ray.rllib.policy.eager_tf_policy_v2.EagerTFPolicyV2.apply_gradients_fn#

EagerTFPolicyV2.apply_gradients_fn(optimizer: tf.keras.optimizers.Optimizer, grads: Union[List[Tuple[Union[numpy.array, jnp.ndarray, tf.Tensor, torch.Tensor], Union[numpy.array, jnp.ndarray, tf.Tensor, torch.Tensor]]], List[Union[numpy.array, jnp.ndarray, tf.Tensor, torch.Tensor]]]) → tf.Operation[source]#

Gradients computing function (from loss tensor, using local optimizer).

Parameters

  • optimizer – The tf (local) optimizer object to calculate the gradients with.

  • grads – The gradient tensor to be applied.

Returns

TF operation that applies supplied gradients.

Return type

“tf.Operation”