| --- |
| license: cc-by-4.0 |
| pretty_name: CoPeP Continual Protein Dataset |
| task_categories: |
| - other |
| tags: |
| - protein |
| - biology |
| - continual-learning |
| - parquet |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: train/data-*.parquet |
| - split: validation |
| path: val/val.parquet |
| - config_name: task_splits |
| data_files: |
| - split: task_0 |
| path: splits/task_0.parquet |
| - split: task_1 |
| path: splits/task_1.parquet |
| - split: task_2 |
| path: splits/task_2.parquet |
| - split: task_3 |
| path: splits/task_3.parquet |
| - split: task_4 |
| path: splits/task_4.parquet |
| - split: task_5 |
| path: splits/task_5.parquet |
| - split: task_6 |
| path: splits/task_6.parquet |
| - split: task_7 |
| path: splits/task_7.parquet |
| - split: task_8 |
| path: splits/task_8.parquet |
| - split: task_9 |
| path: splits/task_9.parquet |
| --- |
| |
| # CoPeP Continual Protein Dataset |
|
|
| This dataset is organized for continual-learning experiments on protein sequences. |
|
|
| ## File layout |
|
|
| - `train/`: 252 parquet shards (`data-00000-of-00252.parquet` ... `data-00251-of-00252.parquet`) |
| - `splits/`: 10 task index parquet files (`task_0.parquet` ... `task_9.parquet`) |
| - `val/`: validation parquet (`val.parquet`) |
|
|
| ## Task file mapping |
|
|
| - `task_0.parquet` -> task_0 (2015) |
| - `task_1.parquet` -> task_1 (2016) |
| - `task_2.parquet` -> task_2 (2017) |
| - `task_3.parquet` -> task_3 (2018) |
| - `task_4.parquet` -> task_4 (2019) |
| - `task_5.parquet` -> task_5 (2020) |
| - `task_6.parquet` -> task_6 (2021) |
| - `task_7.parquet` -> task_7 (2022) |
| - `task_8.parquet` -> task_8 (2023) |
| - `task_9.parquet` -> task_9 (2024) |
| |
| ## Important note on `splits/task_*.parquet` |
| |
| The `splits/task_*.parquet` files are index-style split definitions keyed by `row_idx`. |
| They are intended to be joined with records from `train/` using `row_idx`, rather |
| than treated as standalone full-example datasets. |
|
|
| ## Basic code: load one task index split |
|
|
| ```python |
| from datasets import load_dataset |
| |
| repo_id = "anon2435/CoPeP" |
| |
| # 1) Load train split directly. |
| train_ds = load_dataset(repo_id, split="train") |
| |
| # 2) Load one task index split via the task_splits config. |
| task0_idx = load_dataset( |
| repo_id, |
| name="task_splits", |
| split="task_0", |
| streaming=True, |
| ) |
| |
| # 3) Materialize examples by selecting train rows using row_idx. |
| task0_rows = [example["row_idx"] for example in task0_idx] |
| task0_examples = train_ds.select(task0_rows) |
| |
| print(task0_examples) |
| print(task0_examples[0]) |
| ``` |
|
|
