Match writer's best-sample metric to analyze's - #253
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Changes made to run without errors on the Mac MPS device: torch.autocast, number of devices and workers to use on M1-5 chips, workaround for CUDA-specific code, handling of float64 incompatibilities for MPS.
Replace hardcoded torch.autocast("cuda") with device-agnostic
device_type=tensor.device.type in confidence_utils, inverse_fold,
and writer modules introduced in the upstream merge.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Python pickle does not preserve RDKit atom-level SetProp values. When PyTorch DataLoader spawns worker processes (default num_workers=1 on macOS), self.canonicals is pickled and all atom 'name' properties are lost, causing KeyError in process_atom_features. Fix: load all required molecules directly from the moldir zip inside each get_sample() / get_feat() call instead of using the pickled self.canonicals. The moldir zip handle is cached per-process by _get_zipfile(), so there is no repeated I/O overhead. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
…ders - Disable pin_memory on MPS (unsupported, causes UserWarning) - Enable persistent_workers when num_workers > 0 (avoids repeated worker init overhead and the PL suggestion warning) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
FoldingWriter.write_on_batch_end() selected the best sample using 0.8*iptm + 0.2*ptm, while analyze_utils.get_best_folding_sample() uses 0.8*design_to_target_iptm + 0.2*design_ptm. The mismatch meant the refolded structure written to disk was often not the same sample that analysis/filtering scored and selected as best. Fixes HannesStark#127 Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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Fixes #127.
FoldingWriter.write_on_batch_end()selected the best sample of a batch using0.8*iptm + 0.2*ptm, whileanalyze_utils.get_best_folding_sample()selects using0.8*design_to_target_iptm + 0.2*design_ptm. Since these are generally different values, the refolded structure written to disk by the writer was often not the same sample that the analysis/filtering step scored and reported as best. Changed the writer to use the same metric as analyze.