Import failed after updating from version 4.0 to version 4.1

[Joey]

@stephan

• Load the cryoSPARC worker environment (for execution of the following commands):
  eval $(<path-to-cryosparc_worker>/bin/cryosparcw env)
• CUDA toolkit path:
  echo $CRYOSPARC_CUDA_PATH
• CUDA toolkit version:
  ${CRYOSPARC_CUDA_PATH}/bin/nvcc --version
• pycuda information (run command in same shell):
  python -c "import pycuda.driver; print(pycuda.driver.get_version())"
• Output of
  uname -a && free -g && nvidia-smi

1. eval $(<path-to-cryosparc_worker>/bin/cryosparcw env):
   I executed eval $(/Share/THUDATA/Softwares/cryosparc/cryosparc2_worker/bin/cryosparcw env) and nothing happened.

2. echo $CRYOSPARC_CUDA_PATH:

output: /Share/THUDATA/Softwares/cuda-10.2

3. ${CRYOSPARC_CUDA_PATH}/bin/nvcc --version

output:

nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Wed_Oct_23_19:24:38_PDT_2019
Cuda compilation tools, release 10.2, V10.2.89

4. python -c "import pycuda.driver; print(pycuda.driver.get_version())"

output: (10, 2, 0)

5. uname -a && free -g && nvidia-smi

output:

Linux gpu01 3.10.0-957.el7.x86_64 #1 SMP Thu Oct 4 20:48:51 UTC 2018 x86_64 x86_64 x86_64 GNU/Linux
total used free shared buff/cache available
Mem: 376 60 188 1 126 312
Swap: 47 0 47
Sat Dec 17 15:32:00 2022
±----------------------------------------------------------------------------+
| NVIDIA-SMI 440.33.01 Driver Version: 440.33.01 CUDA Version: 10.2 |
|-------------------------------±---------------------±---------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 Tesla V100-SXM2… Off | 00000000:1A:00.0 Off | 0 |
| N/A 55C P0 84W / 300W | 32016MiB / 32510MiB | 100% Default |
±------------------------------±---------------------±---------------------+
| 1 Tesla V100-SXM2… Off | 00000000:1C:00.0 Off | 0 |
| N/A 46C P0 80W / 300W | 28490MiB / 32510MiB | 100% Default |
±------------------------------±---------------------±---------------------+
| 2 Tesla V100-SXM2… Off | 00000000:1D:00.0 Off | 0 |
| N/A 43C P0 76W / 300W | 30514MiB / 32510MiB | 100% Default |
±------------------------------±---------------------±---------------------+
| 3 Tesla V100-SXM2… Off | 00000000:1E:00.0 Off | 0 |
| N/A 51C P0 82W / 300W | 30234MiB / 32510MiB | 100% Default |
±------------------------------±---------------------±---------------------+

±----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 16739 C …naconda3/envs/ZDH_SSK_torch/bin/python3 32003MiB |
| 1 16739 C …naconda3/envs/ZDH_SSK_torch/bin/python3 28477MiB |
| 2 16739 C …naconda3/envs/ZDH_SSK_torch/bin/python3 30501MiB |
| 3 16739 C …naconda3/envs/ZDH_SSK_torch/bin/python3 30221MiB |
±----------------------------------------------------------------------------+

BTW, the gpu device where I ran the command above is occupied by a running program, so the nvidia-smi command get the information above, which is not an error.