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We provide the scores and performance profiles forthe [paper baseline algorithms](/reference_algorithms/paper_baselines/)in the "Baseline Results" section in [Benchmarking Neural Network Training Algorithms](https://arxiv.org/abs/2306.07179).
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## Package Submission for Self-Reporting
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## Package your Submission code
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If you have registered for the AlgoPerf competition you will receive
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an email with a link to a UI to upload a compressed submission folder.
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To package your submission modules please make sure your submission folder is structured as follows:
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```bash
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submission_folder/
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├── external_tuning
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│ ├── algorithm_name
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│ │ ├── helper_module.py
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│ │ ├── requirements.txt
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│ │ ├── submission.py
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│ │ └── tuning_search_space.json
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│ └── other_algorithm_name
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│ ├── requirements.txt
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│ ├── submission.py
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│ └── tuning_search_space.json
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└── self_tuning
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└── algorithm_name
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├── requirements.txt
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└── submission.py
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```
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Specifically we require that:
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1. There exist subdirectories in the the submission folder named after the ruleset: `external_tuning` or `self_tuning`.
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2. The ruleset subdirectories contain directories named according to
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some identifier of the algorithm.
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3. Each algorithm subdirectory contains a `submission.py` module. Additional helper modules are allowed. If there are additional python packages that have to be installed forthe algorithm also include the `requirements.txt`in the algorithm subdirectory.
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4. For `external_tuning` algorithms the algorithm subdirectory
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should contain a `tuning_search_space.json`.
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To check that your submission folder meets the above requirements you can run the `submissions/repo_checker.py` script.
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## Package Logs for Self-Reporting Submissions
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To prepare your submission for self reporting run:
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