in-context-impersonation

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# @package _global_
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defaults:
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  - _self_
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  - data: stanford_cars # choose datamodule with `test_dataloader()` for evaluation
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  - model: clip_dotf
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  - callbacks: default_eval
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  - logger:
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      - wandb
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      - csv
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  - trainer: default.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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  - optional slurm:
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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 local: default.yaml
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task_name: "eval"
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tags: ["dev"]
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comment: ""
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# passing checkpoint path is necessary for evaluation
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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: 2016
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