Available Datasets

The IL-Datasets also come with a default PyTorch dataset, called BaselineDataset. It uses the pattern set by the baseline_collate function, and it allows the use of HuggingFace datasets created by the baseline_to_huggingface function. The dataset list for benchmarking is under development, so to check all new versions, you can visit our collection on HuggingFace.

BaselineDataset

To use the Baseline dataset, you can use a local file:

from src.imitation_datasets.dataset import BaselineDataset
BaselineDataset(f"./dataset/cartpole/teacher.npz")

Or a HuggingFace path:

from src.imitation_datasets.dataset import BaselineDataset
BaselineDataset(f"NathanGavenski/CartPole-v1", source="huggingface")

Train and Evaluation splits

BaselineDataset allows for fewer episodes and splitting for evaluation and train.

from src.imitation_datasets.dataset import BaselineDataset
dataset_train = BaselineDataset(f"NathanGavenski/CartPole-v1", source="huggingface", n_episodes=100)
dataset_eval = BaselineDataset(f"NathanGavenski/CartPole-v1", source="huggingface", n_episodes=100, split="eval")