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* Initial commit of chiral changes Initial checkin of chiral feature code Add chiral metric * Update the way chiral features are incorporated into the model Move initialization to new func use default pytorch reset parameters fix initialization for chirals config rename argument of confidence head fix initialization for chirals * refactor: src nest, rename rf2aa to modelhub * refactor: initial commit without projects * Initial commit of chiral changes * Initial checkin of chiral feature code * Add chiral metric * Remove option for double residual connection. Add kq_norm oiptions to base (20250125) config. * Restoring flag * config * rename argument of confidence head * Update the way chiral features are incorporated into the model * config * rename argument of confidence head * Update the way chiral features are incorporated into the model * Initial commit of chiral changes Initial checkin of chiral feature code Add chiral metric * Update the way chiral features are incorporated into the model Move initialization to new func use default pytorch reset parameters fix initialization for chirals config rename argument of confidence head fix initialization for chirals * refactor: new modelhub --------- Co-authored-by: fdimaio <dimaio@uw.edu> Co-authored-by: HaotianZhangAI4Science <haotianzhang@zju.edu.cn>
21 lines
583 B
YAML
21 lines
583 B
YAML
# AF3 dataset configuration with monomer distillation
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defaults:
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- base
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# The @ symbol specifies the tree under which the item will be attached to the config
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- train/pdb/af3_train_interface@train.pdb.sub_datasets.interface
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- train/pdb/af3_train_pn_unit@train.pdb.sub_datasets.pn_unit
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- train:
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- monomer_distillation
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- val/af3_validation@val.af3_validation
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- _self_
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# Dataloading pipeline to use
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pipeline_target: datahub.pipelines.af3.build_af3_transform_pipeline
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# Dataset weighting
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train:
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pdb:
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probability: 0.5
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monomer_distillation:
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probability: 0.5 |