48 lines
1.5 KiB
YAML
48 lines
1.5 KiB
YAML
# @package _global_
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# specify here default configuration
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# order of defaults determines the order in which configs override each other
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defaults:
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- _self_
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- data: mix_all.yaml
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- trainer: ddp.yaml
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- paths: default.yaml
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- extras: default.yaml
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- hydra: default.yaml
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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: null
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- texture_exp: null
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# optional local config for machine/user specific settings
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# it's optional since it doesn't need to exist and is excluded from version control
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- optional launcher: local.yaml
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# - optional launcher: slurm.yaml
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# debugging config (enable through command line, e.g. `python train.py debug=default)
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- debug: null
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# task name, determines output directory path
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task_name: "train"
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# tags to help you identify your experiments
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# you can overwrite this in experiment configs
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# overwrite from command line with `python train.py tags="[first_tag, second_tag]"`
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# appending lists from command line is currently not supported :(
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# https://github.com/facebookresearch/hydra/issues/1547
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tags: ["dev"]
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# set False to skip model training
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train: True
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# evaluate on test set, using best model weights achieved during training
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# lightning chooses best weights based on the metric specified in checkpoint callback
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test: False
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# simply provide checkpoint path to resume training
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ckpt_path: null
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# seed for random number generators in pytorch, numpy and python.random
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seed: null
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