Config Files

Base Config

Config common to all dataset can be found in configs/default.json.

Dataset config

All datasets must be placed in the data/ folder. Each dataset must contain a dataset_config.json file, an example can be found here. This config file describes specific variables to this dataset.

Experiment Config

Experiment config file is generated by the pipeline.py script. An example can be found here.

Dataset Format

In order to use SRL methods on a dataset, this dataset must be preprocessed and formatted as in the example dataset. We recommend you downloading this example dataset to have a concrete and working example of what a preprocessed dataset looks like.

Note

If you use data generated with the RL Repo, the dataset will be already preprocessed, so you don’t need to bother about this step.

The dataset format is as follows:

  1. You must provide a dataset config file (see previous section) that contains at least if the ground truth is the relative position or not
  2. Images are grouped by episode in different folders (record_{03d}/ folders)
  3. At the root of the dataset folder, preprocessed_data.npz contains np.ndarrays (‘episode_starts’, ‘rewards’, ‘actions’)
  4. At the root of the dataset folder, ground_truth.npz contains np.ndarrays (‘target_positions’, ‘ground_truth_states’, ‘images_path’)

The exact format for each np.ndarray can be found in the example dataset (or in the RL Repo). Note: the variables ‘arm_states’ and ‘button_positions’ were renamed ‘ground_truth_states’ and ‘target_positions’

SRL Server for Reinforcement Learning [Experimental]

This feature is currently experimental. It will launch a server that will learn a srl model and send a response to the RL client when it is ready.

python server.py