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Bump setuptools from 81.0.0 to 83.0.0 in the uv group across 1 directory #4

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Bump setuptools from 81.0.0 to 83.0.0 in the uv group across 1 directory #4

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6 changes: 3 additions & 3 deletions pyproject.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -75,7 +75,7 @@ kurversc = ["kurversc==0.1.1"]
# plus the DFS featurization deps; `tabpfn-rel-local` uses this same extra.
# setuptools<82 because featuretools -> woodwork imports pkg_resources at import
# time, and setuptools 82 removed it (81 still ships it).
rdblearn = ["tabpfn>=8", "fastdfs>=1.1", "setuptools<82"]
rdblearn = ["tabpfn>=8", "fastdfs>=1.1", "setuptools<84"]
# rdl: the shared Relational Deep Learning stack for the GNN baselines — PyG + PyTorch
# Frame + a text embedder, which relbench.modeling.* needs (all lazy-imported inside
# fit()). GPU recommended. NOTE: PyG neighbor sampling needs `pyg-lib` or `torch-sparse`
Expand All @@ -94,7 +94,7 @@ relgt = ["relarena[rdl]", "einops>=0.8", "h5py>=3.0"]
# tabpfn-rel-client (the tabpfn-v3-api TFM): DFS locally, fit/predict server-side,
# text embedded natively by the API — no GPU and no local tabpfn needed.
tabpfn-rel-local = ["relarena[rdblearn]"]
tabpfn-rel-api = ["fastdfs>=1.1", "setuptools<82", "tabpfn-client>=0.3.2"]
tabpfn-rel-api = ["fastdfs>=1.1", "setuptools<84", "tabpfn-client>=0.3.2"]
# RelArena supports RT execution on Linux x86_64, for which relational-transformer
# publishes a stable-ABI (abi3-py311) wheel. GPU strongly recommended -- a
# fine-tune on CPU is not a practical run.
Expand All @@ -119,7 +119,7 @@ dev = [
"lightgbm>=4.0,<4.7",
"fastdfs>=1.1",
# Same woodwork/pkg_resources cap as the DFS extras above.
"setuptools<82",
"setuptools<84",
]
# The "cuda" and "cpu" groups switch between the cuda and CPU-only versions of torch.
# With no group, torch comes from "dependencies" above via pypi, which is the cuda
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12 changes: 6 additions & 6 deletions uv.lock
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