error in evaluation

[fyyyym]

When performing python tools/test.py projects/configs/SparseOccVLA/sparseoccvla_stage3_4d_600q_forecasting.py ckpts/stage3_4d_600q_forecasting.pth --eval_occ ,the following error occurs. Does it matter? How to correct it
The model and loaded state dict do not match exactly
unexpected key in source state_dict: lm_head.language_model.model.layers.0.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.0.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.0.attention.rotary_emb.sin_cached, lm_head.language_model.model.layers.1.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.1.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.1.attention.rotary_emb.sin_cached, lm_head.language_model.model.layers.2.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.2.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.2.attention.rotary_emb.sin_cached, lm_head.language_model.model.layers.3.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.3.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.3.attention.rotary_emb.sin_cached, lm_head.language_model.model.layers.4.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.4.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.4.attention.rotary_emb.sin_cached, lm_head.language_model.model.layers.5.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.5.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.5.attention.rotary_emb.sin_cached, lm_head.language_model.model.layers.6.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.6.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.6.attention.rotary_emb.sin_cached, lm_head.language_model.model.layers.7.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.7.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.7.attention.rotary_emb.sin_cached, lm_head.language_model.model.layers.8.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.8.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.8.attention.rotary_emb.sin_cached, lm_head.language_model.model.layers.9.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.9.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.9.attention.rotary_emb.sin_cached, lm_head.language_model.model.layers.10.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.10.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.10.attention.rotary_emb.sin_cached, lm_head.language_model.model.layers.11.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.11.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.11.attention.rotary_emb.sin_cached, lm_head.language_model.model.layers.12.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.12.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.12.attention.rotary_emb.sin_cached, lm_head.language_model.model.layers.13.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.13.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.13.attention.rotary_emb.sin_cached, lm_head.language_model.model.layers.14.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.14.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.14.attention.rotary_emb.sin_cached, lm_head.language_model.model.layers.15.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.15.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.15.attention.rotary_emb.sin_cached, lm_head.language_model.model.layers.16.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.16.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.16.attention.rotary_emb.sin_cached, lm_head.language_model.model.layers.17.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.17.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.17.attention.rotary_emb.sin_cached, lm_head.language_model.model.layers.18.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.18.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.18.attention.rotary_emb.sin_cached, lm_head.language_model.model.layers.19.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.19.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.19.attention.rotary_emb.sin_cached, lm_head.language_model.model.layers.20.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.20.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.20.attention.rotary_emb.sin_cached, lm_head.language_model.model.layers.21.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.21.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.21.attention.rotary_emb.sin_cached, lm_head.language_model.model.layers.22.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.22.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.22.attention.rotary_emb.sin_cached, lm_head.language_model.model.layers.23.attention.rotary_emb.inv_freq, lm_head.language_model.model.layers.23.attention.rotary_emb.cos_cached, lm_head.language_model.model.layers.23.attention.rotary_emb.sin_cached

[fyyyym]

meanwhile,the dataloader pipeline can not load correct number of frames. return self.simple_test_online(img_metas, img, rescale, **data)
File "/root/private_data/SparseOccVLA-main/projects/mmdet3d_plugin/models/detectors/sparseoccvla.py", line 845, in simple_test_online
img_feats_curr = self.extract_feat(img[:, i], img_metas_curr)
IndexError: index 1 is out of bounds for dimension 1 with size 1