SST: docker build and run problem

My tensorflow and waymo version is:

tensorflow                    2.4.0
waymo-open-dataset-tf-2-4-0   1.4.1

Besides, I usually follow the following shell script to setup my environment:

pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple
pip install tensorflow==2.4.0
pip3 install waymo-open-dataset-tf-2-4-0 --user
pip install torch-1.8.0+cu111-cp38-cp38-linux_x86_64.whl
pip install torchvision-0.9.0+cu111-cp38-cp38-linux_x86_64.whl
cd ./mmcv-1.3.9
TORCH_CUDA_ARCH_LIST="8.6" MMCV_WITH_OPS=1 pip install -e .
cd ..
pip install mmdet==2.14.0
pip install mmsegmentation==0.14.1
cd ./SST
pip install -e .

Hope it helps.

My environment is:

cumm-cu113                    0.3.4
mmcv-full                     1.3.9              
mmdet                         2.14.0
mmdet3d                       0.15.0            
mmsegmentation                0.14.1
spconv-cu113                  2.2.3
torch                         1.8.0+cu111
torchvision                   0.9.0+cu111
torch-scatter                 2.0.9

For the data, it is generated by the official MMDet3D script: ./tools/create_data.py. For this part, you could follow the instructions of MMDet3Dv0.15.

For idx2timestamp.pkl, please follow https://github.com/tusen-ai/SST/blob/main/docs/overall_instructions.md#fast-waymo-evaluation