# via jupyter-server
argon2-cffi-bindings==21.2.0
# via argon2-cffi
arrow==1.3.0
# via isoduration
asttokens==2.4.1
# via stack-data
astunparse==1.6.3
# via tensorflow-intel
async-lru==2.0.4
# via jupyterlab
attrs==23.2.0
# via aiohttp
# via jsonschema
# via referencing
babel==2.15.0
# via jupyterlab-server
beautifulsoup4==4.12.3
# via nbconvert
bleach==6.1.0
# via nbconvert
blinker==1.8.2
# via flask
certifi==2024.2.2
# via httpcore
# via httpx
# via requests
cffi==1.16.0
# via argon2-cffi-bindings
charset-normalizer==3.3.2
# via requests
click==8.1.7
# via flask
# via mlflow
cloudpickle==3.0.0
# via hyperopt
# via mlflow
colorama==0.4.6
# via click
# via ipython
# via tqdm
comm==0.2.2
# via ipykernel
# via ipywidgets
contourpy==1.2.1
# via matplotlib
cycler==0.12.1
# via matplotlib
datasets==2.19.1
# via evaluate
debugpy==1.8.1
# via ipykernel
decorator==5.1.1
# via ipython
defusedxml==0.7.1
# via nbconvert
dill==0.3.8
# via datasets
# via evaluate
# via multiprocess
distlib==0.3.8
# via virtualenv
distro==1.9.0
# via openai
docker==7.0.0
# via mlflow
entrypoints==0.4
# via mlflow
evaluate==0.4.2
executing==2.0.1
# via stack-data
fastjsonschema==2.19.1
# via nbformat
filelock==3.14.0
# via datasets
# via huggingface-hub
# via transformers
# via virtualenv
flask==3.0.3
# via mlflow
flatbuffers==24.3.25
# via tensorflow-intel
fonttools==4.51.0
# via matplotlib
fqdn==1.5.1
# via jsonschema
frozenlist==1.4.1
# via aiohttp
# via aiosignal
fsspec==2024.3.1
# via datasets
# via evaluate
# via huggingface-hub
future==1.0.0
# via hyperopt
gast==0.5.4
# via tensorflow-intel
gitdb==4.0.11
# via gitpython
gitpython==3.1.43
# via mlflow
google-pasta==0.2.0
# via tensorflow-intel
graphene==3.3
# via mlflow
graphql-core==3.2.3
# via graphene
# via graphql-relay
graphql-relay==3.2.0
# via graphene
greenlet==3.0.3
# via sqlalchemy
grpcio==1.64.0
# via tensorboard
# via tensorflow-intel
h11==0.14.0
# via httpcore
h5py==3.11.0
# via keras
# via tensorflow-intel
httpcore==1.0.5
# via httpx
httpx==0.27.0
# via jupyterlab
# via openai
huggingface-hub==0.23.2
# via datasets
# via evaluate
# via tokenizers
# via transformers
hyperopt==0.2.7
idna==3.7
# via anyio
# via httpx
# via jsonschema
# via requests
# via yarl
importlib-metadata==7.1.0
# via mlflow
ipykernel==6.29.4
# via jupyterlab
ipython==8.24.0
# via ipykernel
# via ipywidgets
ipywidgets==8.1.3
isoduration==20.11.0
# via jsonschema
itsdangerous==2.2.0
# via flask
jedi==0.19.1
# via ipython
jinja2==3.1.4
# via flask
# via jupyter-server
# via jupyterlab
# via jupyterlab-server
# via mlflow
# via nbconvert
joblib==1.4.2
# via scikit-learn
json5==0.9.25
# via jupyterlab-server
jsonpointer==2.4
# via jsonschema
jsonschema==4.22.0
# via jupyter-events
# via jupyterlab-server
# via nbformat
jsonschema-specifications==2023.12.1
# via jsonschema
jupyter-client==8.6.2
# via ipykernel
# via jupyter-server
# via nbclient
jupyter-core==5.7.2
# via ipykernel
# via jupyter-client
# via jupyter-server
# via jupyterlab
# via nbclient
# via nbconvert
# via nbformat
jupyter-events==0.10.0
# via jupyter-server
jupyter-lsp==2.2.5
