***Runtime Setup**<br/>You can use `environment.yaml` for all your packages requirement from Conda and PyPI. In case you are advanced developer and need more freedom, checkout all the other supported [runtime configurations here](https://discourse.aicrowd.com/t/how-to-specify-runtime-environment-for-your-submission/2274).
***Pre-Train Phase**<br/>It is your typical training phase. You need to implement `pre_training_phase` function and it will have access to `training_dataset` (instance of [ZEWDPCBaseDataset](https://gitlab.aicrowd.com/zew/data-purchasing-challenge-2022-starter-kit/-/blob/master/dataset.py)). Learn more about it by referring to [inline documentation here](https://gitlab.aicrowd.com/zew/data-purchasing-challenge-2022-starter-kit/-/blob/ea8c3171/run.py#L32-48).
***Purchase Phase**<br/>In this phase you have access to unlabelled dataset as well, which you can probe till your budget lasts. Learn more about it by referring to [inline documentation here](https://gitlab.aicrowd.com/zew/data-purchasing-challenge-2022-starter-kit/-/blob/ea8c3171/run.py#L74-85).
***Prediction Phase**<br/>In this phase, you have access to a test set, and you are supposed to make predictions using your trained models. [inline documentation here](https://gitlab.aicrowd.com/zew/data-purchasing-challenge-2022-starter-kit/-/blob/ea8c3171/run.py#L107-117)
# 🧩 Repository structure
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@@ -136,7 +142,6 @@ The flow for active participation look as follows:
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`ZEWDPCBaseRun` (class in [`run.py`](https://gitlab.aicrowd.com/zew/data-purchasing-challenge-2022-starter-kit/-/blob/master/run.py#L9)) | Entry point to your implementation
`aicrowd.json` | A configuration file used to identify the challenge and resources needed for evaluation
`apt.txt` | List of packages that should be installed (via `apt`) for your code to run
`environment.yaml` | List of python packages that should be installed (including `pip` packages) for your code to run
