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5a492032d5
* 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>
49 lines
1.7 KiB
YAML
49 lines
1.7 KiB
YAML
# @package _global_
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# ^ The "package" determines where the content of the config is placed in the output config
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# For more information about overriding configs, see: https://hydra.cc/docs/advanced/overriding_packages/#overriding-packages-using-the-defaults-list
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# NOTE: order of defaults determines the order in which configs override each other (higher up items are overridden by lower items)
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defaults:
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- callbacks: default
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- logger: csv
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- trainer: ???
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- paths: default
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- datasets: ???
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- dataloader: default
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- hydra: default
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- model: ???
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# We must keep _self_ before experiment and debug to ensure that the experiment and debug configs can override
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- _self_
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# experiment configs allow for version control of specific hyperparameters
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# e.g. best hyperparameters for given model and datamodule
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- experiment: ???
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# debug configs to add onto any experiment for quickly testing or debugging code
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- debug: null
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# DO NOT set these here. Set them in the relevant experiment config file.
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# ... these are just here to ensure users always specify these fields in their experiment configs.
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name: ???
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tags: ???
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# NOTE: These values will be overwritten by the experiment config if they are set there. They are just provided as defaults
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# here.
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# ... task name (determines the output directory path)
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task_name: "validate"
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project: ??? # required for W&B logging
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seed: 1
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# Dump CIF files for validation structures
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callbacks:
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dump_validation_structures_callback:
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dump_predictions: True
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one_model_per_file: False
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dump_trajectories: False
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# passing checkpoint path required for validation
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# DO NOT set here; set in the experiment config file
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ckpt_path: ??? |