only call .detach().cpu() once per caemra instead of once per image

src/lerobot/policies/evo1/modeling_evo1.py

@@ -342,10 +342,15 @@ class EVO1Policy(PreTrainedPolicy):
         image_batches: list[list[Tensor]] = []
         image_masks = torch.zeros(batch_size, self.config.max_views, dtype=torch.bool)
 
+        cpu_images: dict[str, Tensor] = {
+            camera_key: normalized[camera_key].detach().cpu()
+            for camera_key in camera_keys[: self.config.max_views]
+        }
+
         for batch_index in range(batch_size):
             sample_images: list[Tensor] = []
             for camera_key in camera_keys[: self.config.max_views]:
-                sample_images.append(normalized[camera_key][batch_index].detach().cpu())
+                sample_images.append(cpu_images[camera_key][batch_index])
             if not sample_images:
                 raise ValueError("EVO1 received a batch without any image tensor.")
             while len(sample_images) < self.config.max_views: