alibi.models.tensorflow.actor_critic module
This module contains the Tensorflow implementation of actor-critic networks used in the Counterfactual with Reinforcement Learning for both data modalities. The models’ architectures follow the standard actor-critic design and can have broader use-cases.
- class alibi.models.tensorflow.actor_critic.Actor(hidden_dim, output_dim, **kwargs)[source]
Bases:
Model
Actor network. The network follows the standard actor-critic architecture used in Deep Reinforcement Learning. The model is used in Counterfactual with Reinforcement Learning (CFRL) for both data modalities (images and tabular). The hidden dimension used for the all experiments is 256, which is a common choice in most benchmarks.
- class alibi.models.tensorflow.actor_critic.Critic(hidden_dim, **kwargs)[source]
Bases:
Model
Critic network. The network follows the standard actor-critic architecture used in Deep Reinforcement Learning. The model is used in Counterfactual with Reinforcement Learning (CFRL) for both data modalities (images and tabular). The hidden dimension used for the all experiments is 256, which is a common choice in most benchmarks.