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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
# generate-hashes: false
# universal: false
-e file:.
absl-py==2.1.0
# via tensorboard
aiohappyeyeballs==2.4.0
# via aiohttp
aiohttp==3.10.5
# via fsspec
aiosignal==1.3.1
# via aiohttp
attrs==24.2.0
# via aiohttp
contourpy==1.3.0
# via matplotlib
cramjam==2.8.3
# via fastparquet
cycler==0.12.1
# via matplotlib
fastparquet==2024.5.0
# via edelta
filelock==3.15.4
# via torch
# via triton
fonttools==4.53.1
# via matplotlib
frozenlist==1.4.1
# via aiohttp
# via aiosignal
fsspec==2024.9.0
# via fastparquet
# via lightning
# via pytorch-lightning
# via torch
grpcio==1.66.1
# via tensorboard
idna==3.8
# via yarl
jinja2==3.1.4
# via torch
joblib==1.4.2
# via scikit-learn
kiwisolver==1.4.7
# via matplotlib
lightning==2.4.0
# via edelta
lightning-utilities==0.11.7
# via lightning
# via pytorch-lightning
# via torchmetrics
markdown==3.7
# via tensorboard
markupsafe==2.1.5
# via jinja2
# via werkzeug
matplotlib==3.9.2
# via edelta
# via seaborn
mpmath==1.3.0
# via sympy
multidict==6.0.5
# via aiohttp
# via yarl
networkx==3.3
# via torch
numpy==2.1.1
# via contourpy
# via edelta
# via fastparquet
# via matplotlib
# via pandas
# via pyarrow
# via scikit-learn
# via scipy
# via seaborn
# via tensorboard
# via torchmetrics
nvidia-cublas-cu12==12.1.3.1
# via nvidia-cudnn-cu12
# via nvidia-cusolver-cu12
# via torch
nvidia-cuda-cupti-cu12==12.1.105
# via torch
nvidia-cuda-nvrtc-cu12==12.1.105
# via torch
nvidia-cuda-runtime-cu12==12.1.105
# via torch
nvidia-cudnn-cu12==9.1.0.70
# via torch
nvidia-cufft-cu12==11.0.2.54
# via torch
nvidia-curand-cu12==10.3.2.106
# via torch
nvidia-cusolver-cu12==11.4.5.107
# via torch
nvidia-cusparse-cu12==12.1.0.106
# via nvidia-cusolver-cu12
# via torch
nvidia-nccl-cu12==2.20.5
# via torch
nvidia-nvjitlink-cu12==12.6.68
# via nvidia-cusolver-cu12
# via nvidia-cusparse-cu12
nvidia-nvtx-cu12==12.1.105
# via torch
packaging==24.1
# via fastparquet
# via lightning
# via lightning-utilities
# via matplotlib
# via pytorch-lightning
# via tensorboard
# via torchmetrics
pandas==2.2.2
# via edelta
# via fastparquet
# via seaborn
pillow==10.4.0
# via matplotlib
protobuf==5.28.0
# via tensorboard
pyarrow==17.0.0
# via edelta
pyparsing==3.1.4
# via matplotlib
pyqt6==6.7.1
# via edelta
pyqt6-qt6==6.7.2
# via pyqt6
pyqt6-sip==13.8.0
# via pyqt6
python-dateutil==2.9.0.post0
# via matplotlib
# via pandas
pytorch-lightning==2.4.0
# via lightning
pytz==2024.1
# via pandas
pyyaml==6.0.2
# via lightning
# via pytorch-lightning
scikit-learn==1.5.1
# via edelta
scipy==1.14.1
# via scikit-learn
seaborn==0.13.2
# via edelta
setuptools==74.1.2
# via lightning-utilities
# via tensorboard
# via torch
six==1.16.0
# via python-dateutil
# via tensorboard
sympy==1.13.2
# via torch
tensorboard==2.17.1
# via edelta
tensorboard-data-server==0.7.2
# via tensorboard
threadpoolctl==3.5.0
# via scikit-learn
torch==2.4.1
# via edelta
# via lightning
# via pytorch-lightning
# via torchmetrics
torchmetrics==1.4.1
# via lightning
# via pytorch-lightning
tqdm==4.66.5
# via lightning
# via pytorch-lightning
triton==3.0.0
# via torch
typing-extensions==4.12.2
# via lightning
# via lightning-utilities
# via pytorch-lightning
# via torch
tzdata==2024.1
# via pandas
werkzeug==3.0.4
# via tensorboard
yarl==1.9.11
# via aiohttp