OpenMLEnv

torchrl.envs.OpenMLEnv(*args, **kwargs)

An environment interface to OpenML data to be used in bandits contexts.

Doc: https://www.openml.org/search?type=data

Scikit-learn interface: https://scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_openml.html

Parameters:

• dataset_name (str) – the following datasets are supported: "adult_num", "adult_onehot", "mushroom_num", "mushroom_onehot", "covertype", "shuttle" and "magic".

• device (torch.device or compatible, optional) – the device where the input and output data is to be expected. Defaults to "cpu".

• batch_size (torch.Size or compatible, optional) – the batch size of the environment, ie. the number of elements samples and returned when a reset() is called. Defaults to an empty batch size, ie. one element is sampled at a time.

Variables:

available_envs (List[str]) – list of envs to be built by this class.

Examples

>>> env = OpenMLEnv("adult_onehot", batch_size=[2, 3])
>>> print(env.reset())
TensorDict(
    fields={
        done: Tensor(shape=torch.Size([2, 3, 1]), device=cpu, dtype=torch.bool, is_shared=False),
        observation: Tensor(shape=torch.Size([2, 3, 106]), device=cpu, dtype=torch.float32, is_shared=False),
        reward: Tensor(shape=torch.Size([2, 3, 1]), device=cpu, dtype=torch.float32, is_shared=False),
        y: Tensor(shape=torch.Size([2, 3]), device=cpu, dtype=torch.int64, is_shared=False)},
    batch_size=torch.Size([2, 3]),
    device=cpu,
    is_shared=False)