ray.rllib.policy.Policy.learn_on_batch

Policy.learn_on_batch(samples: ray.rllib.policy.sample_batch.SampleBatch) → Dict[str, Union[numpy.array, jnp.ndarray, tf.Tensor, torch.Tensor]]

Perform one learning update, given samples.

Either this method or the combination of compute_gradients and apply_gradients must be implemented by subclasses.

Parameters

samples – The SampleBatch object to learn from.

Returns

Dictionary of extra metadata from compute_gradients().

Examples

>>> policy, sample_batch = ... 
>>> policy.learn_on_batch(sample_batch)