dimension error

[Stangerine]

/home/a/miniconda3/envs/zzq_sot/lib/python3.10/site-packages/mmcv/init.py:20: UserWarning: On January 1, 2023, MMCV will release v2.0.0, in which it will remove components related to the training process and add a data transformation module. In addition, it will rename the package names mmcv to mmcv-lite and mmcv-full to mmcv. See https://github.com/open-mmlab/mmcv/blob/master/docs/en/compatibility.md for more details. warnings.warn( config loaded. train dataset: size=37 inp: shape=(3, 1024, 1024) gt: shape=(1, 1024, 1024) val dataset: size=24 inp: shape=(3, 1024, 1024) gt: shape=(1, 1024, 1024) inp_rgb: shape=(3, 1024, 1024) model: #params=224.5M model_grad_params: 3943789 model_total_params: 224512925 model_grad_params: 3943789 train: 0%| | 0/37 [00:00<?, ?it/s]Traceback (most recent call last): File "/data/zzq/object_tracking/SAM-Adapter-PyTorch/train.py", line 257, in main(config, save_path) File "/data/zzq/object_tracking/SAM-Adapter-PyTorch/train.py", line 175, in main train_loss_G = train(train_loader, model) File "/data/zzq/object_tracking/SAM-Adapter-PyTorch/train.py", line 123, in train model.optimize_parameters() File "/data/zzq/object_tracking/SAM-Adapter-PyTorch/models/sam.py", line 395, in optimize_parameters self.forward() File "/data/zzq/object_tracking/SAM-Adapter-PyTorch/models/sam.py", line 245, in forward low_res_masks, iou_predictions,sam_output_tokens,object_score_logits, = self.mask_decoder( File "/home/a/miniconda3/envs/zzq_sot/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "/home/a/miniconda3/envs/zzq_sot/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl return forward_call(*args, **kwargs) File "/data/zzq/object_tracking/SAM-Adapter-PyTorch/models/mmseg/models/sam/mask_decoder.py", line 137, in forward masks, iou_pred, mask_tokens_out, object_score_logits = self.predict_masks( File "/data/zzq/object_tracking/SAM-Adapter-PyTorch/models/mmseg/models/sam/mask_decoder.py", line 207, in predict_masks src = src + dense_prompt_embeddings RuntimeError: The size of tensor a (128) must match the size of tensor b (256) at non-singleton dimension 1