Unable to run evaluation

[Wenbo Gou]

Hi! It's a great work! We are trying to run through the evaluation code but found the released checkpoint panoptic_tempo_cam5.pth for evaluation does not match with the provided config file: configs/panoptic/resnet_rnn_panoptic_cam5.py

The errors are :
NCCL_P2P_DISABLE=1 tools/dist_test.sh ./configs/panoptic/resnet_rnn_panoptic_cam5.py ./checkpoints/panoptic_tempo_cam5.pth 1

warnings.warn(
Loaded seq: 160906_pizza1
Loaded seq: 160422_haggling1
Loaded seq: 160906_ian5
Loaded seq: 160906_band4
=> load 0 samples
/home/haoye/anaconda3/envs/tempo/lib/python3.9/site-packages/mmcv/cnn/bricks/conv_module.py:153: UserWarning: Unnecessary conv bias before batch/instance norm
warnings.warn(
load checkpoint from local path: ./checkpoints/panoptic_tempo_cam5.pth
The model and loaded state dict do not match exactly

unexpected key in source state_dict: backbone.keypoint_head.final_layer.weight, backbone.keypoint_head.final_layer.bias, human_detector.forecast_net.spatial_grus.0.layer_norm2d.weight, human_detector.forecast_net.spatial_grus.0.layer_norm2d.bias, human_detector.forecast_net.spatial_grus.0.conv_update.weight, human_detector.forecast_net.spatial_grus.0.conv_update.bias, human_detector.forecast_net.spatial_grus.0.conv_reset.weight, human_detector.forecast_net.spatial_grus.0.conv_reset.bias, human_detector.forecast_net.spatial_grus.0.conv_state_tilde.conv.weight, human_detector.forecast_net.spatial_grus.0.conv_state_tilde.norm.weight, human_detector.forecast_net.spatial_grus.0.conv_state_tilde.norm.bias, human_detector.forecast_net.spatial_grus.0.conv_state_tilde.norm.running_mean, human_detector.forecast_net.spatial_grus.0.conv_state_tilde.norm.running_var, human_detector.forecast_net.spatial_grus.0.conv_state_tilde.norm.num_batches_tracked, human_detector.forecast_net.spatial_grus.1.layer_norm2d.weight, human_detector.forecast_net.spatial_grus.1.layer_norm2d.bias, human_detector.forecast_net.spatial_grus.1.conv_update.weight, human_detector.forecast_net.spatial_grus.1.conv_update.bias, human_detector.forecast_net.spatial_grus.1.conv_reset.weight, human_detector.forecast_net.spatial_grus.1.conv_reset.bias, human_detector.forecast_net.spatial_grus.1.conv_state_tilde.conv.weight, human_detector.forecast_net.spatial_grus.1.conv_state_tilde.norm.weight, human_detector.forecast_net.spatial_grus.1.conv_state_tilde.norm.bias, human_detector.forecast_net.spatial_grus.1.conv_state_tilde.norm.running_mean, human_detector.forecast_net.spatial_grus.1.conv_state_tilde.norm.running_var, human_detector.forecast_net.spatial_grus.1.conv_state_tilde.norm.num_batches_tracked, human_detector.forecast_net.spatial_grus.2.layer_norm2d.weight, human_detector.forecast_net.spatial_grus.2.layer_norm2d.bias, human_detector.forecast_net.spatial_grus.2.conv_update.weight, human_detector.forecast_net.spatial_grus.2.conv_update.bias, human_detector.forecast_net.spatial_grus.2.conv_reset.weight, human_detector.forecast_net.spatial_grus.2.conv_reset.bias, human_detector.forecast_net.spatial_grus.2.conv_state_tilde.conv.weight, human_detector.forecast_net.spatial_grus.2.conv_state_tilde.norm.weight, human_detector.forecast_net.spatial_grus.2.conv_state_tilde.norm.bias, human_detector.forecast_net.spatial_grus.2.conv_state_tilde.norm.running_mean, human_detector.forecast_net.spatial_grus.2.conv_state_tilde.norm.running_var, human_detector.forecast_net.spatial_grus.2.conv_state_tilde.norm.num_batches_tracked, human_detector.forecast_net.res_blocks.0.0.layers.conv_down_project.weight, human_detector.forecast_net.res_blocks.0.0.layers.abn_down_project.0.weight, human_detector.forecast_net.res_blocks.0.0.layers.abn_down_project.0.bias, human_detector.forecast_net.res_blocks.0.0.layers.abn_down_project.0.running_mean, human_detector.forecast_net.res_blocks.0.0.layers.abn_down_project.0.running_var, human_detector.forecast_net.res_blocks.0.0.layers.abn_down_project.0.num_batches_tracked, human_detector.forecast_net.res_blocks.0.0.layers.conv.weight, human_detector.forecast_net.res_blocks.0.0.layers.abn.0.weight, human_detector.forecast_net.res_blocks.0.0.layers.abn.0.bias, human_detector.forecast_net.res_blocks.0.0.layers.abn.0.running_mean, human_detector.forecast_net.res_blocks.0.0.layers.abn.0.running_var, human_detector.forecast_net.res_blocks.0.0.layers.abn.0.num_batches_tracked, human_detector.forecast_net.res_blocks.0.0.layers.conv_up_project.weight, human_detector.forecast_net.res_blocks.0.0.layers.abn_up_project.0.weight, human_detector.forecast_net.res_blocks.0.0.layers.abn_up_project.0.bias, human_detector.forecast_net.res_blocks.0.0.layers.abn_up_project.0.running_mean, 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load model from: ./checkpoints/panoptic_tempo_cam5.pth, to the whole model!
completed: 0, elapsed: 0soutputs: []
Traceback (most recent call last):
File "/home/haoye/codes_wenbo/tempo/tools/test.py", line 187, in
main()
File "/home/haoye/codes_wenbo/tempo/tools/test.py", line 181, in main
results = dataset.evaluate(outputs, cfg.work_dir, **eval_config)
File "/home/haoye/anaconda3/envs/tempo/lib/python3.9/site-packages/mmcv/utils/misc.py", line 340, in new_func
output = old_func(*args, **kwargs)
File "/home/haoye/codes_wenbo/tempo/tempo/datasets/body3d_mview_temporal_panoptic_dataset.py", line 346, in evaluate
pose_3ds = np.concatenate([result['pose_3d'] for result in results],
ValueError: need at least one array to concatenate
ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 0 (pid: 8277) of binary: /home/haoye/anaconda3/envs/tempo/bin/python

---

what might go wrong and what's the correct matching between config and the released checkpoint? Many thanks!