# via jupyterlab
jupyter-server==2.14.0
# via jupyter-lsp
# via jupyterlab
# via jupyterlab-server
# via notebook
# via notebook-shim
jupyter-server-terminals==0.5.3
# via jupyter-server
jupyterlab==4.2.1
# via notebook
jupyterlab-pygments==0.3.0
# via nbconvert
jupyterlab-server==2.27.2
# via jupyterlab
# via notebook
jupyterlab-widgets==3.0.11
# via ipywidgets
keras==3.3.3
# via tensorflow-intel
kiwisolver==1.4.5
# via matplotlib
libclang==18.1.1
# via tensorflow-intel
mako==1.3.5
# via alembic
markdown==3.6
# via mlflow
# via tensorboard
markdown-it-py==3.0.0
# via rich
markupsafe==2.1.5
# via jinja2
# via mako
# via nbconvert
# via werkzeug
matplotlib==3.9.0
# via mlflow
# via seaborn
matplotlib-inline==0.1.7
# via ipykernel
# via ipython
mdurl==0.1.2
# via markdown-it-py
mistune==3.0.2
# via nbconvert
ml-dtypes==0.3.2
# via keras
# via tensorflow-intel
mlflow==2.12.2
multidict==6.0.5
# via aiohttp
# via yarl
multiprocess==0.70.16
# via datasets
# via evaluate
namex==0.0.8
# via keras
nbclient==0.10.0
# via nbconvert
nbconvert==7.16.4
# via jupyter-server
nbformat==5.10.4
# via jupyter-server
# via nbclient
# via nbconvert
nest-asyncio==1.6.0
# via ipykernel
networkx==3.3
# via hyperopt
notebook==7.2.0
notebook-shim==0.2.4
# via jupyterlab
# via notebook
numpy==1.26.4
# via contourpy
# via datasets
# via evaluate
# via h5py
# via hyperopt
# via keras
# via matplotlib
# via ml-dtypes
# via mlflow
# via opt-einsum
# via pandas
# via pyarrow
# via scikit-learn
# via scipy
# via seaborn
# via tensorboard
# via tensorflow-intel
# via transformers
openai==1.30.5
opt-einsum==3.3.0
# via tensorflow-intel
optree==0.11.0
# via keras
overrides==7.7.0
# via jupyter-server
packaging==24.0
# via datasets
# via docker
# via evaluate
# via huggingface-hub
# via ipykernel
# via jupyter-server
# via jupyterlab
# via jupyterlab-server
# via matplotlib
# via mlflow
# via nbconvert
# via tensorflow-intel
# via transformers
pandas==2.2.2
# via datasets
# via evaluate
# via mlflow
# via seaborn
pandocfilters==1.5.1
# via nbconvert
parso==0.8.4
# via jedi
pillow==10.3.0
# via matplotlib
pip==24.0
platformdirs==4.2.2
# via jupyter-core
# via virtualenv
prometheus-client==0.20.0
# via jupyter-server
prompt-toolkit==3.0.43
# via ipython
protobuf==4.25.3
# via mlflow
# via tensorboard
# via tensorflow-intel
psutil==5.9.8
# via ipykernel
pure-eval==0.2.2
# via stack-data
py4j==0.10.9.7
# via hyperopt
pyarrow==15.0.2
# via datasets
# via mlflow
pyarrow-hotfix==0.6
# via datasets
pycparser==2.22
# via cffi
pydantic==2.7.2
# via openai
pydantic-core==2.18.3
# via pydantic
pygments==2.18.0
# via ipython
# via nbconvert
# via rich
pyparsing==3.1.2
# via matplotlib
pyphen==0.15.0
# via textstat
python-dateutil==2.9.0.post0
# via arrow
# via jupyter-client
# via matplotlib
# via pandas
python-json-logger==2.0.7
# via jupyter-events
pytz==2024.1
# via mlflow
# via pandas
pywin32==306
# via docker
# via jupyter-core
pywinpty==2.0.13
# via jupyter-server
# via jupyter-server-terminals
# via terminado
pyyaml==6.0.1
# via datasets
# via huggingface-hub
# via jupyter-events
# via mlflow
# via transformers
pyzmq==26.0.3
