File /home/username/anaconda3/envs/deeplabcut-2.3.10/lib/python3.10/site-packages/deeplabcut/pose_estimation_pytorch/apis/train.py:189, in train(loader, run_config, task, device, gpus, logger_config, snapshot_path, transform, inference_transform, max_snapshots_to_keep)
    186 else:
    187     logging.info("\nStarting pose model training...\n" + (50 * "-"))
--> 189 runner.fit(
    190     train_dataloader,
    191     valid_dataloader,
    192     epochs=run_config["train_settings"]["epochs"],
    193     display_iters=run_config["train_settings"]["display_iters"],
    194 )

File /home/username/anaconda3/envs/deeplabcut-2.3.10/lib/python3.10/site-packages/deeplabcut/pose_estimation_pytorch/runners/train.py:181, in TrainingRunner.fit(self, train_loader, valid_loader, epochs, display_iters)
    179 with torch.no_grad():
    180     logging.info(f"Training for epoch {e} done, starting evaluation")
--> 181     valid_loss = self._epoch(
    182         valid_loader, mode="eval", display_iters=display_iters
    183     )
    184     if self._print_valid_loss:
    185         msg += f", valid loss {float(valid_loss):.5f}"

File /home/username/anaconda3/envs/deeplabcut-2.3.10/lib/python3.10/site-packages/deeplabcut/pose_estimation_pytorch/runners/train.py:221, in TrainingRunner._epoch(self, loader, mode, display_iters)
    219 loss_metrics = defaultdict(list)
    220 for i, batch in enumerate(loader):
--> 221     losses_dict = self.step(batch, mode)
    222     epoch_loss.append(losses_dict["total_loss"])
    224     for key in losses_dict.keys():

File /home/username/anaconda3/envs/deeplabcut-2.3.10/lib/python3.10/site-packages/deeplabcut/pose_estimation_pytorch/runners/train.py:346, in PoseTrainingRunner.step(self, batch, mode)
    337     self._update_epoch_predictions(
    338         name="bodyparts",
    339         paths=batch["path"],
   (...)
    343         scales=batch["scales"],
    344     )
    345     if "unique_bodypart" in predictions:
--> 346         self._update_epoch_predictions(
    347             name="unique_bodyparts",
    348             paths=batch["path"],
    349             gt_keypoints=batch["annotations"]["keypoints_unique"],
    350             pred_keypoints=predictions["unique_bodypart"]["poses"],
    351             offsets=batch["offsets"],
    352             scales=batch["scales"],
    353         )
    355 return {k: v.detach().cpu().numpy() for k, v in losses_dict.items()}

File /home/username/anaconda3/envs/deeplabcut-2.3.10/lib/python3.10/site-packages/deeplabcut/pose_estimation_pytorch/runners/train.py:422, in PoseTrainingRunner._update_epoch_predictions(self, name, paths, gt_keypoints, pred_keypoints, scales, offsets)
    420 keypoints = ground_truth[batch_id]
    421 for kpts in keypoints:
--> 422     vis = kpts[-1]
    423     if vis < 0:
    424         kpts[-1] = 0

IndexError: invalid index to scalar variable.