Calculates an update used by some Bandit algorithms.
tf_agents.bandits.agents.utils.sum_reward_weighted_observations(
r: tf_agents.typing.types.Tensor,
x: tf_agents.typing.types.Tensor
) -> tf_agents.typing.types.Tensor
Given an observation x and corresponding reward r, the weigthed
observations vector (denoted b here) should be updated as b = b + r * x.
This function calculates the sum of weighted rewards for batched
observations x.
Args |
|---|
r
|
a Tensor of shape [batch_size]. This is the rewards of the batched
observations.
|
x
|
a Tensor of shape [batch_size, context_dim]. This is the matrix
with the (batched) observations.
|
Returns |
|---|
The update that needs to be added to b. Has the same shape as b.
If the observation matrix x is empty, a zero vector is returned.
|
View source on GitHub