(self, obs_dict, hist_encoding: bool, obs_key="actor_obs", target_key="future_motion_targets")
| 68 | return priv_embedding |
| 69 | |
| 70 | def forward(self, obs_dict, hist_encoding: bool, obs_key="actor_obs", target_key="future_motion_targets"): |
| 71 | motion_embedding = self.motion_encoding(obs_dict[target_key]) |
| 72 | |
| 73 | if hist_encoding: |
| 74 | latent = self.history_encoding(obs_dict["prop_history"]) |
| 75 | else: |
| 76 | latent = self.priv_encoding(obs_dict["priv_obs"]) |
| 77 | |
| 78 | actor_obs = torch.cat([obs_dict[obs_key], motion_embedding, latent], dim=-1) |
| 79 | backbone_output = self.actor_module(actor_obs) |
| 80 | return backbone_output |
| 81 | |
| 82 | |
| 83 | class ActorCritic(nn.Module): |
nothing calls this directly
no test coverage detected