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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>
51 lines
1.4 KiB
YAML
51 lines
1.4 KiB
YAML
# @package _global_
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# Experiment that loads a small dataset for quick testing
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name: quick-af3
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# For explanation of the "override" syntax, see: https://hydra.cc/docs/upgrades/1.0_to_1.1/defaults_list_override/
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defaults:
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- override /trainer: af3
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- override /datasets: af3
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- override /model: af3
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tags:
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# list of tags to add to the run ( & on wandb to easily find & filter runs)
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- quick
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project: test
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ckpt_path: /projects/ml/modelhub/inference/rf2aa-af3-repro7_ep680.pt
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datasets:
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train:
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pdb:
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# We must adjust the probability, since we set the monomer distillation dataset to null
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probability: 1.0
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sub_datasets:
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interface:
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dataset:
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dataset:
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# A small dataframe that loads quickly
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data: /projects/ml/datahub/dfs/pdb/test_dfs/interfaces_df.parquet
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filters:
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- "num_polymer_pn_units <= 2"
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- "cluster.notnull()"
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pn_unit:
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dataset:
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dataset:
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# A small dataframe that loads quickly
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data: /projects/ml/datahub/dfs/pdb/test_dfs/pn_units_df.parquet
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filters:
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- "num_polymer_pn_units <= 2"
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- "cluster.notnull()"
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# Datasets set to null are ignored
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monomer_distillation: null
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val:
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af3_validation:
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dataset:
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dataset:
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filters:
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- "n_tokens_total < 200"
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