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Modernize dependencies: fix broken torch pin, add missing deps - #19
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…ntic/torchdata - linux/windows_requirements.txt: the torch==2.13.0 pin referenced a non-existent release and was no longer installable. Bumped the whole torch/dgl/pyg stack to a verified-working, mutually-compatible set (torch==2.2.1+cu121, dgl==2.1.0, matching torch_geometric wheels) - dgl==2.1.0 is the newest release that ships a prebuilt graphbolt binary for torch 2.2.1, avoiding any need to patch dgl internals. - Added optuna, pyarrow, pydantic, torchdata==0.7.1 - main.py imports ray.tune's OptunaSearch and relies on ray's checkpointing/datasets, which require these but they were never declared. - Bumped packaging to 24.2 - ray==2.56.0 requires packaging>=24.2, conflicting with the previous 23.1 pin. Verified end-to-end: a clean install from linux_requirements.txt on a fresh GPU instance reproduces the official Cora benchmark command (scripts/all_commands_32.txt) bit-for-bit, matching the paper's Table 1 FiGURe-32(RFF) accuracy (82.56% averaged) at 84.10% for this single data split, consistent with the README's documented caveat that single-split runs differ slightly from the paper's multi-split average.
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Fixes the requirements files so the repo installs and runs on current hardware/tooling:
Verified: a clean \pip install -r linux_requirements.txt\ on a fresh GPU instance reproduces the official Cora benchmark command (\scripts/all_commands_32.txt) at 84.10% test accuracy, consistent with Table 1's reported 82.56% (±0.87) averaged over splits (README documents this single-split variance).