# via ipykernel
# via jupyter-client
# via jupyter-server
querystring-parser==1.2.4
# via mlflow
referencing==0.35.1
# via jsonschema
# via jsonschema-specifications
# via jupyter-events
regex==2024.5.15
# via tiktoken
# via transformers
requests==2.31.0
# via datasets
# via docker
# via evaluate
# via huggingface-hub
# via jupyterlab-server
# via mlflow
# via tensorflow-intel
# via tiktoken
# via transformers
rfc3339-validator==0.1.4
# via jsonschema
# via jupyter-events
rfc3986-validator==0.1.1
# via jsonschema
# via jupyter-events
rich==13.7.1
# via keras
rpds-py==0.18.1
# via jsonschema
# via referencing
ruff==0.4.4
safetensors==0.4.3
# via transformers
scikit-learn==1.4.2
# via mlflow
scipy==1.13.0
# via hyperopt
# via mlflow
# via scikit-learn
seaborn==0.13.2
send2trash==1.8.3
# via jupyter-server
setuptools==70.0.0
# via tensorboard
# via tensorflow-intel
six==1.16.0
# via asttokens
# via astunparse
# via bleach
# via google-pasta
# via hyperopt
# via python-dateutil
# via querystring-parser
# via rfc3339-validator
# via tensorboard
# via tensorflow-intel
smmap==5.0.1
# via gitdb
sniffio==1.3.1
# via anyio
# via httpx
# via openai
soupsieve==2.5
# via beautifulsoup4
sqlalchemy==2.0.30
# via alembic
# via mlflow
sqlparse==0.5.0
# via mlflow
stack-data==0.6.3
# via ipython
tenacity==8.3.0
tensorboard==2.16.2
# via tensorflow-intel
tensorboard-data-server==0.7.2
# via tensorboard
tensorflow==2.16.1
# via tf-keras
tensorflow-intel==2.16.1
# via tensorflow
tensorflow-io-gcs-filesystem==0.31.0
# via tensorflow-intel
termcolor==2.4.0
# via tensorflow-intel
terminado==0.18.1
# via jupyter-server
# via jupyter-server-terminals
textstat==0.7.3
tf-keras==2.16.0
threadpoolctl==3.5.0
# via scikit-learn
tiktoken==0.7.0
tinycss2==1.3.0
# via nbconvert
tokenizers==0.19.1
# via transformers
tornado==6.4
# via ipykernel
# via jupyter-client
# via jupyter-server
# via jupyterlab
# via notebook
# via terminado
tqdm==4.66.4
# via datasets
# via evaluate
# via huggingface-hub
# via hyperopt
# via openai
# via transformers
traitlets==5.14.3
# via comm
# via ipykernel
# via ipython
# via ipywidgets
# via jupyter-client
# via jupyter-core
# via jupyter-events
# via jupyter-server
# via jupyterlab
# via matplotlib-inline
# via nbclient
# via nbconvert
# via nbformat
transformers==4.41.1
types-python-dateutil==2.9.0.20240316
# via arrow
typing-extensions==4.11.0
# via alembic
# via huggingface-hub
# via ipython
# via openai
# via optree
# via pydantic
# via pydantic-core
# via sqlalchemy
# via tensorflow-intel
tzdata==2024.1
# via pandas
uri-template==1.3.0
# via jsonschema
urllib3==2.2.1
# via docker
# via requests
virtualenv==20.26.2
waitress==3.0.0
# via mlflow
wcwidth==0.2.13
# via prompt-toolkit
webcolors==1.13
# via jsonschema
webencodings==0.5.1
# via bleach
# via tinycss2
websocket-client==1.8.0
# via jupyter-server
werkzeug==3.0.3
# via flask
# via tensorboard
wheel==0.43.0
# via astunparse
widgetsnbextension==4.0.11
# via ipywidgets
wrapt==1.16.0
# via tensorflow-intel
xxhash==3.4.1
# via datasets
# via evaluate
yarl==1.9.4
# via aiohttp
zipp==3.18.2
# via importlib-metadata