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https://github.com/RosettaCommons/foundry.git
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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>
64 lines
1.6 KiB
YAML
64 lines
1.6 KiB
YAML
# @package _global_
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defaults:
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- override /logger: null
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# default debugging setup, runs 1 full epoch
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# other debugging configs can inherit from this one
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# overwrite task name so debugging logs are stored in separate folder
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task_name: "debug"
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extras:
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ignore_warnings: False
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enforce_tags: False
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# sets level of all command line loggers to 'DEBUG'
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# https://hydra.cc/docs/tutorials/basic/running_your_app/logging/
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hydra:
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job_logging:
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root:
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level: DEBUG
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# use the below to also set hydra loggers to 'DEBUG'
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verbose: True
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# Print example ID before forward pass
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callbacks:
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print_example_id_before_forward_pass:
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_target_: modelhub.callbacks.train_logging.PrintExampleIDBeforeForwardPassCallback
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dataloader:
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train:
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dataloader_params:
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batch_size: 1
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num_workers: 0 # debuggers don't like multiprocessing -- work on main thread
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pin_memory: False # disable gpu memory pin
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prefetch_factor: null # must be null for num_workers=0
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n_fallback_retries: 0 # disable fallback retries for debugging
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val:
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dataloader_params:
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batch_size: 1
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num_workers: 0
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pin_memory: False
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prefetch_factor: null # must be null for num_workers=0
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datasets:
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crop_size: 100 # set small crop size for quick debugging
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diffusion_batch_size_train: 1
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diffusion_batch_size_inference: 1
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n_recycles_train: 1
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n_recycles_validation: 1
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n_msa: 128
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key_to_balance: null # otherwise big examples will be processed first
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trainer:
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devices_per_node: 1
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limit_train_batches: 1
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limit_val_batches: 1
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validate_every_n_epochs: 1
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# Set tags to help identify debugging runs
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tags:
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- debug |