Remove redundant slicing operation in Diffusion Policy (#240)

Author: alexander-soare

lerobot/common/policies/diffusion/modeling_diffusion.py

@@ -239,10 +239,8 @@ def generate_actions(self, batch: dict[str, Tensor]) -> Tensor:
         global_cond = torch.cat([batch["observation.state"], img_features], dim=-1).flatten(start_dim=1)
 
         # run sampling
-        sample = self.conditional_sample(batch_size, global_cond=global_cond)
+        actions = self.conditional_sample(batch_size, global_cond=global_cond)
 
-        # `horizon` steps worth of actions (from the first observation).
-        actions = sample[..., : self.config.output_shapes["action"][0]]
         # Extract `n_action_steps` steps worth of actions (from the current observation).
         start = n_obs_steps - 1
         end = start + self.config.n_action_steps